Mailbag: Deadly. Holy. Rough. Immediate.

A challenging question from reader David S. He quotes from and responds to an excerpt from Deadly. Holy. Rough. Immediate.

“Over very long periods, you will generally be paid based on the risks an average investor (including all of his liquidity sensitivities, his investment horizons, etc.) would be taking if he made that investment.” (from Deadly. Holy. Rough. Immediate.)

Isn’t this idea built on risk spreads, building up from the risk-free rate?  But in a world where central banks set risk-free rates for other reasons, is the concept of a risk-free rate even coherent?  In other words, does anyone really think Italian government debt is safer than U.S. government debt right now?

Again, it’s a useless theoretical question.  I think risk spreads work; will continue to work; and, even if I felt otherwise, I wouldn’t be foolish enough to try to predict the timing.  But how solid is the theoretical foundation on this one?

Over a sufficiently long horizon, I’d say it’s about a 6 out of 10 (which is about as good as it gets in this game).

There are probably more finance papers on the topic of the relationship between risk and return, or premia for the fancy among us, than any other. Many of them are purely empirical (e.g. what are the long-term Sharpe ratios of different asset classes over various horizons?). Many are purely theoretical (e.g. how should markets with mostly rational actors function to price risk?). Some are a bit of both (e.g. how much of variability in stock prices is driven by changes in expectations vs. changes in discount rates?). Even as a Hayekian who thinks that prices separate us from Communists and the animals, I’m kind of with you. To practitioners, the explanations and frameworks offered by these papers are often unsatisfying.

Over many very long horizons, the data will show you that the Sharpe ratios of major asset classes are similar. In other words, the relationship between the variability in price and long-term returns above a risk-free rate appears to be pretty consistent across assets. You’ll hear this factoid a lot in defense of the idea that long-term risk-adjusted returns of assets should be comparable if investors are at all rational. But this is one of those cases where I think we’ve got to be a little bit skeptical of a surprisingly geometric cow. One exaggerated example?

Commodities.

Their long-run Sharpe ratio is not far off from those of financial assets (this obviously depends on horizon – you’ve, uh, gotta go back for this one). But any sort of attempt to build a theory about why our return expectations for commodities should have anything to do with how volatile their prices are ends up looking like a dog chasing its tail. The practitioner sees this, because he sees how much of a commodity’s price changes are directly driven by non-economic actors, substitutability, seasonality, weather, extraction costs, storage costs, hedgers, etc. Plus, y’know, supply and demand.

This is part of the reason why many practitioners do NOT treat commodities – and this includes things like Bitcoin and other cryptocurrencies, by the way – as investable asset classes. We may have some expectation of their rise, but it is hard to determine in any meaningful theoretical way why we should expect to be paid with returns in any proportion to the risks we are taking on by owning them. Incidentally, I don’t think you need to believe there is a commodity risk premium to justify holding commodities in a portfolio. I would say the same thing about cryptocurrencies if I believed there was a state of the world in which they wouldn’t be treated as a highly correlated speculative asset in any kind of sell-off event for risky assets.

This isn’t just a commodity phenomenon. To David’s point, I think it is obvious that there is a portion of the risk we take in owning financial assets – stocks, bonds and other claims on cash flows – that we probably ought not to expect to be paid for either, or at least for which the smooth, ‘rational actor’ transmission mechanism between risk and the price demanded for it is perhaps not-so-smooth. Low-vol phenomenon, anyone? A half dozen other premia? But prices for financial assets are also hilariously overdetermined. That means that if we line up all the things that influence those prices, we will explain them many times over. It’s a topic that occupies the entire lives and careers of people smarter and more dedicated to the subject than I am, so I hesitate to give it the short shrift I am here. But in the interest of responding somewhat substantively, let me tell you in short what I think:

  • I think that the risk differences caused by placement in capital structure and leverage should have a pretty strong long-term relationship with return, because they describe an actual cash flow waterfall connected to economic reality. This is why I feel confident that I’m going to be paid some spread – even if it isn’t completely proportionate – for risks I take by owning risky financial assets.
  • I think that the risk differences caused by country and currency have a weaker relationship with return. You’ll be able to find examples where this isn’t true, but in general, capital markets still exhibit very local characteristics. Assuming that the differences in realized risk between markets in two countries will give us reliable information about how participants in those markets are pricing their relative risk may be pretty unrealistic.

In practice, I think that the first bullet alone is powerful enough to make it a foundational principle of portfolio construction. Perhaps the most important. I also think it is strong enough that it matters even if you think that a significant portion of price variability and movement is driven by abstraction, game-playing and narrative.

P.S. Folks, if you’re thinking about writing me that volatility isn’t risk, please don’t.

The Many Moods of Macro

I think the original version of this gag is from a Far Side comic in reference to Irish setters, although I’ve omitted it out of respect for Gary Larson’s wishes. Truth be told, I always felt that Old English Sheepdogs would have had a better case for “creature who looks more or less the same regardless of circumstance” than setters. I guess this is one of those things that is infinitely transferable to whatever kind of dog you had growing up.

Unless your childhood dog was a global macro portfolio manager, however, I suspect the rather monotonic flavor of their returns has puzzled you from time to time. For all its inputs, for all its data packaged together from far-flung corners of the globe, all synthesized into sensible and well-researched models, the typical macro fund’s positioning and success is heavily reliant on a small number of influential drivers and environments.

On the surface that’s not necessarily a bad thing, unless you’re paying a ton for it, which you probably are, even in 2018. After all, repeatability and persistent premia are not bugs, but features that we seek out from systematic investing. But for investors in systematic tactical strategies and global macro hedge funds, the expectation of persistent novel sources of return should be scrutinized. In a Three-Body Market, they should be doubted.

A horse having a wolf as a powerful and dangerous enemy lived in constant fear of his life. Being driven to desperation, it occurred to him to seek a strong ally. Whereupon he approached a man, and offered an alliance, pointing out that the wolf was likewise an enemy of the man. The man accepted the partnership at once and offered to kill the wolf immediately, if his new partner would only co-operate by placing his greater speed at the man’s disposal. The horse was willing, and allowed the man to place bridle and saddle upon him. The man mounted, hunted down the wolf, and killed him. The horse, joyful and relieved, thanked the man, and said: ‘Now that our enemy is dead, remove your bridle and saddle and restore my freedom.’ Whereupon the man laughed loudly and replied, ‘Never!’ and applied the spurs with a will.

— Isaac Asimov, Foundation (1951)

At their core, most macro models are central banking models and macro managers are carry investors. They willingly tied themselves to success in predicting bank actions, and in so doing had a wonderful stretch of good returns and low correlations with stocks. Now that predicting bank action will increasingly require short carry positioning, and now that betting on uncoordinated action has gotten tougher, they’re feeling the spurs. This is your choice, too: buck the rider or feel the spurs.


The impulse to find a “a man who can make a plan work”, from F.A. Hayek’s brilliant Road to Serfdom cartoons, is not just a political one, but infects the way we make decisions as investors. We make portfolio plans ourselves, with our committees or with our advisors, and they…rarely turn out exactly like we wanted.

We never have the best possible portfolio we could have had. There is no decision structure that won’t yield questions of the, “Well, why weren’t we 100% in U.S. growth stocks the last three years?” ilk from our clients. More often, we made some real mistakes. We misread the risk environment and weren’t fully invested for our clients. Knowing we shouldn’t, we gave up on a value strategy in a 7-year drawdown right before sentiment turned. We sold bonds ahead of what we thought were inevitable rate hikes and were wrong for five years.

We know we need to fix these kinds of errors.  Too often our solution is to find the team with a model that understands “how all this madness fits together” and can exploit it for us. That’s the allure of systematic macro and tactical asset allocation. It’s well-intended. It’s also a path paved with peril.


This is Part 1 of the multi-part Three-Body Alpha series, introduced in the recent Investing with Icarus note. The Series seeks to explore how the increasing transformation of fundamental and economic data into abstractions may influence strategies for investing — and how it should influence investors accessing them. 

After Ben wrote The Three-Body Problem, and then again with The Icarus Moment, I suspect I reacted like many other readers. I didn’t have to predict whether I thought asset prices were increasingly driven by abstractions or higher degree derivatives of economic and fundamental data, as Ben argued. I was observing it. But between those observations and the related belief that most alpha-oriented strategies have been forced into deeper levels of the Keynesian Newspaper Beauty Contest — that we are increasingly in the business of predicting what others are predicting others are predicting rather than the impact of changes in real economic facts — I have the same questions: How should this impact our strategies? Our portfolios? The questions we ask our advisers and fund managers?

These questions only matter if this whole state of affairs persists, of course. If there’s a hypothetical criticism you could level at the framework Ben and I are working from, it is that the Narrative-driven market isn’t really a thing, that it’s just a label we are throwing on a period of temporary loopiness created by central bank-driven hyperliquidity. A period that appears to be ending. If you think this is the case, then we’re the guys in burlap sacks on the street corner shouting, “This Time It’s Different” right before things go back to normal. I’m empathetic to the view. I mean, I think the view is wrong, but I’ve heard that people are comforted when you tell them you’re empathetic to their view.

I think it’s wrong because we aren’t just observing this in financial markets. We are observing polarization and quantization — rounding words and numbers to their nearest analog — in nearly every human social sphere. Our media-connected Panopticon converts every uttered word into a loaded ideological message, in which every action is a symbol in service to a Narrative. Yes, central bankers were the original missionaries in our little history, but CEOs, financial media, crypto-experts, senators, regulators, traders and other power brokers are all wise to the game now. So, if you want to tell me we will see a return to a market in which the transmission of economic data and fundamental characteristics of issuers manifests in asset prices over some meaningfully investable period of time, fine. But you’ll have to tell me why you think that’s going to happen in politics, culture and media, too.

The painful Catch-22 for the investment advice industry is that people expect times of uncertainty to be the opportunity for advisers to prove themselves. When I talk to financial advisers and RIAs in times of perceived dislocation in asset prices, they want to know whether they ought to transition some of their stock portfolio to hedge funds. They want to know if now is the time to allocate to long/short equity managers. They want to find someone who can steer exposure to take advantage of dispersion when the dislocation corrects. When geopolitical volatility doesn’t manifest in market risk, the conversation is similar. Investors want a macro strategist with a model that answers how it all fits together. Maybe it’s as simple as adding a tactical asset allocation overlay through one of the big turnkey platforms, or maybe it’s hiring a systematic global macro hedge fund. There’s finally dispersion again, and the beta rally is over — now go be tactical and find alpha!

Want to know why Ben’s notes Tell My Horse and Three-Body Problem each yielded more emails from fund managers, CIOs, pension executives and investment professionals than many notes combined? Because they don’t know exactly what to tell their clients who are looking for macro guidance. Because not only is this environment not turning out to be a goldilocks regime for tactical, cross-asset, alpha-seeking managers, it’s becoming an environment in which even the things that used to work aren’t working for them. At all.  Nowhere is that truer than in strategies sitting at the confluence of what in our framework we are calling Systematic strategies operating Economic models. Don’t believe me? Here’s the very long-cycle trend, seen through the lens of the HFRI Macro: Systematic Diversified Index.

Source: eVestment April 2018. An investor cannot invest directly in an index. For illustrative purposes only.

The systematic universe has a lot of trend-following funds. Many of those have performed quite poorly. But that isn’t all that’s happening here. Even the broader Global Macro category, represented here by the HFRI Macro (Total) Index, looks similar. We could similarly split the systematic category into those focused only on trend-following and those that are not, and it would tell the same story.

Source: eVestment April 2018. An investor cannot invest directly in an index. For illustrative purposes only.

What do we mean by “Econometric GTAA”?

The investment industry loves to obfuscate, and terminology can be a bear. Let’s cut through it.

In Hedge Fund Land, “Macro” — represented in the second chart above — is a term of art. Jargon. It refers to a universe of hedge funds, usually self-labeled, that pursue strategies that mostly allocate across and between different broadly defined assets. The term “Systematic Macro” simply refers to those which do so on a mostly systematic basis. By systematic, I mean that the trades are typically generated based on a system rather than determined by a human. That means different things for different funds, and many will have individual sleeves of the portfolio or elements of the portfolio’s construction that still come under human scrutiny. But in general, these funds trade based on generalized ideas and principles memorialized in code.

Depending on who you are talking to, you will also hear strategists, fund managers or consultants talk about “GTAA”, or Global Tactical Asset Allocation strategies. When a fund manager calls a strategy that allocates across assets GTAA instead of Macro, he usually means that he is willing to sell it to you for a lower price, often means that his trades will be confined to a defined, larger set of simple long and short expressions on broad asset classes, and sometimes means that he will have a general bias toward being long financial markets exposure. This is part of the universe I’m writing about here.

There’s a third category of strategies which are not precisely a sub-set of Systematic Macro, but at least occupy a big, overlapping part of the Venn diagram: Managed Futures and CTAs. This, again, is where terminology gets confusing. Managed Futures and CTAs are technically a structural category, by which I mean that they aren’t so much defined by what they do as by what they are. Because futures contracts were originally an instrument devised to trade commodities more efficiently, this industry and its structures formed around strategies for trading futures contracts on those commodities — which makes sense, since CTA stands for “Commodity Trading Advisor.” Over time, as extraordinarily liquid futures contracts became available in equities and interest rate markets, the CTA structures were able to accommodate strategies that looked almost exactly like what we’d see in a global macro hedge fund. But, as I noted in my quip above, this part of the universe tends to trade more often based on price trends, rather than what’s going on in the economy or in companies and other issuers.

So, we have three heavily overlapping Venn diagrams — Systematic Macro, GTAA and Managed Futures. But this piece is about strategies I’m labeling as Econometric GTAA. What do I mean? I mean strategies which trade long and short across a broad range of markets based on computer models driven by (and sometimes predicting the trajectory of and rates of change in) inflation, interest rates, asset flows, economic growth, corporate margins and earnings more broadly, tax rates, trade policy, balance of payments, and trade deficits, etc. These strategies will find their way into your portfolios in many ways. If you buy a Global Macro hedge fund, you will probably get a lot of this. If you hire a Managed Futures fund, you may get some of this, although as I mentioned, it is more likely to be driven by trend-following. If you buy a Multi-Strategy hedge fund, you will probably get a lot of this. But this isn’t just hedge funds. If you buy a “rotation” or “tactical” strategy from an ETF strategist or Tactical Asset Management Plan (TAMP), you will probably get a lot of this. If you hire a financial adviser from an institution with a home office that recommends asset allocation models, you are probably getting some muted flavors of this. So what do these strategies look like?

What Econometric GTAA Models Look Like

When you hire a “tactical” advisor or portfolio manager, while there is a huge amount of surface-level diversity, what you’re usually getting is some subset of the below:

Illustration of Typical Tactical Asset Allocation Framework

Source: Epsilon Theory April 2018. For illustrative purposes only.

The basic framework here takes in some combination of what I’m calling Econometric Data, Market Data and Sentiment. The mix may differ dramatically. In the case of Managed Futures strategies, many ETF strategists and “Tactical Allocation” funds, and others that call themselves Systematic Macro, models may skew entirely toward Market Data. They may even emphasize price movements above just about every other kind of input. This piece isn’t about those funds, and it isn’t about those strategies. It’s a big topic that deserves its own note, because most of the off-the-shelf model portfolios-in-a-box, ETF-based strategies, sector-rotation strategies and tactical allocation funds rely almost entirely on models driven by Market Data alone, usually simple valuation and momentum models.

But what we’re focused on is that top half — the Econometric Data. The approach that managers and strategists will take to incorporate these data will differ. In some cases, strategies will impute a direct transmission engine between econometric data and (implied) expected asset prices, and their desired position. For example, a strategy may be something as simple as rank-ordering countries by their short-term interest rates, buying the ones with higher rates and shorting the ones with lower rates. There are all sorts of implicit views this expresses on investor asset pricing behavior and risk, but the explicit mechanism for establishing positions connects relative interest rates to relative asset price returns over some period of time. This is what the illustration refers to as Implicit Price Behavior models — “Certain values of variable X will more often than not result in changes in the prices of asset price Y.”

In other cases, one or more (usually more) bits of data will be incorporated with economic logic into an interim model. That interim model will typically represent a more explicit simulation of the behavior of another actor or actor(s). For example, rather than estimate a simple relationship between, say, changes in consensus inflation expectations and whether inflation-linked bonds will outperform nominal bonds, many Econometric GTAA strategies will take in GDP growth, earnings growth, balance of payments, wage growth, producer price momentum, corporate margin and money supply data to predict the pressures on central banks to make changes in interest rate policy. That output would then influence views and positioning on a range of assets.

As with the bulk of tactical asset allocation strategies, ETF models, etc. mentioned earlier, the influence of these interim models or even many of the direct transmission models of Econometric Data to positions is often presented in context of valuation of the underlying assets, and momentum of the price of the underlying asset and/or the model’s signal itself. In other words, a fund may predict the pressure on a central bank to act, but it may be the momentum or change in that variable which produces a tradable signal. Alternatively, a trade may be conditioned on some valuation or momentum state, or even by the state of another interim model (i.e. “We trade when we have confirmation between our geopolitical framework and recent price action.”).

The types of positions these models establish will differ as well. For most strategies — especially those that fancy the GTAA moniker — the views tend to be long/short, and usually asset class neutral. For example, a model might pair a 5% long or overweight position in US stocks with a 5% short or underweight position in, say, German stocks. For others, the views might compare assets with cash. In other words, the models decide whether to have market exposure at all. This question of “directionality” is a big one. It’s one that tends to exaggerate differentness among practitioners of these strategies and pigeon-hole the emphasis of more risk-focused managers into a smaller number of relative value trades between assets.

But What is It, Really?

So with all these inputs, with all this diversity, we have our pick of a lot of interesting multi-asset and macro strategists with a lot of interesting different models, right?

Meh, not so much.

We don’t claim to have some secret sauce for analyzing drivers of fund performance. Most approaches are pretty well-trod ground at this point, although I was tempted to measure facial width-to-height ratios just for fun. But no, we’re simple — boring multi-factor regressions against some basic style and market factors. Fortunately, as is often the case, simplicity tells most of the story. Of the 74 funds in the HFRI Systematic Macro universe, 60 have positive, statistically significant betas to interest rates. Around 40 have betas higher than 1.0. These are betas in a multi-factor context that includes a range of market and traditional style factors. To be fair, many of these funds are implemented through futures or with market neutral positioning that allows them to earn cash returns, but this is a small portion of this effect. In the end, you are roughly three times more likely to run into a Systematic Macro fund with returns that look like a levered bet on interest rate-sensitive instruments than one that neutralized (read: hedged) the aggregate systematic influence of rates on its risk profile over time.

Source: Epsilon Theory, HFR, eVestment April 2018. An investor cannot invest directly in an index. For illustrative purposes only.

I don’t think this is an artifact or false positive from the data. Anecdotally, as I’ll argue, I think that many systematic macro funds really do execute strategies that are structurally biased toward being long bonds. But they also have a related bias. They like to own things where you collect a payment from someone else to own it. That someone else may be an issuer, a government or a hedger. Across macro funds, GTAA strategies and model portfolios, the only strategy that is as common as trend-following and a bond bias — systematic ones in particular — is buying higher yielding assets and selling lower yielding assets. We call these “carry trades”. Below are the significant betas (above and beyond the relationship to bonds) of each of the 74 funds to our measure of multi-asset carry trading. Most are positive, only a couple are negative, and the rest are largely positive but not significant after accounting for the existing carry component in their interest rate exposure.

Source: Epsilon Theory, HFR, eVestment April 2018. An investor cannot invest directly in an index. For illustrative purposes only.

Systematic Macro and Econometric GTAA funds have other systematic exposures as well, including a general bias toward short exposure in commodities, and a long bias toward equities, and these aren’t just present in the trend funds that have had those exposures because they have worked. They are common throughout.

If you talked about this with your tactical guy/gal or macro strategist, I know what he’s going to tell you, because it’s what they tell me, too. “There may be some of this, but we’re not directional. We may be long, we may be short, and we have a lot of other trades and signals.” I think you’ll find that this is sometimes completely true. For example, Bridgewater’s Pure Alpha strategy is consistently neutral to most market factors, although if you looked deeper into carry trades, you’d find a pretty persistent positioning in favor of higher yielding currencies. But generally speaking, your manager is telling you a half truth — literally. Across this universe, using static exposure to the most basic of market factors (stocks, bonds, commodities and currencies), you can explain around half of the variability in returns.  That’s not the problem, except that you’re paying them 1.5-and-20 for something you can and should get much cheaper. The problem is that after you take out the 50% you can explain with market factors, the hand-waving, black box, smoke-and-mirrors half they’re trying to sell you as their edge is a tire fire.

I mean, gods, look at this mess. Over the last five years, you would have gotten a positive Sharpe Ratio on whatever these guys did that wasn’t static long exposure to financial markets from only 23 of the 74 funds. Believe your model-driven macro guy when he tells you he isn’t only directionally long rates, -carry and trend-following. But be skeptical when he tells you that you ought to have a positive return expectation on whatever the other stuff he’s doing is.

Source: Epsilon Theory, HFR, eVestment April 2018. An investor cannot invest directly in an index. For illustrative purposes only.

The Many Moods of Macro

So how should we feel about the non-tire fire half of these returns — by which I mean the rates and carry half?

As I’ve alluded to above, the first mood of macro has always been betting on the behavior of central banks. There are a variety of reasons for that, but the first is that Systematic Macro, like other hedge fund strategies — and systematic ones in particular — is drawn to trades, strategies and markets with lower natural volatility. That means, generally, that positioning driven by the models will emphasize either directional exposure to lower volatility asset classes like bonds, or relative value trades (i.e. going long one asset and short a similar one). Importantly, it also means that the models will favor what they perceive as loosely correlated trades or positions. If you have better-than-random confidence in what central banks are likely to do, you have a full range of options to implement those views with characteristics that are attractive to a manager seeking to sell itself as limiting downside with significant uncorrelated upside. The other reason that funds were so fond of strategies reliant on their central bank behavioral models, of course, is that the models themselves were historically pretty effective.

But there’s another, more important reason for the attachment to central bank-driven econometric models. While most trades with significant upside potential and convexity require you to pay a premium — or be “short carry” — during the bond bull run of the last 30 years, a macro manager with a decent prediction model for the behaviors of central bank actions could put on trades with convex characteristics that paid him a positive carry over almost all of this three-decade span. For example, a prediction of a future rate cut would not only get the benefit of the signal but would also receive the term premium in an upward sloping rates curve, a premium that can be significant even in the front end of the curve.  Not only that, because central banks in different countries pursued frequently divergent policies with explicitly different inputs and aims, that manager could put on multiple such trades. And what’s more, these positions were uncorrelated to most portfolios’ primary sources of risk — we were living in a golden age!

This preference for long carry positioning is itself, I think, the second constant mood of macro. While it has historically manifested in part as a willingness to carry a directionally long bias in bonds, it also manifests in a preference for anything that pays you more to own it than something else. In Systematic Macro funds, you will see this in models which — from a variety of econometric inputs — ended up with a consistent preference for higher carry currencies, especially certain emerging markets currencies. The underlying model mechanics might differ. For example, the “emerging markets balance sheet quality” thinkpiece was a staple of the mid-2000s. The story went that the higher yields you earned for owning — I don’t know, Turkish lira — were compensation for perceived risk, but that the econometric support for fiscal stability and quality meant that the real risk of permanent capital loss was far lower. There are a hundred models with rationale like this that all lead to a pronounced bias toward carry.

The third ubiquitous mood of macro is pro-trend, and in particular, medium-to-long-term trend following. I’ve noted that much of the Systematic Macro universe overlaps with Managed Futures and CTAs that have made trend-following their bread and butter, but even among Econometric GTAA strategies, it is quite common to use trends and momentum to drive positions or to condition other models. It is, perhaps, even more common to measure trends in the econometric variables as strategies or factors of their own. Systematic models will also be driven toward pro-momentum stances by their risk management techniques. Because positive returning assets are generally lower volatility assets, things that have done well will tend to score well when the portfolios are being built, even if there is no explicit model saying, “Buy stuff that’s going up!” Beyond that, because many of these funds added implicit or explicit stop-loss logic in 2009, even among funds I would qualitatively (and subjectively) describe as following Econometric GTAA strategies, you can frequently explain much of the variation in returns with price momentum across asset classes of various horizons.

All of this is, incidentally, also why so many of your discretionary macro managers have spent the last two decades trotting out their Eurodollar guys to meet with you. They’re the guys who got paid to bet on central bank actions with diversifying, pro-momentum, carry-paying trades.

Systematic Macro in Three-Body Markets

Now, I don’t have much to say about whether I think that carry trades and momentum trades will work — or at least I don’t have much to say in this note. Suffice it to say that there are good behavioral and empirical reasons to think that they are persistent premia that compensate investors for bearing a certain type of risk, and also good reasons to think that may manifest somewhat differently in markets driven by Narrative abstractions. These are topics for another note.

But I do think it is clear that Econometric GTAA strategies have struggled mightily to adapt to a Narrative-driven market with everything else they are doing. When I have met with strategists and macro funds over the last few years, their language has been static. They walk me through the economic nonsense of negative interest rates and the upside asymmetry created by the zero barrier. They describe how relative growth rates, debt levels, deficits and trade balances cannot possibly support the relative yields of Treasuries and Bunds. They present compelling cases for curve trades between European markets that should converge given influences on ECB asset purchases, or for relative outperformance of this equity market over that because of the extension of corporate margins beyond some historical threshold for some historically long period of time. In other words, the Explicit Behavior models from the illustrated earlier in this note are running through the old motions on what central banks, asset owners and governments are going to do, and none of them are working.

It’s not as if managers and strategists haven’t tried to adapt to a world in which these trade drivers are subsumed into central bank communications strategy and the utilitization of markets by political figures. But when the models driving your trading are built to understand the cost and transmission mechanisms of capital, and your asset prices are driven by how investors think other investors are responding to a stronger adverb in front of a maybe hawkish adjective, it’s got to be more than just adapting and updating your models. It’s recognizing that over an expanded time horizon, asset prices are being driven by a wholly separate set of variables.

What worries me more than anything, however, is that the ability of GTAA and macro strategies to access the moods that may still work (mostly models that end up looking like carry trades) may be limited by their construction and their design in the emerging environment. As macro and GTAA strategists adapt to rising interest rates and inflation, I think you’re going to see some of their models under strain. They will be under strain because their central bank behavior models will be shouting “short rates”, but their DNA, their risk management framework, and maybe even explicit pro-carry models — will be screaming “God, that short looks expensive. Are you sure?” This dependency — implied already in the assessment of sensitivity to bond markets — is real. Since 2000, the average Global Macro hedge fund has generated roughly 2.4x its average return in months where the discount rate was reduced, with almost no advantage during periods with a rising discount rate. I think we may be entering an environment in which the only things that have really worked for these funds get lost in the wash. In their place, I think investors can expect to get weaker, lower Sharpe strategies based on Market Data-driven positioning. A lot of momentum and value, and not much novel insight — in many cases, a very expensive balanced market portfolio with a value overlay.

What do I do if I’m an allocator?

  • I don’t put all my trust in a macro strategist or tactical manager’s econometric models to ‘figure this all out’.
  • I probably own fewer of these funds and have less of my portfolio invested in them in the aggregate.
  • I ask for a manager’s rates and FX attribution. If it’s positive for most of the 2000s and starts to sour and turn over in, say, 2013-2014 and hasn’t recovered, I take the plastic binding rings out and file the pitchbook away in that special Iron Mountain filing cabinet in the print room. You know, the one with the lock on it that the guy comes for every couple weeks?
  • I challenge my macro PMs to explain how their models might approach rates and FX trading differently when rates are rising and if central bank policy remains largely coordinated. If they say, “We’re not directional and have always been agnostic on long or short positions, so it wouldn’t be any different,” I do my most exaggerated eye roll, put my chin on my fist, bat my eyelashes and give ‘em my best ca. 1991 Glamour-Shots-at-the-mall smile until they tell the truth.
  • I actively seek out managers who are incorporating and increasing the role of sentiment analysis, investor asset flows, market structure and Narrative, and reducing the role of econometric models, whether explicitly or through a systematic process for rotating capital between models (or turning off models whose alpha has evaporated).
  • I actively seek out managers who have actually figured out multiple robust models for trading commodities effectively other than trend-following models.
  • I continue to invest with managers accessing Systematic Macro’s traditional moods, but I’m only willing to pay what those replicable strategies are worth.
  • I look for managers who act boldly but hold their views loosely — in a word, humility.

The last goes for you and me, too. We must be humble about our ability to make good predictions about asset prices and returns. In a Three-Body Market, we should be even more humble than usual. But blindly handing over the reins of our asset allocation decisions to impressive people who claim to have developed the one model that will unravel this market’s mysteries is not an act of humility. It’s the very same act of expedience that caused so many of these managers to saddle themselves and their strategies to central banks, and it is the reason they’re feeling the spurs today. Buck it — or feel the spurs yourself.

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Investing with Icarus

The wind blows where it wishes, and you hear the sound of it, but cannot tell where it comes from and where it goes.

The Bible, John 3:8

As Narrative abstractions — cartoons — become our short-hand for things that used to have meaning, our models become more and more untethered from the reality they seek to reproduce. When wind becomes the thing-that-makes-the-leaves-move, then wind becomes a bear rubbing his back on the bark.

He that breaks a thing to find out what it is has left the path of wisdom.

The Lord of the Rings, J.R.R. Tolkien

Pursuing better returns by uncovering absolute truths about the companies and governments we invest in is not a serious enterprise in the face of markets rife with Narrative abstractions. It is a smiley-faced lie, a right-sounding idea that doesn’t work, and which we know doesn’t work. Selling the idea that it does to clients is the territory of the raccoon and the coyote. We can pursue it, or we can do the right things for ourselves and our clients. But not both.

Disneyland is presented as imaginary in order to make us believe that the rest is real, whereas all of Los Angeles and the America that surrounds it are no longer real, but belong to the hyperreal order and to the order of simulation. It is no longer a question of a false representation of reality (ideology) but of concealing the fact that the real is no longer real…

Simulacra and Simulation, Jean Baudrillard (1981)

How does Wall Street maintain the respectability of dishonest businesses? By declaring victory over straw men — active management is dead! Hedge funds lost the Buffett bet, beta won! Risk parity / vol-targeting / AI funds / quant funds are to blame! If you must sell that L.A. is real, you must create Disneyland.

“All right,” said Susan. “I’m not stupid. You’re saying humans need… fantasies to make life bearable.”

REALLY? AS IF IT WAS SOME KIND OF PINK PILL? NO. HUMANS NEED FANTASY TO BE HUMAN. TO BE THE PLACE WHERE THE FALLING ANGELS MEETS THE RISING APE.

“Tooth fairies? Hogfathers? Little—”

YES. AS PRACTICE. YOU HAVE TO START OUT LEARNING TO BELIEVE THE LITTLE LIES.

“So we can believe the big ones?”

YES. JUSTICE. MERCY. DUTY. THAT SORT OF THING.

“They’re not the same at all!”

YOU THINK SO? THEN TAKE THE UNIVERSE AND GRIND IT DOWN TO THE FINEST POWDER AND SIEVE IT THROUGH THE FINEST SIEVE AND THEN SHOW ME ONE ATOM OF JUSTICE, ONE MOLECULE OF MERCY. AND YET — Death waved a hand. AND YET YOU ACT AS IF THERE IS SOME IDEAL ORDER IN THE WORLD, AS IF THERE IS SOME…SOME RIGHTNESS IN THE UNIVERSE BY WHICH IT MAY BE JUDGED.

“Yes, but people have got to believe that, or what’s the point—”

MY POINT EXACTLY.

Hogfather, Terry Pratchett (1997)

So long as the government requires financial markets to act as a utility, and so long as it makes more sense for big tech companies to hire evangelists than CEOs — until the farmer comes out with his gun – we have only a few choices:

  1. We can be raccoons: We can recognize the overwhelming influence of abstractions and continue to sell products and ideas that don’t.
  2. We can be coyotes: We can recognize the overwhelming influence of abstractions and DESIGN new products and ideas that don’t.
  3. We can be victims: We can let the raccoons and coyotes run rampant over the farm.
  4. We can insulate: We can push back from the table and try to do the things that aren’t abstractions. Real things. Physical things. Things that put spendable currency in our accounts.
  5. We can engage: We can do our best to think about how to change our investment strategies and processes to respond to abstraction-driven markets.

These aren’t mutually exclusive, although only two are worthwhile. Ben’s DNA is long vol, so he wrote about how to insulate. My DNA is short vol. This note is first in a series on how to engage.

Speaking of DNA, there are few fields of study I find as thrilling as the intersection of anthropology and genetic geneaology. What I mean by that is how people lived, died and moved, and how their cultures and lineages moved with them. Yes, if kicking off notes with the old King James didn’t give you enough of a hint, I’m a big hit at parties.

Some of the appeal of genetic anthropology comes from the simple pleasures it offers, like the satisfaction of watching white supremacist idiots discover that they are mutts just like the rest of us.

The second appeal is the grand scale of ancestry and human movement, even over cosmologically infintestimal periods of time. This appeal is timeless. For example, in a legend common to three of the world’s great religions, God promises to multiply Abraham’s descendants as the stars of the heaven and as the sand on the seashore. It’s a pretty attractive promise, but temper your excitement — it was a reward for being a hair’s breadth away from murdering his son. The promises are poetic, of course, but the scope of the two is surprisingly different.

There are somewhere around 100 billion to one trillion stars in the Milky Way, an estimate which would vary based on how you estimated the galaxy’s total mass through the gravity it exerted and based on what you assumed was the average type of star. We’ve discovered a Wolf-Rayet star in the Magellanic Cloud with mass perhaps 300 times that of our sun, for example. It is so much larger than our sun that its surface would reach almost a third of the current distance to Mercury. Icarus wouldn’t stand a chance. On the other hand, we’ve discovered a red dwarf only 19 light-years away with less than 10% of the mass of the sun. But the 100 billion to one trillion range is a fair estimate. Earth has already seen 100 billion human lives. It will (hopefully) see its trillionth at some point between the year 2500 and 3000, if y’all could stop killing each other. Still, if you’re willing to ignore that we can see stars from other galaxies, too, I think we can prematurely give this one to Abraham.

As for the sand, there are about seven or eight quintillion grains on the earth. There’s just no way, even if Elon manages to get us off this planet before the next mass extinction event.

Interestingly, if you look backward, that isn’t quite true. When it comes to lineage, exponential math doesn’t always work going forward. One couple dies without any offspring, while another has a dozen children. But it always works going backward. Everyone has two parents and four grandparents. Based on most of those traditions holding that Abraham lived around 2,000 BC, we can estimate that the average living person has about 1.5 quindecillion ancestors from that time. Given that there were only about 72 million people alive at the time, that means that each of those individuals, on average, shows up in your family tree about 20 duodecillion times. That’s a 20 with 39 zeros. Congratulations! Math is amazing, and you are inbred.

The third appeal is that the really interesting findings are new. Very new. Anthropologists, of course, have theorized about the propagation and spread of cultures through comparative review of ancient art, tools, jewelry, burial sites and artifacts for centuries. Linguists can lean on anthropological techniques, but can also compare similar or derived grammar, vocabulary, and the like to identify how languages originated and spread. Maybe even some sense of where they came from. DNA has been used to develop and cultivate theories about human migrations and the spread of cultures for a shorter time, but in earnest starting in the late 1990s into the early 2000s. These studies have principally relied on the DNA of living individuals. Scientists examine current populations and theorize how ancient populations would have had to migrate to create the current distribution of various genetic admixtures — archetypes of varying compositions that can be generalized, like “Near Eastern Farmers.”

But in the last five years, the real excitement has been in the enrichment and analysis of ancient DNA. That means that, instead of just looking at modern populations and developing models to predict how they may have gotten there, we instead may look at the actual DNA of people who lived and died in some place in the distant past. We don’t have to guess how people moved and where they came from based on second-hand sources, like the DNA of people living in the same place thousands of years later, or on the pottery that they left behind.

We can know the truth.

Desperate for Wind

The allure of a fundamental truth is powerful. It’s the draw of science, and it’s a good thing. Understanding the true physical properties of materials and substances, for example, is the foundation of just about every good thing in our world. I mean, except for justice, mercy, duty, that sort of thing. We have the food we eat because those who went before discovered human chemical and enzymatic processes for digestion, and learned the mineral, chemical, water and solar needs for the plants that would be digestible. We have the devices we carry in our pockets because many thousands of researchers, designers and other scientists discovered the electrical conductivity of copper, the thermal conductivity of aluminum, the fracture toughness of various types of glass and a million other things.

I grew up around this kind of thinking. My dad worked for the Dow Chemical Company for some 40 years. Most of that time he spent as a maintenance engineer, an expert in predicting and accounting for the potential failure of devices and equipment used in the production (mostly) of polyethylene. His professional life’s work was perfecting the process of root-cause analysis. There may not be anyone in the world who knows more about how and why a furnace in a light hydrocarbons facility might fail. It may sound hyperspecialized, but that kind of laser-focused search for truth is something I took and take a lot of pride in.

Investors are hungry for that kind of clarity about markets. But it doesn’t exist. In The Myth of Market In-Itself, I wrote about investors’ vain obsession with finding root causes in media, economic news and Ks and Qs. Ben recently wrote about it pseudo-pseudonymously as Neb Tnuh, mourning the conversion of Real Things into cartoons, crude abstractions that investors are forced to treat like the authentic article:

Do I invest on the basis of reality, meaning the fact that wage inflation is, in fact, picking up in a remarkably steady fashion in the real economy? Or do I invest on the basis of Narrative abstractions that I can anticipate being presented and represented to markets at regularly scheduled moments of theater? Because the investment strategy for the one is almost diametrically opposed to the investment strategy for the other.

Like many Epsilon Theory readers, I am Neb Tnuh. Like Neb, I want to evaluate businesses and governments again. I want to understand their business models, evaluate their prospects against their competitors and subtitutes, quantify the return I can expect and the return I ought to demand for the risk, and seek out investment opportunities where the former exceeds the latter. I want this. But like everything else in life, wanting something to be possible doesn’t make it so.

It also doesn’t make it noble. Arch-raccoon James Altucher fancies himself Neb Tnuh, too:

“But business is just a vehicle for transforming the ideas in your head into something real, something tangible, that actually improves the lives of others. To create something unique and beautiful and valuable is very hard. It’s very special to do. It doesn’t happen fast.”
― James Altucher

And sure, there are ways to pull away from the table. There are ways to be short abstractions, like Neb recommends. Before he wrote The Icarus Moment, he wrote Hobson’s Choice, which described some of the few ways that all the Neb Tnuhs out there can reject the false choice between investing on the basis of a reality that is decoupled from risk and return, or not investing at all. These are strategies to insulate against Narrative abstractions, and I think they should be larger parts of almost every investor’s portfolio. Am I being explicit and actionable enough here? I’m talking about more real assets.

But a strategy which only insulates isn’t practical. It’s not practical for asset owners with boards, or actuarial returns, or a need to hit traditional benchmarks. It’s not practical for individuals who may not have the luxury, wealth or flexibility to, oh, I don’t know, buy an airport or 3,000 acres of northern red oak forests in Georgia. It probably isn’t desirable either. First, that level of underdiversification implies an extreme difference in return expectation, and I’m not going to leave that free lunch on the table. Neither should you. Second, the raison d’etre of turning the market into a utility, of propagating central bank missionaries and evangelist CEOs is the belief that those behaviors are at least somewhat predictable. If we’re not applying that in some measure to the rest of our portfolios, we’ve probably left something else on the table.

And so, unless we would be victims of the coyotes and raccoons who would sell us their own panaceas to this investing environment, we must engage with Narrative-driven markets. But it is hard. It is hard because the nature of abstractions is to require far more information — which usually means more time, too — to change their state. Think about when you’re explaining some complicated analogy to someone and they get confused (did you like my meta joke?). How much longer does it take you to get your conversation back on track? Think about the Keynsian Newspaper Beauty Contest. When you’re playing at the third or fourth level, how much more difficult is it to hold the pattern of what you’re evaluating in your mind, and how much more difficult is it to change that pattern to respond to new information once you’ve approximated it with some other thing, some heuristic or placeholder?

When an asset’s price, volatility behavior or direction is being driven by agreed-upon abstractions, so too is the required information to change its state far greater than usual. Missionaries explain away bad news, or create a new pro forma metric. Media members promote the new spin on the story. Supplicants call on confirmation bias to interpret it based on their existing thesis. And the contrarians who could move the price have all gone to the Hamptons for the decade. Notice how volatility spikes briefly and then disappears?

The question on whether to engage, or to try your luck with strategies that presume a strong, efficient link between economic facts and asset prices, is a question of timing. Unless your investment horizon — by which I mean the horizon over which your trade can go profoundly against you without your getting fired (if you’re a professional) or changing your mind (whether or not you’re a professional) — is more than 10 years, I simply don’t think you can have any confidence that your fundamental analysis has anything more than even odds. Sorry. And in case you were wondering, the answer is no. I don’t care who you are. You do not have a 10+ year horizon to survive being told by Mr. Market you were wrong without being fired or putting yourself under extreme pressure to change your mind.

Investing in a Time of Icarus

But we have already written about a lot of this. You know that Ben and I have said that many of these strategies just aren’t going to work the way that they used to, or when we’re looking for low-hanging fruit, that they haven’t worked the way that we all expected them to. You know that we think this is largely the result of markets and economies becoming utilities, Narrative replacing economic sensibility, and governments and oligarchs stepping into their own as missionaries for that utility and the Narratives that support it.

But what do we do? What do we do differently?

I’ve written about part of the answer fairly plainly in the Things that Matter and the Things that Don’t Matter series from 2017. There is a finite, definable list of investment principles which matter all the time, even in an Icarus Moment. Ben has written about the second element, which is to insulate.

For those who want to engage and continue the search for alpha, the answer depends.

First, it depends on the definition of alpha. When I say alpha, I mean any asset class-level decision that causes a portfolio to deviate from either the most diversified possible portfolio or a market cap-weighted portfolio of all global financial assets. I also mean any security-level decision that causes a portfolio to deviate from the broadest possible market-cap weighted benchmark for that asset class. It’s a simple definition that doesn’t get pedantic about whether a systematic active strategy is really a kind of “beta.” Sure it is. Or no, it’s not. It’s a stupid debate. I don’t care.

Second, it depends on the type of investment strategy you are using. It also depends on your methodology for implementing that strategy. Incorporating both of these requires some kind of framework to discuss.

Here’s what we’ll do: the dimensions I will use for the framework will be different from style boxes, and they’ll be different from categories used by many hedge fund index providers or asset allocators. I will define the categories instead by how I think they interact with an Icarus Moment, or a Three-Body Market — with a market in which asset price movements are heavily influenced by Narratives over an extended period of time.

The first dimension of those categories is what basis on which the strategy seeks to predict future asset prices (by which I include relative future asset prices). I roughly split strategy types into three categories: Economic Models, Behavioral Models and Idiosyncratic Models. Economic Models, in my definition, seek to predict future asset prices principally on the basis of actual and projected economic data about an economy, a financial market or an issuer, whether it’s a company or a government. Behavioral Models may incorporate some elements of Economic Models, but are principally driven by suppositions and beliefs about the behaviors of other market participants rather than the underlying companies. Idiosyncratic Models include various strategies which may even seek to exert direct influence on the future price of an asset.

For the second dimension of the framework, I think it is useful to separate investment strategies which are Systematic from those which are Discretionary. By Systematic Strategies, I refer to alpha-seeking strategies that reflect more-or-less static, if potentially emergent, beliefs about how prices are determined by certain characteristics or states, and whether those characteristics or states are directly related to economic data or more clearly influenced by observable investor behaviors.  The second category, Discretionary Strategies, refers to those in which there may be a process associated with similar beliefs, but in which the decision is made based on the judgment of a human portfolio manager. There are frequently observer effects in any investment strategy (i.e. where the act of observing something changes it), but particularly so in Narrative-driven markets. The systematic/discretionary dimension is important to understanding how this can manifest.

Those two dimensions give us six broad categories, which I have filled in with general descriptions of strategies that I think fall into each. There are things I haven’t captured here, but not many. Of active traditional and non-traditional investment strategies in public markets, I’m comfortable that this captures more than 80%. Close enough for government work.

Over the next few months, I will write a piece covering each of these six categories. My aim with this exercise is three-fold. For those who elect to both insulate and engage:

  • I want to tell you the strategies that I don’t think will work.
  • I want to tell allocators / asset owners how I think the evaluation of the strategies that may work should change.
  • I want to tell asset managers how I think they should consider adapting their strategies so that they still work in this environment.

If you think that I have bad news for the strategies on the left third of the table, thank you for paying attention. If you’re looking for a prize at the bottom, there is none.

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Is Volatility Back?

On this special episode of the Epsilon Theory podcast, we share an excerpt from a conference call we recorded on February 13 discussing our thoughts on the market selloff earlier in the month. You’ll hear from Christopher Guptill, co-CEO and chief investment officer at Broadmark Asset Management and Dr. Ben Hunt, author of Epsilon Theory.


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The Myth of Market In-Itself: Things That Matter #3, Pt. 2

Nothing at all. No figures. Only a blank.

“What’s it mean?” Reinhart muttered, dazed.

“It’s fantastic. We didn’t think this could—”

“What’s happened?”

“The machines aren’t able to handle the item. No reading can come. It’s data they can’t integrate. They can’t use it for prediction material, and it throws off all their other figures.”

“Why?”

“It’s—it’s a variable.” Kaplan was shaking, white-lipped and pale. “Something from which no inference can be made. The man from the past. The machines can’t deal with him. The variable man!”

Philip K. Dick, The Variable Man (1953)

This science fiction classic imagines a future world where specialization and technology have made versatility, adaptability and ingenuity obsolete. The unwitting introduction of a man from the past Thomas Cole capable of solving practical (and mundane) problems of this world throws off the models they use to predict the outcomes of government and military action.

Thomas Cole breaks the models because his foreignness allows him to see problems outside the confines of specialized taxonomy. He isn’t too dumb to see the tribes and archetypes of the future. He transcends them, and can’t be controlled by them. The successful navigator of policy-controlled, narrative-driven markets must be Thomas Cole. He must be The Variable Man.

When someone shows you who they are, believe them the first time.

Maya Angelou, as told by Oprah Winfrey

I have given them Your word; and the world has hated them because they are not of the world, just as I am not of the world. I do not pray that You should take them out of the world, but that You should keep them from the evil one. They are not of the world, just as I am not of the world. Sanctify them by Your truth. Your word is truth. As You sent Me into the world, I also have sent them into the world.

The Bible, The Gospel of John 17:14-18

One of the most powerful consistent themes of many religious texts is the battle between the adherent’s role in the spiritual world and in the physical one. The approach Jesus describes here in the Gospel of John is to be in the world, but not of it. It’s a consistent message for the man who dined with gamblers and prostitutes.

We’re presented with the same challenge. Behavior exists. Tribes exist. Taxonomies exist. “Communications Policy” exists. Rejecting them doesn’t mean rejecting their existence, and it absolutely doesn’t mean that we ought not to invest and trade with awareness of how they impact markets. Being as shrewd as snakes and as innocent as doves means a willingness to know about tribal thinking even when we reject it in ourselves.

The Most Interesting Man in the World: “I have no idea what this is.”

Although, truth be told, there are some things it’s worth being content knowing nothing about.

We will live in this world, which for us has all the disquieting strangeness of the desert and of the simulacrum, with all the veracity of living phantoms, of wandering and simulating animals that capital, that the death of capital has made of us—because the desert of cities is equal to the desert of sand—the jungle of signs is equal to that of the forests—the vertigo of simulacra is equal to that of nature—only the vertiginous seduction of a dying system remains, in which work buries work, in which value buries value—leaving a virgin, sacred space without pathways.

— Jean Baudrillard, Simulacra and Simulations (1981)

If anything describes the feeling I get about the market, it is disquieting strangeness. Sound familiar to you? As Baudrillard pointed out, this is the vertigo we get from a world of things that are not things in-themselves, but socially constructed amalgams of symbols and proxies for those things. With every Narrative, every bit of fiat news, the vertigo for those who seek after the truth of something increases. There is no cure, but the only treatment is to try to really, truly understand the simulacra of reality for what they are.


We live in a world awash with archetypes.

A personality test once told me that I’m an INTJ. When I play(ed) Dungeons and Dragons my alignment was Chaotic Good, and I usually roleplayed a Half-Elf Bard. I’m a #NeverTrumper on the libertarian wing of the Republican Party. I attend a Presbyterian Church, but I’ve always identified as Non-Denominational, which is, of course, a denomination that takes its denominational identity from not belonging to a denomination. I’ve been a WASP all my life, and a non-POC cishet who was coercively assigned the male gender at birth for about 2 ½ years since society decided that the sentence I just wrote is not at all horrifying and makes any kind of sense. I am of Scots-Irish extraction, a Libra or a Virgo depending on the calendar, and Buzzfeed tells me I would be Faramir[1] in the Lord of the Rings Universe, Jon Snow in Game of Thrones and Miranda in Sex and the City. Apparently, if I were admitted to Hogwarts the sorting hat would put me in Ravenclaw.

Over the last few months Ben and I have written a lot about archetypes like this, along with tribes and symbols, and the way that they are used. In Gandalf, GZA and Granovetter I argued that when symbols are used as allegories as tools to divide and dominate they have the effect of either (1) causing people to shift their beliefs and actions to match up with the symbol or tribe they identify with or (2) causing people to treat others as if their beliefs and values align with the symbol. Or, in Ben’s terminology, the (1) obedience collar and the (2) dog whistle. In that note, I took particular issue with the latter, with the idea that anyone gets to determine our intent as citizens or investors.

Here, as we continue the exploration of why investor behavior is one of the Things that Matter in our Code, I want to expand on the first: the tendency for the temperament and behaviors of investors to coalesce around archetypes. Because while we believe we ought to fight to ensure that we are all treated like principals, we also believe that when someone shows us who they are, we ought to believe them. And investors show us an awful lot about who they are. Archetypes are everywhere in markets, and if you have the patience to understand and observe them, you will understand what we think is one of the Things That Matter for all investors.

Notes from a Much More Boring Field

I grew up running through corn fields in Minooka, Illinois, but I don’t have it in me to be a gentleman farmer like Ben.

No, my notes from the field are much more dull as regular readers will know, my prior field was an institutional allocator. And people who were and are in my position bear a lot of responsibility for the archetypes in markets. You see, picking fund managers is hard, usually a waste of time, and basically everybody sucks at it. Fund evaluators have very little visibility into what causes a manager to generate returns that produce outperformance or a higher-than-expected risk-adjusted return. And so, instead of focusing on a few “things that matter” to identifying strategies and approaches that could even conceivably have an edge, the emphasis of nearly every fund allocator is exclusively on process.

Here’s the problem with that: process is a necessary but insufficient condition for consistently beating the market.

The fund allocator’s toolkit is full of ways to tell if a manager is following his process. He looks at tracking error. Rolling correlations to all sorts of indices. Cash positions over time. Factor exposures over time. Risk contributions from factor exposures, country bets, all sorts of things. These are the things that fund managers are expected to discuss, and they are often the right things to discuss. But if you have no justifiable idea whether the process itself should or will lead to outperformance, what the hell are you actually measuring? We have built an entire industry on accurately measuring whether someone followed the recipe, without knowing if the recipe tastes like hot garbage.

As a consequence, the conventions of our industry are exactly the same as the conventions of our political reality: we evaluate participants’ consistency with an archetype that is vapor, a construct, a simulacrum. In so doing, we create strong forces to drive them toward consistently behaving in that very particular way, toward incentives and responses to stimuli that are repeatable mostly because we reward them for being repeatable! It’s not really even a Pavlovian response, because the reward is usually crappy performance.

Managers of institutional pools of capital are one of the largest influences on markets, and so it is critical to understand the languages that coalesce around these archetypes. Others form around the conventions of retail gatekeepers (Howdy, Morningstar… or Lipper for the mutual fund managers who didn’t like their Morningstar rating), around sell-side research providers, around the styles of well-respected investors (e.g. Buffett) or around insufferable gasbaskets (e.g. Cramer). Others form around the self-reinforcing conventions of esoteric worlds like FinTwitter, which end up driving far more of something like USD/BTC than anything fundamental about cryptocurrency.

Returns are anywhere and everywhere a behavioral phenomenon. Dick Thaler likes to quote Herb Simon’s characterization of “behavioral economics” as a pleonasm, but talking about a behavioral approach to markets is just as redundant. It is impossible for a non-behavioral analysis of market returns to be useful. If we are ever to understand why prices move and why our investments generate returns for the portfolios we build for ourselves and our clients, we must at least develop some understanding of how and why blocs of investors form, how they buy and sell securities, how and when they change their stripes, and how that results in changes in the prices of the investments we own. We’re going to do a lot of generalizing, so caveat the below however you deem appropriate. This isn’t a precise science or at least it isn’t yet.

The Value Archetype

It’s easy enough to introduce what it is we’re talking about with a “style” that most investors are familiar with. Well, sort of, anyway.

The language of value is familiar—buy cheap things. The investor who has adopted it is rarely a news-responder. In many cases he fancies himself a bettor on things that are out-of-favor or forgotten. In the market voting machine, he casts his ballots and crosses the [actual and proverbial] spread for things with bad tape, with bad narratives, with problems. Don’t mistake the language for the style. Graham and Dodd, Buffett and their “intrinsic value” ilk are value investors in the way that everyone is a value investor – in that they want to buy something they think will be worth more in the future than it is today. They aren’t who we’re talking about here.

We are talking about the investor who believes that investors pay too much for quality, for growth, for sex appeal, and that it will harm their returns. These days, most of these value investors are quants. Some of them are financial advisors selling a package of contrarian ideas, of differentiated thinking. Many more of them are fundamental shops, folks that focus on multiples-based analysis and build fancy models after the fact to justify the things they buy on the basis of multiples, not that there’s anything wrong with that.

So how do these value investors impact prices and returns?

Visualize the order book from Part 1, and again, think about it in long-horizon terms. Members of the Value Archetype form a big part of the willingness of the market to buy things that most think are unattractive. They form the corpus of the out-of-the-money bid for any security or market, and like their counterparts in the Mean-Reversion Archetype we’ll read about shortly, that’s when they tend to participate in the marginal price-setting process. That, and on the ask side, where they tend to be the sellers of gains. When a lot of people are rallying at this banner, it can be a pretty meaningful force to constrain upward movement in prices.

When there aren’t as many, the Value Archetype plays a much smaller part in the price-setting process. Consider: who is selling a stock that goes from trading at 45x earnings to 50x earnings? It ain’t the Value guy. He sold it a long time ago, and the next guy couldn’t care less.

The Growth Archetype

We tend to think of “growth” as being the opposite of “value,” but that isn’t strictly true. For most of the indexes that track these styles, it is kinda true, although in their vernacular, “growth” is really just “anti-value.” In other words, when you see a growth index, in most cases it isn’t sorting companies by how quickly they grew or are expected to grow, but by how expensive they are. That’s not what we’re talking about.

There may be a few investors out there who are actively looking to buy things because they are expensive, I suppose, but there are plenty who don’t care all that much if it has what they are looking for. What many of them are looking for is growth, or at a minimum the narrative of growth. That narrative may be favoring one stock over a peer. It may be in favoring technology securities over the retail sector. It may be in favoring emerging markets investments over developed markets. There are some investors at certain times and under certain conditions who see valuations as temporary phenomena and growth narratives as the only relevant focus.

Some of these individuals actively choose this posture. They believe the narratives, they buy, and they cross the spread to do it. Prices rise.

Some under this banner have no choice. They have asset-liability issues that require them to seek out growth. They are pushed by falling yields in alternative asset classes precipitated by central bank action. They, too, must buy and cross the figurative spread to do it. Prices rise.

We’ll come back to this, because it’s important.

The Momentum Archetype

Quantitative investors do this. Traders do this. In a way, of course, these are people responding to the Epsilon that represents a portion of market returns. In most cases, they do it because it generally works. Winners tend to keep winning and losers tend to keep losing. Many investors who coalesce around this archetype do so very willingly (pictured right), while others would be mortified to think that they would be tarred with a “technical” investor brush. And so they are focused on consistent improvement in earnings, or in guidance from management, or in an improving story. Narrative momentum rather than price momentum, but momentum all the same.

In the end, what matters is that these individuals ‘cross the spread’ to support continued movement in the price of securities. Some can be long/short, and so this can happen in both directions. But it’s generally long, and getting longer.

The Mean-Reversion Archetype

I’m abstracting a lot from time horizons here, and I’m doing so intentionally. Part of my story is that in a non-ergodic world, the idea that the long-term can be considered fully independently from the path that begins in shorter horizons is madness. And so, while I fully recognize that there are many, many funds that pursue strategies that happily encompass each of value, momentum and mean-reversion strategies, I’m not talking about strategies. I’m talking about frameworks of thinking and talking about investments that color the decisions that investors make across the board.

And on this dimension, while mean-reversion has a specific meaning within the context of, say, CTA and statistical arbitrage strategies, what I’m really talking about is the consciously contrarian asset allocator. Only instead of looking for unloved companies, this is the falling-knife catcher. The one looking for the turn, the top, the bottom, the inflection point.

Some demonstrate this trait consciously, but far more do so passively through policies called “rebalancing,” most of which have a negative expected return. After all, momentum works. But these people are volatility reducers. They step in to provide the bid when the longs are screaming bloody murder and the ask when the shorts are getting crushed.

The Others

Look, there are all sorts of taxonomies people rally around. We could talk about some nebulous definition of “quality” guys or the nothing-land that is most “GARP” investing. We could talk about investors who are students of more arcane technical trading approaches, or about those who invest based on macroeconomic data or news. But it’s the four things above that matter.

Except that there is a rapidly growing fifth category, a sort of Nihilistic Archetype. It’s the passive investor. Except inasmuch as he adheres to another archetype in his cross-asset allocation decisions (which he frequently does), the passive investor expresses no opinion whatsoever with respect to the pricing of individual securities. He doesn’t participate in relative price-setting.

He is out of the game.

Where Does This Put Us?

Can you tell that I’m going somewhere with this? To better understand why I think it’s important for all investors to think about the behaviors of their fellow-travelers in markets, let’s walk through what I think is happening right now:

  • The Value Archetype is dead: No one is rallying around this banner. Read the sell-side language. No one is pitching value-oriented research, because they’d have no one to sell it to. Even the old stalwarts, the quants, have evolved toward either risk premia-based or Value+Momentum+Quality mandates that dampen the emphasis on value alone. Sure, you’ll get the occasional bank strategist calling for a rotation into financials (they’ve got to be early calling the new thing), but of the people setting prices, very few of them are speaking this language. I’m not saying I don’t believe in value. I do! But the market’s belief in it is nothing more than lip service right now.
  • The Mean-Reversion Archetype guys in CTA and Global Macro Land are bleeding out: Selling winners and buying losers has rarely been a more painful trade. I’ve talked to a few FAs who are sticking with long vol trades or defensive positions because, well, at this point, you might as well stick to your guns. But other than that, this is a dead language, folks. If you expect someone to bail you out of a short squeeze, you’re barking up the wrong tree.
  • Passive Investing is levitating broad markets but allowing intra-market volatility: Investors, allocators and fund managers alike have piled into the Growth train, in part because they want to, and in part because retirees and pension plans with unfunded future liabilities have no other choice. Since they are doing so through broad market instruments and are not about to sell into weaker growth prospects, there is continued upward pressure on prices. Within markets, the decline in participants who are actively participating on individual securities is allowing continued spread potential between sectors, styles, etc.

The combined effect? Everything is levitating. With value and mean-reversion as lingua non grata, the people setting prices are (1) Growth investors, (2) Momentum investors and (3) Passive investors adhering to those archetypes. There is no one left to sell, because there is no one left who cares nearly enough about valuation or is confident enough in their ability to time a top in markets to sell into strength. The result is in Information Surface terms a market that has tremendous difficulty generating any price volatility to the negative.

What Does This Mean for Investors?

We can be in the market and be long. We can be not of this market and be ready for the move to the downside. Or we can be in the market, but not of it, by incorporating the behaviors of others into our thinking about markets AND retaining our ability to think independently about possible outcomes. How?

  1. With the core of your portfolio, you don’t fight it. This is most of what being aware of investor behaviors and the complete hegemony they have over market movements means.
  2. You think more specifically about how other investors are thinking about this market. Why they’re buying. Why they’re buying what they’re buying. You think about their motivations. And you think about how a change in their motivations would change in response to various market influences. Is a shooting war in the Middle East going to materially change investors’ view of and preference for growth? (Probably not) Is a material change in language coming from all Central Banks going to shift it? (Maybe, as Ben has written)
  3. You prepare your portfolio or at least your framework for what happens when that informational bowling ball climbs the wall to the downside, because when it does, volatility can return in a big damned hurry.

Thomas Cole wasn’t a genius. He succeeded because he was capable of acknowledging the existence and influence of archetypes without succumbing to them in his own behavior and actions. If you would navigate this market, your Code should allow you to do the same.

[1]Hopefully it’s book Faramir, and not the movie Faramir that Peter Jackson made into a spineless clone of Boromir because Jackson lacks any understanding of plot or character.

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You Still Have Made a Choice: Things that Matter #2

Drummers are really nothing more than time-keepers. They’re the time of the band. I don’t consider I should have as much recognition as say a brilliant guitar player. I think the best thing a drummer can have is restraint when he’s playing — and so few have today. They think playing loud is playing best. Of course, I don’t think I’ve reached my best yet. The day I don’t move on I stop playing. I don’t practice ever. I can only play with other people, I need to feel them around me.

— Ginger Baker (founder of Cream), from a 1970 interview with Disc Magazine

La cuisine, c’est quand les choses ont le goût de ce qu’elles sont.
(Good cooking is when things taste of what they are.)

— Maurice Edmond Sailland (Curnonsky) — 1872-1956

There are those who think that life
Has nothing left to chance
A host of holy horrors
To direct our aimless dance

A planet of playthings
We dance on the strings
Of powers we cannot perceive
The stars aren’t aligned
Or the gods are malign
Blame is better to give than receive

You can choose a ready guide
In some celestial voice
If you choose not to decide
You still have made a choice

 — Rush, “Freewill”, Permanent Waves (1980)

For the kingdom of heaven is like a man traveling to a far country, who called his own servants and delivered his goods to them. And to one he gave five talents, to another two, and to another one, to each according to his own ability; and immediately he went on a journey. Then he who had received the five talents went and traded with them, and made another five talents. And likewise, he who had received two gained two more also. But he who had received one went and dug in the ground, and hid his lord’s money. After a long time the lord of those servants came and settled accounts with them.

So he who had received five talents came and brought five other talents, saying, ‘Lord, you delivered to me five talents; look, I have gained five more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you were faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’ He also who had received two talents came and said, ‘Lord, you delivered to me two talents; look, I have gained two more talents besides them.’ His lord said to him, ‘Well done, good and faithful servant; you have been faithful over a few things, I will make you ruler over many things. Enter into the joy of your lord.’

Then he who had received the one talent came and said, ‘Lord, I knew you to be a hard man, reaping where you have not sown, and gathering where you have not scattered seed. And I was afraid, and went and hid your talent in the ground. Look, there you have what is yours.’

But his lord answered and said to him, ‘You wicked and lazy servant, you knew that I reap where I have not sown, and gather where I have not scattered seed. So you ought to have deposited my money with the bankers, and at my coming I would have received back my own with interest. Therefore, take the talent from him, and give it to him who has ten talents.

For to everyone who has, more will be given, and he will have abundance; but from him who does not have, even what he has will be taken away. And cast the unprofitable servant into the outer darkness. There will be weeping and gnashing of teeth.

The Bible, The Gospel of Matthew 25:14-30

This note was featured in Meb Faber’s book The Best Investment Writing – Volume 2, alongside another Epsilon Theory note from Ben Hunt. Click here to get a copy.

I will never understand why more people don’t revere Rush.

With the possible exception of Led Zeppelin[1], I’m not sure there has been another band with such extraordinary instrumentalists across the board, such synergy between those members and their musical style and such a consistent approach to both lyrical and melodic construction. And yet they were only inducted into the Rock & Roll Hall of Fame in 2013. A short list of bands and singers the selection committee thought were more deserving: ABBA, Madonna, Jackson Browne, the Moonglows, Run DMC. At least they got in when Randy Newman did. I remember the first time I heard YYZ, the Rush tune named after the IATA airport code for Toronto’s Pearson International Airport, pronounced “Why Why Zed” in the charming manner of the Commonwealth. It was then that I decided I would be a drummer. I did play for a while, and reached what I would describe as just above a baseline threshold of competence.

That’s not a throwaway line.

There’s a clear, explicit line that every drummer (hopefully) crosses at one point. A step-change in his understanding of the role of the instrument. The true novice drummer always picks up the sticks and plays the same thing. Common time. Somewhere between 90-100 beats per minute. Eighth note closed hi-hat throughout. Bass drum on the down and upbeat of the first beat. Snare on second down beat. And then it’s all jazzy up-beat doodling on the snare for the rest of that bar until the down beat of four. Same thing for three measures, and on the fourth measure it’s time for that awesome fill he’s been practicing. I don’t know how many subscribers are drummers, but I assure you, literally couples of you are nodding your heads.

The fills and off-beat snare hits are all superfluous and not necessary to the principal role of a drummer in rock and roll: to keep the damned beat. But there are a number of reasons why every neophyte does these same things. Mimicry of more advanced players who can do the creative and interesting things without losing the beat, for one. We see Tony Williams, John Bonham, or Bill Bruford and do what it is we think they are doing to make the music sound good. The amateur often also thinks that these are the necessary things to be perceived as a more advanced player, for another. He doesn’t just imagine that his mimicry will make him sound more like the excellent players, but imagines himself looking like them to others. More than anything, the amateur does these things because he hasn’t quite figured out that keeping a good beat is so much more important than anything else he will do that he’s willing to sacrifice it for what he thinks is impressive.

This thought process dominates so many other fields as well. Consider the number of amateur cooks who hit every sauce or piece of meat with a handful of garlic powder, onion powder, oregano, salt, pepper and cayenne, when the simplicity of salt as seasoning dominates most of the world’s great cuisine. There is an instinct to think that complexity and depth must come from a huge range of ingredients[2] or from complexity in preparation, but most extraordinary cooking begins from an understanding of a small number of methods for heating, seasoning and establishing bases for sauces. Inventiveness, creativity and passion can take cuisine in millions of directions from there, but many home cooks see the celebrity chef’s flamboyant recipe and internalize that the creative flourishes are what matters to the dish, and not the fact that he cooked a high-quality piece of meat at the right heat for the right amount of time.

If you’re not much of a cook, consider instead the 30-handicap golfer who wouldn’t be caught dead without a full complement of four lob wedges in his bag. You know, so that he can address every possible situation on the course. The trilling singer of the national anthem who can’t hold a pitch but sees every word of the song as an opportunity to sing an entire scale’s worth of notes. The karate novice who addresses his opponent with a convoluted stance. The writer who doesn’t know when to stop giving examples to an audience who understood what he was getting at half-way through the one about cooking.

I’m guessing at least one of these things pisses you off, or at the very least makes you do an internal eye roll. And yet, as investors we are guilty of doing this kind of thing all the time, any time the topic of diversification comes up.

It comes from a good place. We know from what we’ve been taught (and from watching the experts) that we should diversify, but we don’t have a particularly good way of knowing what that means. And so we fill our portfolios with multiple flavors of funds, accounts and individual securities. Three international equity funds with different strategies. Multiple different styles in emerging markets. Some value. Some growth. Some minimum volatility. Some call writing strategies. Some sector funds. Maybe some long/short hedge funds. Some passively managed index funds, some actively managed funds. Definitely some sexy stock picks. And in the end, the portfolio that we end up with looks very much like the global equity market, maybe with a tilt here or there to express uniqueness — that flashy extra little hit on the snare drum to look impressive.

This piece isn’t about the time we waste on these things. I already wrote a piece about that a few weeks ago. This is about the harm we do to our portfolios when we play at diversifying instead of actually doing it.

The Parable of the Two FA’s

So what does actually diversifying look like?

There are lot of not-very-useful definitions out there. The eggs-in-one-basket definition we’re all familiar with benefits from simplicity, which is not nothing. In addition, it does work if people have a good concept of what the basket is in the analogy. Most people don’t. Say you have $100, and you decide that a basket is an advisor or a fund. So you split the money between the two, and they invest in the same thing. You have not diversified[3]. The other definitions for diversification tend to be more complicated, more quantitative in nature. That doesn’t make them bad, and we’ll be leaning on some of them. But we need a rule of thumb, some heuristic for describing what diversification ought to look like so that we know it when we see it. For the overwhelming majority of investors, that rule of thumb should go something like this:

Diversification is reducing how much you expect to lose when risky assets do poorly or very poorly without necessarily reducing how much total return you expect to generate.

Now, this is not exactly true, and it’s very obviously not the whole definition. But by and large it is the part of the definition that matters most. The more nuanced way to think about diversification, of course, is to describe it as all the benefits you get from the fact that things in your portfolio don’t always move together, even if they’re both generally going up in value. But most investors are so concentrated in general exposure to risky assets — securities whose value rises and falls with the fortunes and profitability of companies, and how other investors perceive those fortunes — that this distinction is mostly an academic one. Investors live and die by home country equity risk. Period. Most investors understand this to one degree or another, but the way they respond in their portfolios doesn’t reflect it.

I want to describe this to you in a parable.

There was once a rich lord who held $10 million in a S&P 500 ETF. He knew that he would be occupied with his growing business over the next year. Before he left, he met with his two financial advisors and gave them $1 million of his wealth and told them to “diversify his holdings.”

He returned after a year and came before the first financial advisor. “My lord, I put the $1 million you gave me in a Russell 1000 Value ETF. Here is your $1.1 million.” The rich man replied, “Dude, that’s almost exactly what my other ETF did over the same period. What if the market had crashed? I wasn’t diversified at all!” And the financial advisor was ashamed.

Furious and frustrated, the rich man then summoned his second financial advisor. “Sir, I put your $1 million in a Short-Duration Fixed Income mutual fund of impeccable reputation. Here’s your $1 million back.”

“Oh my God,” the lord replied, “Are you being serious right now? If I wanted to reduce my risk by stuffing my money in a mattress I could have done that without paying you a 65bp wrap fee. How do you sleep at night? I’m going to open a robo-advisor account.”

Most of us know we shouldn’t just hold a local equity index. We usually buy something else to diversify, because that’s what you do. But what we usually do falls short either because (1) the thing we buy to diversify isn’t actually all that different from what we already owned, or (2) the thing we buy to diversify reduces our risk and our return, which defeats the purpose. There’s nothing novel in what I’m saying here. Modern portfolio theory’s fundamental formula helps us to isolate how much of the variation in our portfolio’s returns comes from the riskiness of the stuff we invested in vs. the fact that this stuff doesn’t always move together.

Source: Salient 2017 For illustrative purposes only.

The Free Lunch Effect

So assuming we didn’t have any special knowledge about what assets would generate the highest risk-adjusted returns over the year our rich client was away on business, what answer would have made us the good guy in the parable? Maximizing how much benefit we get from that second expression above — the fact that this stuff doesn’t always move together.

Before we jump into the math on this, it’s important to reinforce the caveat above: we’re assuming we don’t have any knowledge about risk-adjusted returns, which isn’t always true. Stay with me, because we will get back to that. For the time being, however, let’s take as a given that we don’t know what the future holds. Let’s also assume that, like the Parable of the Two FA’s, our client holds $10 million in S&P 500 ETFs. Also like the parable, we have been asked to reallocate $1 million of those assets to what will be most diversifying. In other words, it’s a marginal analysis.

The measure we’re looking to maximize is the Free Lunch Effect, which we define as the difference between the portfolio’s volatility after our change at the margin and the raw weighted average volatility of the underlying components. If the two assets both had volatility of 10%, for example, and the resulting portfolio volatility was 9%, the Free Lunch Effect would be 1%.

If maximizing the Free Lunch Effect is the goal, here’s the relative attractiveness of various things the two FA’s could have allocated to (based on characteristics of these markets between January 2000 and July 2017).

Volatility Reduction from Diversification — Adding 10% to a Portfolio of S&P 500

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

The two FA’s failed for two different reasons. The first failed because he selected an asset which was too similar. The second failed because he selected an asset which was not risky enough for its differentness to matter. The first concept is intuitive to most of us, but the second is a bit more esoteric. I think it’s best thought of by considering how much the risk of a portfolio is reduced by adding an asset with varying levels of correlation and volatility. To stop playing at diversification, this is where you start.

Volatility Reduction by Correlation and Volatility of Diversifying Asset

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

If You Choose not to Decide

If there are some complaints that can be leveled against this approach, two of them, I think, are valid and worthy of exploration.

The first is that diversification cannot be fully captured in measures of correlation. If you read Whom Fortune Favors, you’ll know that our code recognizes that we live in a behaviorally-influenced, non-ergodic world. While I think we’d all recognize that U.S. value stocks are almost always going to be a poor diversifier against global equities (and vice versa), clearly there are events outside of the historical record or what we know today that could completely change that. And so the proper reading of this should always be in context of an adaptive portfolio management process.

The second complaint, as I alluded to earlier, is the fact that we are not always indifferent in our risk-adjusted return expectations for different assets. I’m sure many of you looked at the above chart and said to yourself, “Yeah, I’m not piling into commodities.” I don’t blame you (I’m still not satisfied with explanations for why I ought to be paid for being long contracts on many commodities), but that is the point. Not owning commodities or MLPs because you don’t get them isn’t the same as not expressing an opinion. If you choose not to decide, you still have made a choice.

When investors choose to forgo diversification, on any basis, they are implicitly betting that decisions that they make will outperform what diversification would have yielded them. It may not be optimal to own the most diversified portfolio you can possibly own, because anti-diversifying decisions might, in fact, be worth it. But it is exactly that thought process that must become part of our code as investors. It’s OK to turn down a free lunch, but you’d damn well better know that what you’re going to spend your money on is better.

So how do you quantify that implicit bet? Again, the Free Lunch Effect gives us our easiest answer. Consider the following case: let’s assume we had two investment options, both with similar risk of around 15%. For simplicity’s sake we’ll start from our naïve assumption that our assets produce, say, 0.5 units of return for every unit of risk we take. If the two assets are perfectly uncorrelated, how much more return would we need to demand from Asset 1 vs. Asset 2 to own more of it than the other? To own 100% Asset 1?

Well, the chart below shows it. In the case above, if you invest 100% of your portfolio in Asset 1, an investor who thinks about his portfolio in risk-adjusted terms is implicitly betting that Asset 1 will generate more than 3% more return per year, or an incremental 0.21 in return/risk units. If the assets are less similar, this implicit view grows exponentially.

Implied Incremental Return Expectation from Overweighted Asset

Source: Salient 2017. For illustrative purposes only. Past performance is not indicative of how the index will perform in the future. The index reflects the reinvestment of dividends and income and does not reflect deductions for fees, expenses or taxes. The index is unmanaged and is not available for direct investment.

A Chain of Linked Engagements

If we do not learn to regard a war, and the separate campaigns of which it is composed, as a chain of linked engagements each leading to the next, but instead succumb to the idea that the capture of certain geographical points or the seizure of undefended provinces are of value in themselves, we are liable to regard them as windfall profits.

— On War, Carl von Clausewitz

The point of this note isn’t to try to convince you to focus your portfolio construction efforts on higher volatility diversifiers like those highlighted earlier (although many of you should). It’s also not to argue that maximizing diversification should be your first objective (although most of us are so far from the optimum that moving in this direction wouldn’t hurt). It is to emphasize that portfolio construction and the decisions we make are a chain of linked engagements. It is to give you pause when you or your client asks for a ‘best new investment idea’. If your experiences are like mine, the question is nearly always expressed in isolation — recommend me a stock, a mutual fund, a hedge fund. These questions can never be answered in isolation. If you really must tinker with your allocation, sure, I can give you my view, but only if I know what else you own, and only if I know what you intend to sell in order to buy the thing.

Anyone who will make a recommendation to you without knowing those things is an idiot, a charlatan, or both.

Most of us, whether we are entrenched in financial markets or not, think about our decisions not in a vacuum but in terms of opportunity cost. If we buy A, we’re giving up B. If we invest in A, we’re giving up on B. If we do A, we won’t have time for B. Opportunity cost is fundamental to thinking about nearly every aspect of human endeavor but for some reason is completely absent from the way many investors typically think about building portfolios.

Look, if you didn’t completely follow where I was going with Whom Fortune Favors, I get it. Telling you to think about risk and diversification separately is more than a little bit arcane. But here’s where it comes together: an investor can only make wise decisions about asset allocation, about selecting fund managers, about tactical bets and about individual investments when he has an objective opportunity cost to assess those decisions against that allows him to make his portfolio decisions intentionally, not implicitly. That opportunity cost is the free lunch provided by diversification.

If we take this way of thinking to its natural extreme, we must recognize that we can, at any point, identify the portfolio that would have provided the maximum diversification, at least using the tools we’ve outlined here. For most periods, if you run through that analysis, you are very likely to find that a portfolio of those assets in which every investment contributes a comparable amount of risk to the whole — a risk parity portfolio, in other words — typically provides something near to that maximum level of diversification. I am not suggesting that your portfolio be the maximum diversification portfolio or risk parity. But I am suggesting that a risk parity portfolio of your investable universe is an excellent place to use as an anchor for this necessary analysis.

If you don’t favor it for various reasons (e.g. using volatility as a proxy for risk is the devil, it’s just levered bonds, etc.), then find your home portfolio that accomplishes similar goals in a way that is rules-based and sensible. Maybe it’s the true market portfolio we highlight in I am Spartacus. If you’re conservative, maybe it’s the tangency portfolio from the efficient frontier. And if you’re more aggressive, maybe it is something closer to the Kelly Optimal portfolio we discussed in Whom Fortune Favors. From there, your portfolio construction exercise becomes relatively simple: does the benefit I expect from this action exceed its diversification opportunity cost?

How do you measure it? If you have capital markets assumptions or projections, feel free to use them. Perhaps simpler, assume a particular Sharpe Ratio, say 0.25 or 0.30, and multiply it times the drop in diversification impact from the action you’re taking. Are you confident that the change you’re making to the portfolio is going to have more of an impact than that? That’s…really it. Now the shrewd among you might be saying, “Rusty, isn’t that kind of like what a mean-variance optimization model would do?” It isn’t kind of like that, it’s literally that. And so what? We’re not reinventing portfolio science here, we’re trying to unpack it so that we can use it more effectively as investors.

Recognize that this isn’t just a relevant approach to scenarios where you’re changing things around because you think it will improve returns dramatically. This is also a useful construct for understanding whether all the shenanigans in search of diversification, all that Chili P you’re adding, are really worth the headache. Is that fifth emerging markets manager really adding something? Is sub-dividing your regions to add country managers really worth the time?

In the end, it’s all about being intentional. With as many decisions as we have to manage, the worst thing we can do is let our portfolios make our decisions for us. Given the benefits of diversification, investors ought to put the burden of proof on anything that makes a portfolio less diversified. In doing so, they will recognize why this code recognizes the intentional pursuit of real diversification as the #2 Thing that Matters.


[1] I don’t want to hear it from the “but they stole people’s music and weren’t super nice about it” crowd. Zep played better rock and roll music than anyone before or after, and it’s not even close.

[2] And it can. Pueblan and Oaxacan cuisine feature moles with extraordinary complexity that does come from the melding of a range of seasonings and ingredients. Traditional American chilis, South Asian curries and soups from around the world often do as well. Dishes en croute (e.g. pate en croute, coulibiac, etc.) are notoriously tricky, too.

[3] Cue the fund-of-funds due diligence analyst pointing out that we would have, in fact, diversified our fraud risk. Die on that hill if you want to, friend.


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Whom Fortune Favors: Things that Matter #1, Pt. 2


Click here to read Part 1 of Whom Fortune Favors


Fook: There really is an answer?

Deep Thought: Yes. There really is one.

Fook: Oh!

Lunkwill: Can you tell us what it is?

Deep Thought: Yes. Though I don’t think you’re going to like it.

Fook: Doesn’t matter! We must know it!

Deep Thought: You’re really not going to like it!

Fook: Tell us!

Deep Thought: Alright. The answer to the ultimate question…of Life, the Universe, and Everything…is… “42”. I checked it thoroughly. It would have been simpler, of course, to have known what the actual question was.

— Douglas Adams, Hitchhiker’s Guide to the Galaxy

As investors, our process is usually to start from the answer and work our way back to the question. Unfortunately, the answers we are provided are usually pre-baked products, vehicle types or persistent industry conventions, which means that the answers we get when we actually focus on the questions that matter may be counterintuitive and jarring. The entire point of developing a personal code for investing is knowing which questions matter and ought to be asked first, before a single product, vehicle or style box gets thrown into the mix.

The purpose you undertake is dangerous.’ Why, that’s certain. ‘Tis dangerous to take a cold, to sleep, to drink; but I tell you, my lord fool, out of this nettle, danger, we pluck this flower, safety.

William Shakespeare, Henry IV, Part 1, Act 2, Scene 3, Hotspur

Thomasina: When you stir your rice pudding, Septimus, the spoonful of jam spreads itself round making red trails like the picture of a meteor in my astronomical atlas. But if you stir backwards, the jam will not come together again. Indeed, the pudding does not notice and continues to turn pink just as before. Do you think this is odd?

Septimus: No.

Thomasina: Well, I do. You cannot stir things apart.

Septimus: No more you can, time must needs run backward, and since it will not, we must stir our way onward mixing as we go, disorder out of disorder into disorder until pink is complete, unchanging and unchangeable, and we are done with it forever. This is known as free will or self-determination.

Thomasina: Septimus, do you think God is a Newtonian?

Septimus: An Etonian? Almost certainly, I’m afraid. We must ask your brother to make it his first enquiry.

Thomasina: No, Septimus, a Newtonian. Septimus! Am I the first person to have thought of this?

Septimus: No.

Thomasina: I have not said yet.

Septimus: “If everything from the furthest planet to the smallest atom of our brain acts according to Newton’s law of motion, what becomes of free will?”

Thomasina: No.

Septimus: God’s will.

Thomasina: No

Septimus: Sin.

Thomasina (derisively): No!

Septimus: Very well.

Thomasina: If you could stop every atom in its position and direction, and if your mind could comprehend all the actions thus suspended, then if you were really, really good at algebra you could write the formula for all the future; and although nobody can be so clever as to do it, the formula must exist just as if one could.

Septimus (after a pause): Yes. Yes, as far as I know, you are the first person to have thought of this.

— Tom Stoppard, Arcadia, (1993)

On this most important question of risk, we and our advisors often default to approaches which rely on the expectation that the past and present give us profound and utterly reliable insights into what we ought to expect going forward. As a result, we end up with portfolios and, more importantly, portfolio construction frameworks which don’t respect the way in which capital actually grows over time and can’t adapt to changing environments. That’s not good enough.

Most of these notes tend to stand on their own, but this one (being a Part 2) borrows a lot from the thinking in Part 1. If you’re going to get the most out of this note, I recommend you start there. But if you’re pressed for time or just lazy, I wanted you to take away two basic ideas:

  • That the risk decision dominates all other decisions you make.
  • That the risk decision is not exactly the same as the asset class decision.

Children of a Lazier God

Before I dive into the weeds on those ideas, however, I want to tell you about a dream I have. It’s a recurring dream. In this dream, I have discovered the secret to making the most possible money with the least possible effort.

Hey, I never said it was a unique dream.

It is, however, a unique investing case. Imagine for a moment that we had perfect omniscience into returns, but also that we were profoundly lazy – a sort of Jeffersonian version of God. We live in a world of stocks, bonds and commodities, and we want to set a fixed proportion of our wealth to invest in each of those assets. We want to hold that portfolio for 50+ years, sit on a beach watching dolphins or whatever it is people do on beach vacations, and maximize our returns. What do we hold? The portfolio only needs to satisfy one explicit and one implicit objective. The explicit objective is to maximize how much money we have at the end of the period. The implicit objective is the small matter of not going bankrupt in the process.

This rather curious portfolio is noteworthy for another reason, too: it is a static and rather cheeky case of an optimal portfolio under the Kelly Criterion. Named after John Kelly, Jr., a Bell Labs researcher in the 1950s, the eponymous criterion was formally proposed in 1956 before being expanded and given its name by Edward O. Thorp in the 1960s. As applied by Thorp and many others, the Kelly Criterion is a mechanism for translating assessments about risk and edge into both trading and betting decisions.

Thorp himself has written several must-reads for any investor. Beat the Dealer, Beat the Market and A Man for All Markets are all on my team’s mandatory reading list. His story and that of the Kelly Criterion were updated and expanded in William Poundstone’s similarly excellent 2005 book, Fortune’s Formula: The Untold Story of the Scientific Betting System that Beat the Casinos and Wall Street.  The criterion itself has long been part of the parlance of the professional and would-be professional gambler, and has also been the subject of various finance papers for the better part of 60 years. For the less prone to the twin vices of gambling and authoring finance papers, Kelly translates those assessments about risk and edge into position sizes. In other words, it’s a guide to sizing bets. The objective is to maximize the geometric growth rate of your bankroll — or the expected value of your final bankroll — but with zero probability of going broke along the way. It is popular because it is simple and because, when applied to games with known payoffs, it works.

When we moonlight as non-deities and seek to determine how much we ought to bet/invest, Kelly requires knowing only three facts: the size of your bankroll, your odds of winning and the payout of a winning and losing bet. For the simplest kind of friendly bet, where a wager of $1 wins $1, the calculation is simple: Kelly says that you should bet the difference between your odds of winning and your odds of losing. If you have a 55-to-45 edge against your friend, you should bet 10% of your bankroll. Your expected compounded return of doing so is provably optimal once you have bet against him enough to prove out the stated edge — although should you manage to reach this point, you are a provably suboptimal friend.

Most of the finance papers that apply this thinking to markets have focused on individual trades that look more or less like bets we’d make at a casino. These are usually things with at least a kinda-sorta knowable payoff and a discrete event where that payoff is determined: a single hand of blackjack, an exercise of an option, or a predicted corporate action taking place (or not taking place). It’s a lot harder to get your head around what “bet” we’re making and what “edge” we have when we, say, buy an S&P 500 ETF instead of holding cash. Unless you really are omniscient or carry around a copy of Grays Sports Almanac, you’re going to find estimating the range of potential outcomes for an investment or portfolio of investments pretty tricky. Not that it stops anyone from trying.

Since I don’t want to assume that any of us is quite so good at algebra as to write the formula for all the future, at a minimum what I’m trying to do is get us to think about risk unanchored to the arbitrarily determined characteristics and traits of asset classes. In other words, I want to establish an outside bound on the amount of risk a person could theoretically take in a portfolio if his only goal was maximizing return. Doing that requires us to think in geometric space, which is just a fancy way of saying that we want to know how the realization of returns over time ends up differing from a more abstract return assumption. It’s easy enough to get a feel for this yourself by opening Excel and calculating what the return would be if your portfolio went up 5% in one year and down 5% in the next (works for any such pair of numbers). Your simple average will always be zero, but your geometric mean will always be less than zero, by an increasing amount as the volatility increases.

So, if we knew exactly what stocks, bond and commodities would do between 1961 and 2016, what portfolio would we have bought? The blend of assets if we went Full Kelly would have looked like this:

Source: Salient 2017. For illustrative purposes only.

Only there’s a catch. Yes, we would have bought this portfolio, but we would have bought it more than six times. With perfect information about odds and payoffs, the optimal bet would have been to buy a portfolio with 634% (!) exposure, consisting of $2.00 in stocks, $3.21 in bonds and $1.13 in commodities for every dollar in capital we had. After all was said and done, if we looked back on the annualized volatility of this portfolio over those 50 years, what would we have found? What was the answer to life, the universe and everything?

44. Sorry, Deep Thought, you were off by two.

Perhaps the only characteristic of this portfolio more prominent than its rather remarkable level of exposure and leverage, is its hale and hearty annualized volatility of 44.1%. This result means if all you cared about was having the most money over a 50+ year period that ended last year, you would have bought a portfolio of stocks, bonds and commodities that had annualized volatility of 44.1%, roughly three times the long-term average for most equity markets[1], and probably five times that of the typical HNW investor’s portfolio.

And before you go running off to tell my lovely, charming, well-dressed and distressingly unsusceptible-to-flattery compliance officer that I told you to buy a 44% volatility super-portfolio, allow me to acknowledge that this requires some… uh… qualification. Most of these qualifications are pretty self-explanatory, since the whole exercise isn’t intended to tell you what you should buy going forward, or even the right amount of risk for you. This portfolio, this leverage and that level of risk worked over the last 50 years. Would they be optimal over the next 50?

Of course not. In real life, we’re not omniscient. Whereas a skilled card counter can estimate his mathematical edge fairly readily, it’s a lot harder for those of us in markets who are deciding what our asset allocation ought to look like. Largely for this reason, even Thorp himself advised betting “half-Kelly” or less, whether at the blackjack table or in the market. When asked why, Thorp told Jack Schwager in Hedge Fund Market Wizards, “We are not able to calculate exact probabilities… there are things that are going on that are not part of one’s knowledge at the time that affect the probabilities. So you need to scale back to a certain extent.”

Said another way, going Full Kelly on a presumption of precise certainty about outcomes in markets is a surefire way to over-bet, potentially leading to a complete loss of capital. Now, scaling back is easy if we are starting from an explicit calculation of our edge as in a game of blackjack. It’s not as easy to think about scaling down to, say, a Half Kelly portfolio. There is, however, another fascinating (but intuitive) feature of the Kelly Optimal Portfolio that allows us to scale back this portfolio in a way that may be more familiar: the Kelly Optimal Portfolio can be generalized as the highest return case of a set of portfolios generating geometric returns that are most efficient relative to the risk they take[2].

This may sound familiar. In a way, it’s very much like a presentation of Markowitz’s efficient frontier. Markowitz plots the portfolios that generate the most return for a given unit of risk, but his is a single-period calculation. It isn’t a geometric approach like Kelly, but rather reflects a return expectation that doesn’t incorporate how volatility and non-linearities impact the path and the resulting compound return. There have been a variety of academic pieces over the years covering the application of geometric returns to this framework, but most have focused on either identifying a single optimal geometric portfolio or on utility. Bernstein and Wilkinson went a bit further, developing a geometric efficient frontier.

All of these analyses are instructive and useful to the investor who wants to take path into account, but because the efficient frontier is heavily constrained by the assumed constraint on leverage, it’s not as useful for us. What we want is to take the most efficient portfolio in geometric terms, and take up or down the risk of that portfolio to reflect our tolerance for capital loss. In other words, we want a geometric capital market line. The intuitive outcome of doing this is that we can plot the highest point on this line as the Full Kelly portfolio. The second, and perhaps more satisfying outcome, is that we can retrospectively identify that scaling back from Full Kelly just looks like delevering on this geometric capital market line.

The below figure plots each of these items, including a Half Kelly portfolio that defines ruin as any scenario in the path in which losses exceed 50%, rather than full bankruptcy. The Half Kelly portfolio delivers the highest total return over this period without ever experiencing a drawdown of 50%.

Source: Salient, as of December 31, 2016. For illustrative purposes only.

When we de-lever from the Full Kelly to Half Kelly portfolio, we drop from a terrifying 44% annualized volatility number (which experiences an 80% drawdown at one point) to 18.5%, closer to but still materially higher in risk than most aggressive portfolios available from financial advisors or institutional investors.

This can be thought of in drawdown space as well for investors or advisors who have difficulty thinking in more arcane volatility terms. The below exhibit maps annualized volatility to maximum loss of capital over the analysis period. As mentioned, the 50% maximum drawdown portfolio historically looks like about 18.5% in volatility units.

Source: Salient, as of December 31, 2016. For illustrative purposes only.

For many investors, their true risk tolerance and investment horizon makes this whole discussion irrelevant. Traditional methods of thinking about risk and return are probably serving more conservative investors quite well. And there are some realities that anyone thinking about taking more risk needs to come to terms with, a lot of which I’m going to talk about in a moment — there’s a reason we wanted to talk about this in geometric terms, and it’s all about risk. But for those with a 30, 40 or 50-year horizon, for the permanent institutions with limited cash flow needs, it’s reasonable to ask the question: is the amount of risk in the S&P 500 Index or in a blend of that with the Bloomberg Barclays Aggregate Bond Index the right amount of risk to take? Or can we be taking more? Should we be taking more?

Did you think that was rhetorical? Nope.

Many investors can – and if they are acting as fiduciaries probably ought to — take more risk.

If every hedge fund manager jumped off a bridge…

This may not be a message you hear every day, but I’m not telling you anything novel. Don’t just listen to what your advisors, fund managers and institutional peers are telling you. They’re as motivated and influenced by career risk concerns as the rest of us. Instead, look at what they’re doing.

The next time you have a conversation with a sophisticated money manager you work with, ask them where they typically put their money. Yes, many of them will invest alongside you because that is right and appropriate (and also expected of them). But many more, when they are being honest, will tell you that they have a personal account or an internal-only strategy operated for staff, that operates at a significantly higher level of risk than almost anything they offer to clients. Vehicles with 20%, 25% or even 30% volatility are not uncommon. Yes, some of this is hubris, but some of it is also the realization on the part of professional investors that maximizing portfolio returns — if that is indeed your objective — can only be done if we strip back the conventions that tell us that the natural amount of risk in an unlevered investment in broad asset classes is always the right amount of risk.

Same thing with the widely admired investors, entrepreneurs and business operators. The individual stocks that represent their wealth are risky in a way that dwarfs most of what we would be willing to tolerate in individual portfolios. We explain it away with the notion that they are very skilled, or that they have control over the outcomes of the company — which may be true in doses — but in reality, they are typically equally subject to many of the uncontrollable whims that drive broader macroeconomic and financial market outcomes.

Then observe your institutional peers who are increasing their allocations to private equity and private real estate. They’re not just increasing because hedge funds have had lower absolute returns in a strong equity environment, although that is one very stupid reason why this is happening. It’s also happening because institutions are increasingly aware that they have limited alternatives to meet their target returns. While few will admit it explicitly, they use private equity because it’s the easiest way to lever their portfolios in a way that won’t look like leverage. In a true sense of uncertainty or portfolio level risk, when the risk of private portfolios is appropriately accounted for, I believe many pools of institutional capital are taking risk well beyond that of traditional equity benchmarks.

Many of the investors we all respect the most are already taking more risk than they let on, but explain it away because it’s not considered “right thinking.”

To Whom Much is Given

When we make the decision to take more risk, however, our tools and frameworks for managing uncertainty must occupy more of the stage. This isn’t only about our inability to build accurate forecasts, or even our inability to build mostly accurate stochastic frameworks based on return and volatility, like the Monte Carlo simulations many of us build for clients to simulate their growth in wealth over time. It’s also because the kinds of portfolios that a Full Kelly framework will lead you to are usually pretty risky. Their risk constraint is avoiding complete bankruptcy, and that’s not a very high bar. The things we have to do to capture such a high level of risk and return also usually disproportionately increase our exposure to big, unpredictable events. If you increase the risk of a portfolio by 20%, most of the ways you would do so will increase the exposure to these kinds of events by a lot more than 20%.

Taken together, all these things create that famous gap between our realized experience and what we expected going in. This is a because most financial and economic models assume that the world is ergodic. And it ain’t. I know that’s a ten-dollar word, but it’s important. My favorite explanation of ergodicity comes from Nassim Nicholas Taleb, who claims to have stolen it from mathematician Yakov Sinai, who in turns claims to have stolen it from Israel Gelfand:

Suppose you want to buy a pair of shoes and you live in a house that has a shoe store. There are two different strategies: one is that you go to the store in your house every day to check out the shoes and eventually you find the best pair; another is to take your car and to spend a whole day searching for footwear all over town to find a place where they have the best shoes and you buy them immediately. The system is ergodic if the result of these two strategies is the same.

There are infinite examples of investors making this mistake. My mind wanders to the fund manager who offers up the fashionable but not-very-practical “permanent loss of capital” definition of risk, a stupid definition that is the last refuge of the fund manager with lousy long-term performance. “Sure, it’s down 65%, but that’s a non-permanent impairment!” Invariably, the PM will grumble and call this a 7-standard deviation event because he assumed a world of ergodicity. Because of the impact of a loss like this on the path of our wealth, we’ll now have to vastly exceed the average expected return we put in our scenario models in Excel just to break even on it.

“It’s not a permanent impairment of capital!”

It matters what path our portfolios follow through time. It matters that our big gains and losses may come all at once. It matters to how we should bet and it matters to how we invest. You cannot stir things apart!

So if you’ve decided to take risk as an investor, how we do avoid this pitfall? Consider again the case of the entrepreneur.

The entrepreneur’s portfolio is concentrated, which means that much of his risk has not been diversified away. A lot of that is going to be reflected in the risk and return measures we would use if we were to plot him on the efficient frontier. That doesn’t necessarily mean his risk of ruin will appear high, and his analysis might, in fact, inform the entrepreneur that he ought to borrow and hold this business as his sole investment. He’s done the work, performed business plan SWOT analyses, competitor analyses, etc., and concluded that he has a pretty good grasp of what his range of outcomes and risks look like.

In an ergodic world, this makes us feel all warm and fuzzy, and we give ourselves due diligence gold stars for asking all the right questions. In a non-ergodic world, the guy dies using his own product. A competitor comes out of nowhere with a product that immediately invalidates his business model. A bigger player in a related industry decides they want to dominate his industry, too. And these are just your usual tail events, not even caused the complexity of a system we can’t understand but by sheer happenstance. For the entrepreneur, all sorts of non-tail events over time may materially and permanently change any probabilistic assessment going forward. How do we address this?

The first line of defense as we take more risk must be diversification. After all, there is a reason why the Kelly Portfolios distribute the risk fairly evenly across the constituent asset classes.[3]

Even that isn’t enough. Consider also the case of the leveraged investor in multiple investments with some measure of diversification, for example a risk parity investor, Berkshire Hathaway[4], or the guy who went Full Kelly per our earlier example, but without the whole perfect information thing. This investor has taken the opposite approach, which is to diversify heavily across different asset classes and/or company investments. His return expectation is driven not so much by his ability to create an outcome but by the exploitation of diversification. As he increases his leverage, his sensitivity to the correctness of his point-in-time probabilistic estimates of risk, return and correlations between his holdings will increase as well. In an ergodic world, this is fine and dandy. In a non-ergodic world, while he has largely mitigated the risk of idiosyncratic tails, he is relying on relationships which are based on a complex system and human behaviors that can change rapidly.

Thus, the second line of defense as we take more risk must be adaptive investing. Sometimes the only answer to a complex system is not to play the game, or at least to play less of it. Frameworks which adapt to changing relationships between markets and changing levels of risk are critical. But even they can only do so much.

Liquidity, leverage and concentration limits are your rearguard. These three things are also the only three ways you’ll be able to take more risk than asset classes give you. They are also the three horsemen of the apocalypse. They must be monitored and tightly managed if you want to have an investment program that takes more risk.

It’s not my intent to end on a fearful note, because that isn’t the point at all. More than asset class selection, more than diversification, more than fees, more than any source of alpha you believe in, nothing will matter to your portfolio and the returns it generates more than risk. And the more you take, the more it must occupy your attention. That doesn’t mean that we as investors ought to cower in fear.

On the contrary, my friends, fortune favors the bold.


[1] Back in 1989, Grauer and Hakansson undertook a somewhat similar analysis on a finite, pre-determined set of weightings among different assets with directionally similar results. Over most windows the optimal backward-looking levered portfolio tends to come out with a mid-30s level of annualized volatility.

[2] For this and the other exhibits and simulations presented here, I’m very grateful to my brilliant colleague and our head of quantitative strategies at Salient, Dr. Roberto Croce.

[3] And that reason isn’t just “we’re at the end of a 30-year bond rally,” if you’re thinking about being that guy.

[4] One suspects Mr. Buffett would be less than thrilled by the company we’re assigning him, but to misquote Milton Friedman, we are all levered derivatives users now.


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Chili P is My Signature: Things that Don’t Matter #5

Jesse After His Chili P Phase

Walter: Did you learn nothing from my chemistry class?
Jesse: No. You flunked me, remember, you prick? Now let me tell you something else. This ain’t chemistry — this is art. Cooking is art. And the shit I cook is the bomb, so don’t be telling me…
Walter: The shit you cook is shit. I saw your setup. Ridiculous. You and I will not make garbage. We will produce a chemically pure and stable product that performs as advertised. No adulterants. No baby formula. No chili powder.
Jesse: No, no, chili P is my signature!
Walter: Not anymore.
Breaking Bad, Season 1, Episode 1

“There was only one decline in church attendance, and that was in the late 1960s, when the Vatican said it was not a sin to miss Mass. They said Catholics could act like Protestants, and so they did.“
— Rodney Stark, Ph.D.

She should have died hereafter;
There would have been a time for such a word.
To-morrow, and to-morrow, and to-morrow,
Creeps in this petty pace from day to day
To the last syllable of recorded time,
And all our yesterdays have lighted fools
The way to dusty death. Out, out, brief candle!
Life’s but a walking shadow, a poor player
That struts and frets his hour upon the stage
And then is heard no more: it is a tale
Told by an idiot, full of sound and fury,
Signifying nothing.
— William Shakespeare, Macbeth, Act 5, Scene 5

“I can’t do it if I think about it. I would fall down, especially if I’m wearing street shoes,” he said, laughing. “It wasn’t something I did because I wanted to. I didn’t even know I did that until someone showed me a video.”
— Fernando Valenzuela about his unique windup to the LA Times (2011)

Fernando-mania

Baseball was in the midst of a crisis in 1981.

In the years prior, competition for talent in larger markets had driven player salaries higher and higher. This caused owners to seek increasing restrictions on free agency. The players’ union went on strike in June, right in the middle of the season. Fans were furious, and mostly with the owners, as is the usual way of things. We still hate millionaires, of course, but we positively loathe billionaires. While the strike ended by the All-Star break in early August, work stoppages and disputes of this sort have often been the signposts of baseball’s long, slow march to obscurity against the rising juggernaut of American football and the sneaky, if uneven, popularity of basketball. It was not a riskless gamble for either party, and as future strikes taught us, the aftermath could have gone very badly.

But not this time. You see, baseball had a secret weapon to quickly bring fans back after the 1981 strike: a “short fat dark guy with a bad haircut.” His name was Fernando Valenzuela.

Fernando was an anomaly in another long, slow march — that of baseball’s transition from a pastime to something more clinical, more analytical, more athletic. We were at a midpoint in the shift from the everyman-made-myth that was Babe Ruth or the straight-from-the-storybook folk hero like Joe DiMaggio to the brilliant, polished finished products of baseball academies today. Only a few years after 1981, we would see the birth of the new generation of uberathletes in Bo Jackson, a man who many still consider among the most gifted natural athletes in history. Only a decade earlier, the top prospect in baseball was one Greg Luzinski. The two weighed about the same. Their body composition was just a little bit different.

Fernando was certainly a physical throwback of the Luzinski variety, but so much more. He was a little pudgy. His hair was, long, shaggy and unkempt. More to the point, everything he did was inefficient, out of line with trends in the league. His windup was long and tortured, with a high leg kick that reached shoulder level in his early years and chest level in his older, slightly chubbier years. It featured an unnecessary vertical jerk of his glove straight upward near the end, and most uniquely, a glance to the heavens that became a signature of Fernando-mania. To stretch the inefficiency to its natural limits, his most effective pitch was a filthy screwball, a pitch that had been popular for decades but had already significantly waned by the early 1980s. Fathers and coaches taught their sons that it would hurt their arms (which a properly thrown screwball does not do), and by the late 1990s the pitch that ran inside on same-handed batters was all but extinct, except in Japan, where a very similar pitch called the shuuto continued to find adherents.

There were many reasons he captured the national imagination. He was a gifted Mexican pitcher in Los Angeles, a city full of baseball-obsessed Mexican-Americans and migrant workers. He was also truly marvelous as a 20-year old rookie in 1981. His stretch of eight games between April 9th and May 14th still ranks as one of the most dominant in history. Eight wins. Eight complete games. Five shutouts. Sixty-eight strikeouts. And that was how he started his career!(1)

But more than anything, I think, it was the pageantry and the spectacle of it all. The chubby, mop-top everyman who came out of nowhere with a corny sense of humor, who threw from a windup out of a cartoon, who threw a pitch that nobody else threw anymore. It was inefficient and ornamental and just so unnecessary — and we loved it. I still do. It was even how I was taught to pitch growing up. My father told me and instructed me to throw with “reckless abandon”, and so in my windup I would rotate my hips and point my left toe at second base before kicking it in a 180-degree arc at a shoulder level, nearly falling to the ground from the violent shift in weight after every pitch.

Alas, the efficiency buffs who disdained such extravagances were and are mostly right. While Valenzuela had a long and decent career, the greatest pitchers of the modern era — Roger Clemens, Pedro Martinez and especially Greg Maddux — all thrived on efficient mechanics and a focus on a smaller number of high quality pitches.(2) While a screwball is nice, and in many ways unique, it also isn’t particularly effective as a strikeout pitch in comparison to pitches with more vertical movement like, say, curveballs, split-finger fastballs or change-ups, or pitches that can accommodate lateral movement AND velocity, like sliders and cut-fastballs.

There’s a lesson in this.

As humans, especially humans in an increasingly crowded world where we can be instantly connected to billions of other people, the urge to stand out, to carve out a different path, can be irresistible. This influences our behavior in a couple of ways. First, it drives us to cynicism. Think back on the #covfefe absurdity. If you’re active on social media, by the time you thought of a funny #covfefe joke, your feed was probably already filled with an equal number of posts that decided that the meme was over, using the opportunity to skewer the latecomers to the game. Those, too, were late to the real game, which had by that time transitioned to new ironic uses of the nonsense word. A clever idea that is shared by too many quickly becomes an idea worthy of derision. And so the equilibrium — or at least the dominant game theory strategy — is to be immediately critical of everything.

It also makes us inexorably prone to affectation. We must add our own signature, that thing that distinguishes us or our product; the figurative chili-powder-in-the-meth of whatever our form of productive output happens to be.  Since we are all writers of one sort or another now, we feel this acutely in how we communicate. When part of what you want to be is authentic in your communication, our introspection becomes a very meta thing — we can talk ourselves into circles about whether we’re being authentic or trying inauthentically to appear authentic. But we’re always selling, and while our need for a unique message has exaggerated this tendency, at its core it clearly isn’t a novel impulse. People have been selling narratives forever. But if there’s a lesson in Epsilon Theory, surely it is that successful investors will be those who recognize, survive and maybe even capitalize on narrative-driven markets — not necessarily those whose success is only a function of their ability to push substance-less narratives of their own.

Perhaps most perniciously, our urge to stand out is also an urge to belong to a Tribe — to find that small niche of other humans that afford us some measure of human interaction while still permitting us to define ourselves as a Thing Set Apart. The screwball, the chili powder, the fancy windup, the obscure quotes about Catholicism from sociology Ph.D.s in your investing think-piece — instead of a barbaric yawp, it becomes a signal to your tribe. When pressed, our willingness to rip off the steering wheel and adopt a competitive strategy becomes dominant, a necessity. Lingering in the back of our heads as we go all-in on our tribe is the knowledge that our tribal leaders, no matter who they are, will sell us down the river every time.

In our investing lives, when we build portfolios, we know full well how many options our clients or constituents have, so these three competing impulses drive our behaviors: cynicism, affectation and tribalism. The cynical, nihilistic impulse shouts at us that nothing matters enough to justify risking being fired, and so we end up choosing the solution that looks most like what everyone else has done. That’s the ultimate equilibrium play we’re all headed toward anyway, right? The affectation impulse requires that we add a little something to distinguish us from our peers. A dash of chili powder. A screwball here or there, or an outlandish delivery to delight and astonish. Our tribal impulse compels us toward the right-sounding idea that makes us part of a group (I’m looking at you, Bogleheads). More frequently, we’re motivated by a combination of all three of these things in one convoluted, ennui-laden bit of arbitrary decision-making.

The real kick in the teeth of all this is that many of the things we are compelled to do by these impulses are actually good and important things, even Things that Matter. But because of the complex rationale by which we arrive at them (and other biases besides), we often implement the decisions at such a halfhearted scale that they become irrelevant. In other, worse cases, the decisions function like the tinkering we discussed in And They Did Live by Watchfires, potentially creating portfolio damage in service of a more compelling marketing message or to satisfy one of these impulses. In both cases, these flourishes and tilts are too often full of sound and fury, signifying nothing.

Too Little of a Good Thing

What, exactly, are we talking about? Well, how about value investing, for starters?

I think this one pops up most often as a form of the tribal impulse, although clearly many advisors and allocators use it as a way to add a dash of differentiation as well. Now, most of us are believers in at least a few investing tribes, each with its own taxonomy, rituals, acolytes and list of other tribes we’re supposed to hate in order to belong. But none can boast the membership rolls of the Value Tribe (except maybe the Momentum Tribe or the Passive Tribe). And for good reason! Unlike most investment strategies and approaches devised, buying things that are less expensive and buying things that have recently gone up in price can both be defended empirically and arrived at deductively based on observations of human behavior. The cases where science is really being applied to investing are very, very rare, and this is one of them. Rather than pour more ink into something I rather suppose everyone reading this believes to one extent or another, I’d instead direct you to read the splendid gospel from brothers Asness, Moskowitz and Pedersen on the subject. Or, you know, if you’re convinced non-linearities within a population’s conditioning to sustained depressing corporate results and lower levels of expected growth mean that such observations are only useful for analysis of the actions of an individual human and can’t possibly be generalized or synthesized into a hypothesis underpinning the existence of the value premium as an expression of market behavior, then don’t read it. Radical freedom!

What is shocking is how ubiquitous this belief is when I talk to investors, and how little investors demonstrate that belief in their portfolios. We adhere to the tribe’s religion, but now that it’s not a sin to skip out, we only attend its church on Christmas and Easter. And maybe after we did something bad for which we need to atone.

Value is the more socially acceptable tribe (let’s be honest, momentum has always had a bit of a culty, San Diego vibe), so let’s use that as our case study. Since I’m worried I’m leaving out those for whom cynicism is the chosen neurosis, let’s use robo-advisors to illustrate that case study. They’re instructive as a general case as well, since they, by definition, seek to be an industry-standard approach at a lower price point. Now, of the two most well-advertised robos, one — Wealthfront — mostly ignores value except in context of income generation. The other — Betterment — embraces it in a pretty significant way. I went to their very fine website and asked WOPR what a handsome young investment writer ought to invest in to retire around 2045. Here is what they recommended:

Source: Betterment 2017. For illustrative purposes only.

Pretty vanilla, but then, that’s kind of the idea of the robo-advisor. But I see a lot of registered investment advisors and this is also straight out of their playbook. It’s tough to find an anchor for the question “I know I want/need value, but how much?” As a result, one of the most common landing spots I see is exactly what our robot overlords have recommended: half of our large cap equities in core, and the other half in value. We signal/yawp a bit further: we can probably also afford to do it in the smaller chunks of the portfolios, too. Lets just do all of our small cap and mid cap equities in a value flavor. As for international and emerging equities, we don’t want to scare the client with any more line items or pie slices invested in foreign markets than we need, so let’s just do one big core allocation there.

I’m putting words in a lot of our mouths here, but if you’re an advisor or investor who works with clients and this line of thinking doesn’t feel familiar to you, I’d really like to hear about it. Because this is exactly the kind of rule of thumb I see driving portfolio decisions with so many allocators that I speak to. But how do we actually get to a portfolio like this? If you think there’s a realistic optimization or non-rule-of-thumb-driven investment process that’s going to get you here, let’s disabuse ourselves of that notion.

Could plugging historical volatility figures and capital markets expectations into a mean/variance optimizer get you to this split on value vs. core? In short? No. No, we know that this is an impossible optimizer solution because the diversification potential at the portfolio level — what we call the Free Lunch Effect in this piece — would continue to rise as we allocated more and more of our large cap allocation to a value style (and less and less to core). In other words, while the intuition might be that having both a core and value allocation is more diversifying (more pie slices!), that just isn’t true. In a purely quantitative sense, you’d be most diversified at the portfolio level with no core allocation at all!

Free Lunch Effect of Various Allocations to Large Cap Value vs. Large Cap Core in Example Portfolio

Source: Salient 2017. For illustrative purposes only.

If your instinct is to say that doesn’t look like much diversification, however, you’d be right as well. Swinging our large cap portfolio from no value to nothing but value reduces our portfolio risk by around 8bp without reducing return (i.e., the Free Lunch). That’s not nothing, but it’s damn near. The reason is that the difference between the Russell 1000 Value Index and the Russell 1000 Index or the S&P 500, or the difference between your average large cap value mutual fund and your average large cap blend mutual fund, is not a whole lot in context of how most things within a diversified portfolio interact. Said another way, the correlation is low, but the volatility is even lower, which means it has very little capacity to impact the portfolio. Take a look below at how much that value spread contributes to portfolio volatility. The below is presented in context of total portfolio volatility, so you should read this as “If I invested all 32% of the large cap portion of this portfolio in a value index and none in a core index, the value vs. core spread itself would account for about 0.1% of portfolio volatility.”

Percentage of Portfolio Volatility Contributed by LC Value-Core Spread

Source: Salient 2017. For illustrative purposes only.

Fellow tribesmen, does this reflect your conviction in value as a source of return? Some of you may quibble, “Well, this is just in some weird risk space. I think about my portfolios in terms of return.” Fine, I guess, but that just tells the same story. Consider how most value indices are constructed, which is to say a capitalization weighted splitting of “above average” vs. “below average” stocks on some measure (e.g., Russell) or multiple measures (e.g., MSCI) of value. We may have in our heads some of the excellent research on the value premium, but those are almost always expressed as regression alphas or as spread between high and low quintiles or deciles (Fama/French) or tertiles (Asness et al). In most cases they are also based on long/short or market neutral portfolios, or using methodologies that directly or indirectly size positions based on the strength of the value signal rather than the market capitalization of the stock. There are strategies based on these approaches that do capitalize on the long-term edge of behavioral factors like value. But that’s not really what you’re getting when you buy most of these indices or the many products based on them.(3)

So what are you getting? For long-only stock indices globally, probably around 80bp(4) and that assumes no erosion in the premium vs. long-term average. Most other research echoes this – the top 5 value-weighted deciles of Fama/French get you about 1.1% annualized over the average since 1972, and comparable amounts if you go back even further. Using the former figure, if you swung from 0% value to 32% value in your expression of your large cap allocation — frankly a pretty huge move for most investors and allocators — we’re talking about a 26bp difference in expected portfolio returns. Again, not nothing, but if our portfolio return expectations are, say, 8%, that’s a 3.2% contributor to our portfolio returns under fairly extreme assumptions.

Does this reflect your conviction in value as a source of return? No matter how we slice it, the ways we implement even fundamental, widely understood and generally well-supported sources of return like value seem to be a bit long on the sound and fury, but unable to really drive portfolio risk or return. Why is this so hard? Why do we end up with arbitrary solutions like splitting an asset class between core and value exposure like some sort of half-hearted genuflection in the general direction of value?

Because we have no anchor. We believe in value, but deep down we struggle to make it tangible. We don’t know how much of it we have, we don’t even know how much of it we want. We struggle even to define what “how much” means, and so we end up picking some amount that will allow us to sound sage and measured to the people who put their trust in us to sound sage and measured.

I’m going to spend a good bit of time talking about how I think about the powerful diversifying and return-amplifying role of behavioral sources of return like value as we transition our series to the Things that Matter, so I’ll beg both your patience and indulgence for leaving this as a bit of a resolutionless diatribe. I’ll also beg your pardon if it looks like I’ve been excessively critical of the fine folks who put together the portfolio that has been our case study. In truth, that portfolio goes much further along the path than most.

The point is that for various behavioral reasons, our style tilts like value, momentum or quality occupy a significant amount of our time, marketing and conversations with clients, and — by and large — signify practically nothing in terms of portfolio results. In case I wasn’t clear, yes, I am saying that value investing — at least the way most of us pursue it — doesn’t matter.

The Magically Disappearing Diversifier

The time we spend fussing around with miniscule style tilts, however, often pales in comparison to the labor we sink into our flourishes in alternatives, especially hedge funds. Some of this time is well-spent, and well-constructed hedge fund allocations can play an important role in a portfolio. When I’m asked to look at investors’ hedge fund portfolios, there are usually two warning signs to me that the portfolios are serving a signaling/tribal purpose and not some real portfolio objective:

  1. Low volatility hedge funds inside of high volatility portfolios that aren’t using leverage
  2. Hedge fund portfolios replacing Treasury or fixed income allocations

Because of the general sexiness (still, after all these years!) of hedge fund allocations to many clients or constituents, the first category tends to be the result of our affectation impulse. We want to add that low-vol, market-neutral hedge fund, or the fixed income RV fund that might have been taking some real risk back in 2006 when they could lever it up a bajillion times, not because of some worthwhile portfolio construction insight, but perhaps because it allows us to sell the notion that we are smart enough to understand the strategies and important enough to have access to them. Not everyone can get you that Chili P, after all. In some cases, sure — we are signaling to others that we are also part of that smart and sophisticated enough crowd that invests in things like this. In the institutional world, where it’s more perfunctory to do this, it’s probably closer to cynicism: “Look, I know I’m going to have a portfolio of low-vol hedge funds, so let’s just get this over with.”

For many clients and plans — specifically those where assets and liabilities are mostly in line and the portfolio can be positioned conservatively, say <10% long-term volatility — that’s completely fine. But for more aggressive allocations, there is going to be so much equity risk, so much volatility throughout the portfolio, that the notion that these portfolios will serve any diversification role whatsoever is absurd. They’re just taking down risk, and almost certainly portfolio expected returns along with it. Unless you feel supremely confident that you’ve got a manager, maybe a high frequency or quality stat arb fund, that can run at a 2 or 3 Sharpe, it is almost impossible to justify a place for a <4% volatility hedge fund in a >10% target risk portfolio. They just won’t move the needle, and there are better ways to improve portfolio diversification, returns or risk-adjusted returns.

The second category starts to veer out of “Things that Don’t Matter” territory into “Things that Do Matter, but in a Bad Way.” More and more over the last two years, as I’ve talked to investors their primary concern isn’t equity valuations, global demographics, policy-controlled markets, deflationary pressures, competitive currency crises, protectionism, or even fees! It’s their bond portfolio. The bleeding hedge fund industry has been looking for a hook since their lousy 2008 and their lousier 2009, and by God, they found it: sell hedge funds against bond portfolios! Absolute return is basically just like an income stream! There seems to be such a strong consensus for this that it may have become that cynical equilibrium.

No. Just no.

It’s impossible to overstate the importance of a bond/deflation allocation for almost any portfolio. This is an environment that prevails with meaningful frequency that has allowed the strong performance of one asset historically: bonds, especially government bonds (I see you with your hands raised in the back, CTAs, but I’m not taking questions until the end). The absolute last thing any allocator should be thinking about if they have any interest in maintaining a diversified portfolio, is reducing their strategic allocation to bonds. I’ll be the first to admit that when inflationary regimes do arrive, they can be long and persistent, during which the ability of duration to diversify has historically been squashed. The negative correlation we assume for bonds today is by no means static or certain, which is one of the reason I favor using more adaptive asset allocation schemes like risk parity that will dynamically reflect those changes in relationship. But even in that context, the dominance and ubiquity of equity-like sources of risk means that almost every investor I see is still probably vastly underweight duration.

Now many of us do have leverage limitations that start to create constraints, and so I won’t dismiss that there are scenarios where that constraint forces a rational investor not to maximize risk-adjusted returns, but absolute returns. I’m also willing to consider that on a more tactical basis, you may be smarter than I am, and have a better sense of the near-term direction of bond markets. In those cases, reducing bond exposure, potentially in favor of absolute return allocations, may be the right call. But if you have the ability to invest in higher volatility risk parity and managed futures, or if you have a mandate to run with some measure of true or derivatives-induced leverage, my strong suspicion is that you’ll find no cause to sell your bond portfolios in favor of absolute return.

Ultimately, it’s hard to be too prescriptive about all this, because our constraints and objective functions really may be quite different. To me, that means that the solution here isn’t to advise you to do this or not to do that, except to recommend this:

Make an honest assessment of your portfolio, of the tilts you’ve put on, and each of your allocations. Do they all matter? Are you including them because of a good faith and supportable belief that they will move the portfolio closer to its objective?

If we don’t feel confident that the answer is yes, it’s time to question whether we’re being influenced by the sorts of behavioral impulses that drive us elsewhere in our lives: cynicism, affectation and tribalism. In the end, the answer may be that we will continue to do those things because they feel right to us and our clients. And that may be just fine. A little bit of marketing isn’t a sin, and if your processes that have served you well over a career of investing are expressed in context of a particular posture, there’s a lot to be said for not fixing what ain’t broken. There’s nothing wrong with an impressive-looking windup, after all, until it adversely impacts the velocity and control of our pitches.

What is a sin, however, is when a half-hearted value tilt causes us to be comfortable not taking advantage of the full potential of the value premium in our portfolios. When the desire to get cute with low-vol hedge funds causes us to undershoot our portfolio risk and return targets. Perhaps most of all, when we spend our most precious resource — time — designing these affectations. We will be most successful when we reserve our resources and focus for the Things that Matter.


(1) Please – no letters about his relief starts in 1980. If MLB called him a rookie, imma call him a rookie.

(2) Probably the only exception in this conversation is Randy Johnson, who, while mostly vanilla in his mechanics, would probably get feedback from a coach today about his arm angle, his hip rotation and a whole bunch of other things that didn’t keep him from striking out almost 5,000 batters.

(3) As much as marketing professionals at some of the firms with products in this area would like to disagree and call their own product substantially different, they all just operate on a continuum expressed by the shifting of weightings toward cheaper stocks. Moving from left to right as we exaggerate the weighting scheme toward value, the continuum basically looks like this: Value Indices -> Fundamental Indexing -> Long-Only Quant Equity -> Factor Portfolios

(4) Simplistically, we’re just averaging the P2 and half of the P3 returns from the Individual Stock Portfolios Panel of Value and Momentum Everywhere, less the average of the full universe. An imperfect approach, but in broad strokes it replicates the general half growth/half value methodology for the construction of most indices in the space.


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What a Good-Looking Question: Things that Don’t Matter #2

Peter Griffin buys a tank.

Peter Griffin: What can you tell me about this one?

Car Salesman: Oh, that’s just an old tank I use for those commercials where I declare war on high prices. Now about that sedan…

Peter Griffin: Hang on there, slick. Now I see your game. We come in here wanting a practical car, but then you dangle this tank in front of me and expect me to walk away. Now, I may be an idiot, but there is one thing I am not, sir, and that, sir, is an idiot. Now, I demand you tell me more about this tank!

Car Salesman: Well, if you’re looking for quality, then look no further.

Peter: That’s more like it! Tell me, what are the tank’s safety features?

Car Salesman: What a good-looking question. Three inches of reinforced steel protects your daughter from short-range missile attacks.

Peter: I see. And does the sedan protect against missiles?

Car Salesman: It does not.

Family Guy, Season 5, Episode 3, “Hell Comes to Quahog”

There was an unclouded fountain, with silver-bright water, which neither shepherds nor goats grazing the hills, nor other flocks, touched, that no animal or bird disturbed not even a branch falling from a tree. Grass was around it, fed by the moisture nearby, and a grove of trees that prevented the sun from warming the place. Here, the boy, tired by the heat and his enthusiasm for the chase, lies down, drawn to it by its look and by the fountain. While he desires to quench his thirst, a different thirst is created. While he drinks he is seized by the vision of his reflected form. He loves a bodiless dream. He thinks that a body, that is only a shadow. He is astonished by himself, and hangs there motionless, with a fixed expression, like a statue carved from Parian marble.

Flat on the ground, he contemplates two stars, his eyes, and his hair, fit for Bacchus, fit for Apollo, his youthful cheeks and ivory neck, the beauty of his face, the rose-flush mingled in the whiteness of snow, admiring everything for which he is himself admired. Unknowingly he desires himself, and the one who praises is himself praised, and, while he courts, is courted, so that, equally, he inflames and burns. How often he gave his lips in vain to the deceptive pool, how often, trying to embrace the neck he could see, he plunged his arms into the water, but could not catch himself within them! What he has seen he does not understand, but what he sees he is on fire for, and the same error both seduces and deceives his eyes.
― Ovid, Metamorphoses, Book III

Brian: Look, you’ve got it all wrong! You don’t need to follow me. You’ve got to think for yourselves! You’re all individuals!

Crowd: Yes! We’re all individuals!

Brian: You’re all different!

Crowd: Yes! We’re all different!

Man: I’m not.

Crowd: Shhh!

Life of Brian (1979)

There may be members of the committee who might fail to distinguish between asbestos and galvanized iron, but every man there knows about coffee — what it is, how it should be made, where it should be bought — and whether indeed it should be bought at all. This item on the agenda will occupy the members for an hour and a quarter, and they will end by asking the Secretary to procure further information, leaving the matter to be decided at the next meeting.

― C. Northcote Parkinson, Parkinson’s Law: Or the Pursuit of Progress

One of our portfolio managers at Salient started his career working the desk at a retail branch of a large financial services firm in Braintree, Massachusetts. He likes to tell the story of “Danny from Quincy” (pronounced Qwin’-zee). Danny is a rabid Boston sports fan who frequently called in to a local sports talk radio show. Your mind may have already conjured an image of our protagonist, but for the uninitiated, American sports talk radio is community theatre at its most bizarre (and entertaining), its callers a parade of exaggerated regional accents shouting really awful things at no one in particular. Local sports talk radio is even more of an oddity, since on the clear fundamental question, that is, which team everyone supports, practically all parties involved agree.

Lest Bostonians feel singled out, this phenomenon is infinitely transferable. In Buffalo, Pittsburgh, Chicago, Kansas City and Oakland, it is much the same. In each, the listener can expect the same level of anger, whether it is shouting about things everyone listening agrees on, like the ‘fact’ that the NFL has always preferred Peyton Manning to Tom Brady and that Deflategate just boiled down to jealousy, or relatively petty items of disagreement, like the ‘fact’ that Belichick reached on a player in the draft who would have been available in the 4th or 5th rounds when what they really needed was help at defensive back.

When Danny from Quincy wandered into our colleague’s Braintree branch, Danny’s voice was distinctive enough that he was immediately recognized. From their conversation, it was clear that this happened to Danny all the time. Here was a local celebrity minted by nothing other than the fact that he could shout agreed-upon concepts at the loudest possible volume and with proper non-rhotic diction.

It is hardly a novel observation that disputes among those who agree on the most critical questions and disagree on details are often among the most violent. After all, more died in the disputes between French Catholics and Huguenots alone than in all three of the Crusades. And it took twice as long for John Lennon and Paul McCartney to get in a recording studio together after the Yoko Ono Experience than it took for King George III to receive John Adams as ambassador after the Treaty of Paris. As investors, however, we have turned this seemingly normal human behavior into an art form.

There are all sorts of social and psychological reasons why we so enjoy wallowing in issues of lesser import with those with whom we otherwise largely agree. One of the main reasons is that big, important issues — the ones that divide us into broad groups — tend to be either issues outside of our control, or complex and more difficult to understand. By contrast, the smaller, less important issues are more likely to be understood by a wider range of people. Or at least they are more familiar.

In 1957, C. Northcote Parkinson’s eponymously titled book Parkinson’s Law: Or the Pursuit of Progress dubbed this phenomenon the Law of Triviality. In referencing the work of a finance committee, it concluded that “…the time spent on any item of the agenda will be in inverse proportion to the sum involved.” In other words, the more trivial something is, the more time we are likely to spend discussing it.

In his book, Parkinson dramatically reenacts the three agenda items before a finance committee: a $10 million nuclear reactor, a $2,350 bicycle shed and a $57 annual committee meeting refreshment budget. As you might expect, the details of a plan to build a nuclear reactor would fall well outside the abilities of even sophisticated committees, and even for those members with some sophistication, the task of bringing legitimate concerns or questions before an otherwise unknowledgeable group is daunting. In Parkinson’s example, the knowledgeable Mr. Brickworth considers commenting on the item but “…does not know where to begin. The other members could not read the blueprint if he referred to it. He would have to begin by explaining what a reactor is and no one there would admit that he did not already know.” He concludes that it is “better to say nothing.”

The item passes after two and a half minutes of discussion.

The next item before the committee is the discussion of a committee to build a bicycle shed for clerical staff. The discussion includes a range of topics, from cost to necessity to the choice of construction materials. As Parkinson puts it, “A sum of $2,350 is well within everybody’s comprehension. Everyone can visualize a bicycle shed. Discussion goes on, therefore, for 45 minutes, with the possible result of saving some $300. Members at length sit back with a feeling of achievement.” It is not difficult to guess where the meeting goes from there. It becomes a multi-hour marathon discussion of the $57 coffee budget, which leads to a demand for additional research and a subsequent meeting.

This dynamic should be familiar to almost anyone in the investment industry. Whether you are a financial advisor, institutional allocator, professional investor or just an individual trying to navigate the waters of an industry seemingly designed with the purpose of confusing investors, you’re at risk of more than a few Bike Shed discussions.

The code-driven investor doesn’t waste his time on the Things that Don’t Matter.

The Biggest Bike Shed of them All

Problematically, the biggest, most egregious Bike Shed probably dominates more discussions between asset owners (individuals, institutional investors) and asset managers than anything else: talking stocks.

Stop for a moment and take an inventory. If you’re an individual investor, think about your last meeting with your financial advisor. Financial advisors, pension fund execs, endowment managers, think about your last meeting with your fund managers. How much of the meeting did you spend talking about or listening to them talk about stocks and companies? A third of the meeting? Half? More? Maybe you were well-behaved and focused on things that matter, but let’s be honest with each other. We all talk about stocks way too much and we know it.

It makes me think a bit about doctors in the post-WebMD era. Once upon a time, an experienced and well-trained physician could practice medicine with deference — almost a sort of detached awe — from the patient. That is, until the internet convinced every one of us who ran in sheer terror from the syllabus for organic chemistry that we have every bit as much skill as a doctor in diagnosing ourselves with every kind of malady. For the professional investor — especially the professional investor in common stocks — this has been the case for centuries. There is no profession for which the lay person considers himself so prepared to succeed as in the management of stock portfolios.

Lest you feel any empathy for the professional in this case, our layperson isn’t entirely wrong. Not because he has some latent talent but because the average stock portfolio manager probably doesn’t. This shouldn’t be provocative. It also isn’t an opinion, as Nobel Prize winner Eugene Fama famously said, and as I rather less famously agreed in I Am Spartacus. It’s math. To pick winners and losers in the stock market is a zero-sum game, which means that for every winner who is overweight a good stock, there is a loser who is underweight. And both of them are paying fees.

As I wrote previously, it is true that this notion is driven by a narrow capitalization-weighted view of the world. It also doesn’t take into account that investors with different utility functions may differ in what they consider a win. Yet the point remains: so long as math is still a thing, on average, active managers won’t outperform because they can’t. This is a big reason why over long periods only 3% of mutual fund managers demonstrate the skill to do so after fees (Fama & French, 2010).

But the question of whether we ought to hire active stock managers isn’t even the Bike Shed discussion — after all, the phony active vs. passive debate took the top spot on this ignominious list. Instead, the mistake is the obscene amount of time we as investors spend thinking about, discussing and debating our views on individual stocks.

So why do we spend so much time doing this?

Well, for one, it’s a hell of a lot of fun. Whether we are investors on our own behalf or professionals in the industry, dealing with financial lives and investments can be drudgery. As individuals, it’s taxes and household budgets and 401(k) deferral percentages and paying people fees. As professionals, it’s due diligence and sales meetings and prospectuses and post-Christmas-party trips to HR training. Daydreaming about a stock where you really feel like you have a unique view that you haven’t heard from someone else is a blast by comparison.

Fun aside, familiarity plays an even more significant role. Each investor encounters companies with public stocks as a consumer and citizen on a daily basis. We are familiar with Apple because we buy their phones and tablet devices. We know Exxon because we have a friend or family member who works there. We work at another pharmaceuticals company and we think that gives us an edge in understanding Merck.

It is so important to recognize that these things give you an edge in talking about a stock, but absolutely zero advantage in investing in one. Lest we think that something is better than nothing, in this case, that is decidedly not so. When we know nothing, and know that we know nothing (h/t Socrates) about a company that will matter to its stock, we are far more likely to make sensible decisions concerning it, which typically means making no decision at all. When we know nothing and think we know something valuable, we are more likely to take actions for which we have no realistic expectation of a positive payoff. But it’s worse than taking a random uncompensated risk, because this kind of false-knowledge-driven investing also engenders all sorts of emotional and behavioral biases. These biases will drive you to hold positions longer than you should, ignore negative information and all other sorts of things that emotionally compromised humans do.

We also spend time doing this because talking about companies and stocks gives us a sort of feeling of parity that we usually don’t feel when we’re talking to our fund managers and financial advisors. These guys are often some of the smartest people we get to talk to. It can be intimidating. We look for any common ground we can find. We love being told we asked a very good or smart question. Strangely, my questions were much smarter when I worked at a $120 billion fund than since that time. I must have gotten stupider.

In case this is hitting a bit too close to home, let me assure you that you are not alone.

Before I was an asset manager — when I represented an asset owner — I was occasionally invited to speak at conferences. One such conference was in Monaco. Now, our fund had an investment with a hedge fund based there and given the travel expenses associated with conducting diligence meetings in Europe, combining the two made good fiscal sense. It also meant that our usual practice of conducting diligence in pairs wasn’t really feasible. So, I was running solo.

On Tuesday, I attended the conference, giving speeches to other asset owners about what effective diversification in a hedge fund portfolio looks like, and then speaking later on a panel to an audience of hedge funds on how to present effectively to pension fund prospects. I could barely leave the room without a mob of people looking for a minute of my time or a business card, and friends, I’m not a particularly interesting public speaker. I felt like a big shot.

On Wednesday, I met our fund manager for lunch. I don’t remember the name of the venue, but it was attached to some Belle Époque hotel with a patio overlooking the Mediterranean. From the front of the hotel, we were ushered through a sort of secret passageway by a tuxedoed man who, when we arrived at the patio, was joined by three similarly attired partners who proceeded to lift and move a 400-some-odd-pound concrete planter that isolated the table we would be sitting at from the rest of the patrons. When we had passed by and sat down — not without a Monsieur-so-and-so greeting and obsequious bow of the head to my host — they then lifted and returned the planter to its place and disappeared.

The gentleman welcomed me to his city graciously in Oxbridge English, but I knew from my notes that he spoke Italian, German and French as a native as well. I think he was conversant in Dutch and several other languages besides. He was an activist investor, and had such a penetrating understanding of the companies in which he invested (usually no more than 5 or 6 at any time) that I could tell immediately I was several leagues out of my depth. He was so intimately familiar with the tax loss carryforward implications of eight potential cross-border merger partners for a portfolio financial services holding that I deemed it impossible he didn’t sport an eidetic memory.

By the time I had finished a cup of bisque and he had finished (food untouched) passionately discussing solutions to flawed regulator-driven capital adequacy measures, I was so thoroughly terrified of this brilliant and just disgustingly knowledgeable man that I couldn’t help but grasp at the thing I knew I could hang with him on. I wasn’t going to be the sucker at this table!

“So, what about your position in this British consumer electronics retailer?”

And down we go into the rabbit hole, Alice. Ugh.

Look, we’ve all been there. Or maybe it’s just me and none of you have ever felt intimidated and stupid and reached out for something, anything. Either way, it’s so critical that you know that your fund manager, even your financial advisor, loves it when you want to talk stocks. Loves. It. He loves it because he knows his client will have some knowledge of them, which gives him a chance to establish common ground and develop rapport with you. It keeps the meeting going without forcing him to talk about the things he doesn’t want to talk about, namely his performance, his fees and how he actually makes money for his clients.

It’s a great use of time for him — he’s selling! — and an absolutely terrible use of time and attention for you, the investor. If they drive the conversation in that direction, stop them. If you commit an unforced error and try to get them to sell you the tank instead of the sedan, stop yourself.

Why It Doesn’t Matter

But is thinking about your individual stock investments and those made on your behalf really always such a terrible use of time? Even though I asked the question I just answered in a rhetorical way that might have indicated I was going to change my mind and go a different direction here, yeah, no, seriously, it’s a ridiculously bad use of time. Let me be specific:

If you are spending more than a miniscule fraction of your day (say, 5% of whatever time you spend working on or talking to people about investments) trying to pick or talk about individual stocks, and you are not (1) an equity portfolio manager or (2) managing a portfolio with multiple individual stock positions that are more than 5% of total capital each, this is absolutely one of the Five Things that Don’t Matter.

Why? The answer has more to do with the nature of stock picking than anything else, but in short:

  1. You probably don’t have an edge.
  2. Even if you do, being right about it won’t necessarily make the stock go up.
  3. And even if it sometimes did, it wouldn’t matter to your portfolio.

There are empirical ways to tell you how hard it is to have an edge. Academics and asset managers alike have published innumerable studies highlighting the poor performance of active equity managers against broad benchmarks and pointing out the statistical inevitability of outliers like Buffett or Miller. But you’ve probably already read those, and if you’re like me you want to know why. So here’s why it’s so damned hard.

There are only two possible ways to outperform as a stock-picker:

Method 1: Having a different view about a company’s fundamental characteristics than the market expects, being right, and the market recognizing that you are right.

Method 2: Having a view that market perception about a company will change or is changing, estimating how that will impact buying and selling behaviors, and being right.

That’s it. Any investment strategy that works must by definition do one of these things, whether consciously or subconsciously. Deep value investors, quality investors, Holt and CFROI and CROCE aficionados, DDM wonks, intrinsic value guys, “intuitive” guys, day traders, the San Diego Momentum Mafia, quants — whatever. It’s all packaging for different ways of systematically or intuitively cracking one of these two components in a repeatable way.

The problem for almost all of us — individuals, FAs, fund managers, asset owners — is that we want to think that doing truly excellent fundamental analysis guided by a rigorous process and well-constructed models is enough. Friends, this is the fundamental message of Epsilon Theory, so I hope this doesn’t offend, but fundamental analysis alone is never enough to generate alpha.

This is what leads us to focus our efforts vainly on trying to find the most blindingly intelligent people we can find to build the best models and find that one-off balance sheet detail in the 10-K notes that no one else has found. We’re then disappointed after three straight years of underperformance, and then we fire them and hire the next rising star. It is what leads us to spending time researching companies ourselves, evaluating their new products, comparing their profitability ratios to those of other companies, and the like.

This isn’t to say that fundamental analysis doesn’t have value to a valid equity investment strategy. It certainly can and may, but as a necessary but insufficient component of Method 1 described above. The missing and absolutely indispensable piece is an accurate picture of what the market actually knows and is expecting for the stock, and how participants will react to your fundamental thesis being correct.

This is where (probably) you, I and the overwhelming majority of fund managers and financial professionals sit. We may have the capacity to understand what makes a company tick, how it works. We may even be able to identify the key variables that will determine its success. But when it comes to really assessing what the next $500 million of marginal buyers and sellers — you know, the people who determine what the price of the thing actually is — really think about this stock and how they would respond to our thesis being right, I believe we are typically lost. We’ve built a Ferrari with no tires to grip the road. A beautiful, perfectly engineered, useless masterpiece of an engine.

This is one of the reasons I think that platforms that canvass the views of the people that mostly closely influence the decision-making framework of buy-side investors (i.e., sell-side research) are one of the rare forms of true and defensible edge in our industry. It’s also why I think highly of quantitative investors who systematically exploit behavioral biases that continuously creep into both Methods above over time. It’s why statistical arbitrage and high-speed trading methods work by focusing on nothing other than how the marginal buyer or seller will implement a change in their views. It’s why I think you can make an argument for activist investing on the basis that it takes direct control of both a key fundamental factor and how it is being messaged to market participants. It’s also why we’re so excited about the Narrative Machine.

But it’s also why — despite my biases toward all things technological — I also retain respect for the rare instances of accumulated knowledge and intuition about the drivers of investor behavior. I can add no thoughts or added value concerning the most recent allegations against him, but Lee Cooperman is the best case study I can think of for an investor who gets Method 1. This is a man who defines old school in terms of fundamental analysis. He sits at a marble desk, shelves behind him bedecked with binders of his team’s research and Value Line books flanking a recording studio-style window looking out on his trading floor. His process leverages a large team of hungry young analysts in a classic you-propose-I-dispose model. So yes, the fundamental analysis is the centerpiece. But in my opinion what set him and his returns apart was his ability from 50 years in this city, training or working with half of his competitors, to understand how his peers — the marginal buyer and seller — would be thinking about and would respond to what he discovered in his team’s fundamental analysis.

Ladies and gents, if you think the savvy kid from the Bronx who gets people in an intuitive sense doesn’t occupy a prominent seat at this table, you simply don’t know what you’re talking about.

But even so, let’s daydream. Let’s imagine that you are, in fact, Leon-effing-Cooperman in the flesh, with all his skills and experience. But instead of holding his relatively concentrated book, you’re holding what you and I probably own or advise for our clients or constituents (or at least should): some form of a balanced and diversified portfolio. Even if you knew that you were good at this one part of the game, would it even matter?

Sadly, not really.

You see, in a typical diversified investor’s portfolio, the idiosyncratic characteristics of individual securities — the ones driven by the factors truly unique to that company — are unlikely to represent even a fraction of a fraction of the risk an investor takes.

Consider for example a generalized case where an investor built a portfolio from an index portfolio — say US stocks — and a separate “tracking error” portfolio. This is kind of what we’re doing when we select an active manager. Even with relatively robust expectations for tracking error and the unrealistic assumption that all of the tracking error came from idiosyncratic (those unique to that security) sources with no correlation to our equity portfolio, the bets made on individual stocks account for less than 10% of total risk.

Percent of Portfolio Risk from Active Risk

Source: Salient Partners, L.P., as of 03/31/2017

Now think about this in context of our larger portfolio! In practice, most stock discussions take place in context of multi-manager structures or portfolios, in which case the number of stocks will rise and the level of tracking error will fall even further than the above. To take that even further, the majority of the sources of that tracking error will often not be related so much to the individual securities selected by the underlying managers, but a small number of systematic factors that end up looking like equity risk, namely (1) a bias to small cap stocks and (2) a bias toward or away from market volatility.

In the context of any adequately diversified portfolio, stock picks are a Bike Shed. If it is your job in the context of a very large organization to evaluate the impact of active management, you may bristle a bit at this. I remember how I justified it to myself by saying, “Well, I’m only talking about stocks this much because I want to get a picture of how she thinks about investing, and what her process is.” That’s all well and good, if true. Even so, consider whether the discussion is really allowing you to fully determine whether the advisor or fund manager has an edge under the Methods described above.

For the rest of us, spending time thinking about, discussing and debating your stock picks or those of your advisors is almost certainly a bad use of time, no matter how enjoyable. That’s why it sits at #2 on our Code’s list of Things that Don’t Matter. And if you still think we’ve given fund managers too much of a pass here, you’ll find more to like at #3.

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I Am Spartacus: Things that Don’t Matter #1

I am Spartacus!

Herald: I bring a message from your master, Marcus Licinius Crassus, commander of Italy. By common of His Most Merciful Excellency, your lives are to be spared! Slaves you were, and slaves you remain. But the terrible penalty of crucifixion has been set aside on the single condition that you identify the body or the living person of the slave called Spartacus.

Antoninus (Tony Curtis): I am Spartacus!

Other Slaves: I’m Spartacus!

— Spartacus (1960)

We are all active managers, friends. The sooner the better that we realize this and start focusing on the when and why it makes sense for investors, instead of wishcasting “good environments for active management” that don’t exist. While we may not be obscuring each other’s identities, it’s probably time for more of us to stand up and say, “I am an active manager!” Although, I suppose it is worth mentioning that shortly after this scene, Spartacus is forced to kill his best friend before being crucified.

“Active management is a zero-sum game before cost, and the winners have to win at the expense of the losers.”

— Eugene Fama, Ph.D., Investment News, October 7, 2013

Walter Sobchak: Am I wrong?

The Dude: No, you’re not wrong.

Walter: Am I wrong?

The Dude: You’re not wrong, Walter. You’re just an asshole.

Walter: All right then.

— The Big Lebowski (1998)

“You heard about it? Yeah you had to.

Mm hmm I know you changed your mind,

You ain’t the only one with bad news.

I know that it made you feel strange, huh?

You was right in the middle complainin’

and forgot what you was cryin’ about.”

— Mystikal, “Bouncin’ Back” (2001)

Ahchoo: Look, Robin, you don’t have to do this. I mean, this ain’t exactly the Mississippi. I’m on one side. I’m on the other side. I’m on the east bank, I’m on the west bank. It’s not that critical.

Robin: It’s the principle of the thing.

— Robin Hood: Men in Tights (1993)

It seems like every few years the debate on active vs. passive management comes back in full force — not that any of this is new, of course. DFA, Vanguard, and brilliant investors and writers like Charlie Ellis have been shouting from the mountaintop about what a waste of time active management is for decades now. So why the breathless excitement from the financial press on the topic this time? Mostly because they haven’t the faintest idea what they’re talking about.

Don’t mistake me: Charlie Ellis isn’t wrong. Jack Bogle isn’t wrong. Gene Fama isn’t wrong. But the basis for the broader active vs. passive debate is misleading at best, and outright fraud at worst. Let’s get a few objective, unequivocal facts out of the way about active management:

  1. There is no such thing as a “good” or “bad” environment for active management.
  2. Everyone — including you, dear reader — is an active investor.
  3. Costs matter. The rest of this debate is a waste of time.

This is why the debate over active vs. passive is #1 on my list of Things that Don’t Matter.

The myth of the good or bad environment for active management

Most investors have at least a passing familiarity with the notion of the zero-sum game. It is an academic and logically sound construct which says that if one investor is overweight or long a particular security relative to its market capitalization weighted share of that market, it stands to reason that another investor must necessarily be underweight or short.

This is true to the point of tautology, and there’s no disputing it. It’s true, and it’s used as the fundamental, deterministic argument for why active management can never  work. If every winner is offset with a loser and everyone is paying fees, over time the house is going to win. It’s also why Dr. Fama has famously and accurately said that if the data shows that active management is working, then the data is wrong.

But if this is the case, how it is possible that there are “good” or “bad” environments for active managers or stock pickers? Wouldn’t every environment just be equally bad to the tune of the drag from fees and expenses? If so, why are we talking about this historically bad period for fund managers?

The reason we are talking about it is that practically every study, allocator, advisor, researcher and article covering this topic considers passive management in context of a particular benchmark or index. However, not every pool of assets benchmarked against an index is necessarily seeking to outperform that index on an absolute basis. Even more to the point, these pools certainly don’t confine their investments to constituents of that index.

If you weighted each of the benchmarks used by investors, funds and institutions by the value of each of those pools of capital, you would end up with something that looked very different from the market capitalization of the world’s financial assets. By way of the most obvious example, I suspect that the total value of pools of capital that benchmark themselves formally against the S&P 500 Index (“S&P 500”) vastly exceeds the market capitalization of the S&P 500 itself. The value that does so informally is probably many multiples of that.

The way that this plays out in practice is surprisingly consistent. Consider a U.S. large-cap strategy. There are four biases that are ubiquitous — uniform might be nearer the mark — among both actively managed mutual funds and institutional separate accounts:

  • investments in small- and mid-cap stocks
  • investments in higher volatility / higher beta stocks
  • investments in international stocks
  • cash holdings

In other words, there is no good or bad environment for active management. There are good or bad environments for the relatively static biases that are almost universal among the pools of capital that benchmark themselves to various indices.

If you are an allocator, financial advisor or individual investor, you may have heard from your large-cap fund managers during the first half of 2016 how bad an environment it was for active management. Maybe they said that the market is ignoring fundamentals or that everything is moving together or that the market is adopting a short-term view.

That’s about 50% story-telling and 50% confirmation bias. It’s also 0% useful.

In an overwhelming majority of cases, that environment is simply one in which either small-caps underperformed or high beta / high-risk stocks did.

From the same investor vantage point, the second half of 2016 probably looked different. We often say that we don’t have a crystal ball, but I have a very reliable prediction about your annual reviews with your U.S. large-cap managers. They may inform you that “fundamentals started mattering again” in the second half of the year. The market started paying attention to earnings quality and management decisions and [insert generalization that will fill up the allotted time for the meeting here].

No they didn’t.

Small-cap and high-beta or high volatility stocks bounced back really hard. When you do your review with your active small-cap managers, you may be surprised when they, on the other hand, are doing so poorly relative to their benchmarks. Why? Because small-cap managers manage portfolios that are typically above the market cap of the Russell 2000 Index (“Russell 2000”) and nearly uniformly underperform when small-cap is trouncing large-cap.

Let’s take a look at how and why this is. The chart below splits up every month from January 2001 through January 2017 by the spread between the return of the Russell 2000 and the S&P 500. The chart plots the average excess return of each of the funds in the Morningstar Large Blend category against the S&P 500 by how pronounced the difference between small- and large-caps was for the period. In other words, what we’re looking at is whether large-cap funds have done better or worse vs. the S&P when large-caps are outperforming small-caps in general.

The results are stark. In the bottom decile of months for the large vs. small spread (i.e., the 10% of months where small-caps do the BEST), large-cap blend managers outperform the S&P by an annualized rate of just over 4%. By contrast, in the top decile for large-cap vs. small-cap, they underperform by an annualized rate of nearly 5%!

Those bad environments for stock picking your fund managers are so fond of telling you about? They’re only bad because almost all of your active managers are picking riskier stocks and putting small- and mid-caps in your large-cap fund.

Sources: Bloomberg, Ken French U.S. Research Returns, Morningstar as of 01/31/17. For illustrative purposes only. Past performance is no guarantee of future results.

Unfortunately for those of you who breathed a sigh of relief in August and September of 2016 because your active managers were ‘working’ again, this doesn’t necessarily mean your fund manager had a flash of brilliance from the patio of his Southampton rental. Low beta just spat up all the excess returns it generated in the first half of the year.

These kinds of biases are not confined to large-cap U.S. equity managers, of course. As mentioned, your small-cap managers are usually going to get smoked when small-caps are roaring. Your international equity managers are all buying emerging markets stocks around the edges of their portfolios (that’s why they were geniuses until the last three years or so, and now we think they’re stupid). Your fixed income guys are often just about all doing “core plus” even if they don’t say so on the wrapper. Your long/short equity and event funds have persistent sectoral biases.

Every category of active management has its own peculiar but fairly persistent bias against its benchmark.

OK, so active managers have consistent biases. So what? It still rolls up to the same zero-sum game, right? Yes, but it’s useful to think about and understand what’s going on underneath the hood. Namely, since we know that actively managed large-cap mutual funds and institutional separate accounts are usually underweight mega-caps, large-caps and lower risk stocks relative to the passive universe, we must fill in the gap: who is overweight these stocks to offset?

The answer is, well, strategies other than large-cap strategies, or ones that are not benchmarked to the S&P 500 or Russell 1000 Index (“Russell 1000”). That can include a wide variety of vehicles, but at the margin it includes (1) hedge funds, (2) individual or corporate holders of ‘un-benchmarked’ securities portfolios and (3) portfolios that are targeting a sub-set or variant of the large-cap universe. Clearly it also includes all sorts of strategies benchmarked to other markets entirely, one of the most common examples being multi-asset portfolios. As illustrated in the exhibit below, the S&P 500 is very obviously not completely owned by pools of capital that are benchmarked to the S&P 500.

For illustrative purposes only.

Hedge funds provide us with the most exaggerated example of one of the ways this happens. Let’s presume that large-cap mutual funds are underweight low volatility mega-cap stocks to the tune of $50 billion.

Now let’s examine two cases — in the first case, $25 billion in hedge fund capital is deployed to buy all $50 billion of that on a levered long basis. In the second case, $100 billion of hedge fund capital is used, meaning that the funds chose to hold 50% cash and spent the remaining 50% on the mega-cap stocks.

If the S&P 500 is up and a particular publication wants to talk about hedge fund returns, they’re going to talk about the first scenario as a heroic period of returns for hedge funds. In the second scenario, hedge funds are a scam run to prop up the richest 1%. Neither is true, of course — well, not on this basis alone, at least — because the benchmark isn’t capturing the risk posture that an investor is using as part of its asset allocation scheme to select that investment — in this case a long/short hedge fund.

Consider as well that many of the strategies that are ‘filling in’ for active large-cap managers’ underweights to Johnson & Johnson and ExxonMobil do so in tactical or multi-asset portfolios, many of which are going to be compared against different benchmarks entirely. Still, others may be executed under minimum volatility or income equity mandates. When you consider that the utility functions of investors in these strategies may be different, and that one investor may reasonably emphasize risk-adjusted returns rather than total returns, or that two investors might have meaningfully different needs for income in context of their overall financial situation, the argument starts to get very cloudy indeed.

There is no such thing as a passive investor

So when faced with an income objective like the example above, the response of many in the passive management camp is typically some form of, “Well, just buy more of a passive income equity fund, or move more money to bonds.”

It is this kind of argument that exemplifies why this active vs. passive debate feels so phony, so contrived. As it is too often applied, the mantra of passive management emphasizes avoiding funds that make decisions that many those allocators/advisors/investors will then make themselves and charge/pay for under the guise of asset allocation.

If a fund manager rotates between diversified portfolios of stocks, bonds, credit and other assets based on changing risks or income characteristics, he gets a Scarlet A for the vile, dastardly active manager he is. If an investor or allocator does the same thing by allocating between passively managed funds in each of those categories, he posts about it on Reddit and gets 200 up-votes.

If a fund manager invests in a portfolio of futures (lower cost passive exposure than ETFs, by the way) to reach a target level of risk and diversification without trying to pick individual securities at all, just go ahead and tattoo the “A” on their deserving forehead in permanent ink. If an investor or allocator does the same thing to build a portfolio that is equally or more distinct from a global cap-weighted benchmark using more expensive ETFs, we can only celebrate them and hope they pen a scathing white paper on the systemic risks embedded in risk-targeted investment strategies.

Everyone is often doing the same things — and usually paying for it — in different ways. To paraphrase Ahchoo (bless you), some of you are on the east bank and some of you are on the west bank. But this ain’t exactly the Mississippi. It’s not. That. Critical.

What IS critical is understanding why this debate occupies such an august (notorious?) spot on this list of Things that Don’t Matter. And here it is: I am fully confident that not a single passive investor owns a portfolio of global financial assets in the respective weights of their total value or market capitalization. Instead, they allocate away from the cap-weighted global financial assets standard based on (1) their risk appetite, (2) in order to better diversify and (3) to satisfy certain personal goals around income and taxes.

Let’s put some figures on this. Using a basic methodology from public sources (while acknowledging without having access to his letters that Paul Singer has adopted a similar approach) as of the end of 2015 or 2016 — we’re talking big numbers here, so the timeliness isn’t that important — global investable assets look something like the pie chart below.

Sources: BIS, Savillis, World Bank. For illustrative purposes only.

Yes, there’s overlap here. Yes, if you added in capital raised to invest in private companies it would add another 1.2% to equities, and including insider holdings in private companies would expand this more (although debatably). It also doesn’t include a range of commodities or commodities reserves because of the (generally) transitive nature of the former and indeterminate nature of the latter. But it’s good enough for our purposes. So does your portfolio look like this? If not, let me be the first to initiate you into the club of active managers.

Every investor is an active investor when it comes down to the major dimensions of asset allocation: risk, diversification, income and liquidity. Eliminating strategies as “Active” because they seek to manage risk, improve diversification, increase income or take advantage of greater (or lesser) liquidity is wrong-headed at best and hypocritical at worst. Most of all, it harms investors.

The S&P 500 example is not universally applicable, of course. Public large capitalization stocks are well-covered by indices, and so index funds that track the S&P 500 or Russell 1000 are generally sound examples of vehicles seeking to avoid the pitfalls of the zero-sum game. That is not always the case, however.

One example of this I like to use is the Alerian MLP Index. It is a perfectly acceptable representation of the energy MLP market, and deserves credit for being the first to track this growing asset class. It tracks 50 key constituents with around $300 billion in total market cap. The overall universe of listed midstream energy companies, however, is closer to 140-150 and sports a market cap of nearly $750 billion. There are several index funds and ETFs that track the index, and dozens of so-called actively managed funds that include a higher number of securities that look rather more like the cap-weighted market for energy infrastructure!

A more mainstream example of this might be the Dow Jones Industrial Index, famous for being used by CNBC every day and by a professional investor for the last time in the mid-1950s. This index of 30 stocks covers only a fraction of the breadth of listed stocks in the U.S. with meaningfully different characteristics on a dozen dimensions, and is tracked by a “passive” ETF with roughly $12 billion in assets. Meanwhile, lower cost large-cap mutual funds and accounts with 120 holdings built to deliver higher than typical income at a lower volatility than the market are “actively managed.” To make matters more complicated, many asset classes that are a meaningful — and diversifying — part of the cap-weighted global market simply do not have passive alternatives.

There is a wonderful local convenience store chain called Wawa where I went to college. I had a…uh…friend whose laziness was so well-developed that his diet was entirely driven by what was available at Wawa. If they didn’t have it, he didn’t eat it. Now, there are all sorts of delightful things to be had there, so don’t get me wrong. But if you’ve got something other than hot dogs, ham sandwiches or Tastykake Krimpets on your mind, you’re out of luck.

I’m sorry to say that the Index Fund Wawa is fresh out of vehicles owning securities issued by private companies, listed securities in certain niches of the markets (e.g., preferred securities in real estate) with meaningful diversification and income benefits, less liquid instruments and others unable to be held in daily or continuous liquidity vehicles. Many of these strategies have significant diversification potential and roles within portfolios. Many are often highly effective tools for adding income, efficient risk mitigation or other characteristics to portfolios. Many may even have higher expected returns or risk-adjusted returns. But you’ll have to leave the Wawa to get them.

None of this even begins to venture into hedge funds and other alternative strategies, and how they ought to be considered in context of the overall debate. To be sure, the answer is probably to observe that the same criticisms and defenses that can be brought to bear against (or on behalf of) active management apply to strategies like this as well.

But to a great extent for hedge funds (and to a lesser one for traditional strategies), there are potential sources of return that may be consistently exploited that have nearly the same empirical and fundamental underpinnings of market exposure as a source of potential return. At their core — and consistent with how we discuss them in Epsilon Theory — they are almost universally an expression of human behavior. Whether expressed through premia to value, momentum or carry premia, or else biases investors have toward quality, lottery payoffs, liquidity and the like, the great irony is that the most successful actively managed strategies are those that exploit the fact that many investors are often drawn to the appeal of active management under the guise of ‘beating the market.’

For this reason, it is somewhat baffling to see the disdain with which passionate passive investors treat many alternative strategies. If we believe that active management can persistently lead investors to predictable bad outcomes driven by understandable behavioral biases and responses to information, why would we be averse to approaches that seek to exploit this? Most investors can, however, see the forest for the trees on this issue. That is the reason why, despite the contraction in actively managed strategies more broadly, most projections for the market for liquid alternatives posit a doubling of assets in the space between 2015 and 20201.

1Both PWC and McKinsey’s work on this topic comes highly recommended.

Costs matter (and the rest of this debate is a waste of time)

Now admittedly, I have waited quite a long time to talk about one of the principal concerns around many actively managed strategies: cost.

In coming around to this critical consideration, it is worth circling back to the indisputable fact that Bogle, Fama and Ellis are right. Trying to beat the market in most markets by being overweight the right stocks and underweight the right stocks is a loser’s game. Doing that and paying fees for it makes it an expensive loser’s game. The reality is that investors need to put the pitchforks away and ask themselves a set of simple questions when considering actively managed funds:

  • Portfolio Outcomes: For a fund that is making active decisions that I would be responsible for in my asset allocation, like risk targeting, biasing toward income and yield or improving portfolio diversification, do the benefits justify the cost?
  • Incomplete or Non-Existent Indexes: When an active fund provides better diversification or coverage of an opportunity set, or covers an investment universe that is not investable through passive solutions, do the benefits justify the cost?
  • Exploiting Bad Behaviors: When investing to exploit the behaviors of other investors who are trying to beat the market to increase returns or improve risk-adjusted returns of my portfolio, do the benefits justify the cost?

It shouldn’t be any surprise that this will often lead you to the same conclusion as a passive management zealot, because adding value that justifies the cost on the above dimensions is still really hard. Active management should be evaluated with the same critical eye and cost/benefit analysis every one of us use when we make active decisions in our portfolio design and asset allocation. But because it won’t always be the case, the process matters, and the code you follow to draw your investment conclusions matters.

The active vs. passive debate, on the other hand, does not. Enough.

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Invisible Threads: Matrix Edition

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-hickory-lake

Old Hickory Lake, TN – visible light image (L) and infrared light image (R)

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-morpheus

Morpheus: Do you believe in fate, Neo?
Neo: No.
Morpheus: Why not?
Neo: Because I don’t like the idea that I’m not in control of my life.
Morpheus: I know *exactly* what you mean. Let me tell you why you’re here. You’re here because you know something. What you know you can’t explain, but you feel it. You’ve felt it your entire life, that there’s something wrong with the world. You don’t know what it is, but it’s there, like a splinter in your mind, driving you mad.

“The Matrix” (1999)

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-cypher

Cypher: I know this steak doesn’t exist. I know that when I put it in my mouth, the Matrix is telling my brain that it is juicy and delicious. After nine years, you know what I realize? [Takes a bite of steak]
Cypher: Ignorance is bliss.

“The Matrix” (1999)

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-agent-smith

Agent Smith: Never send a human to do a machine’s job.

“The Matrix” (1999)

A right-hand glove could be put on the left hand if it could be turned round in four-dimensional space.
Ludwig Wittgenstein, “Tractatus Logico-Philosophicus” (1921)

I remember that I’m invisible and walk softly so as not awake the sleeping ones. Sometimes it is best not to awaken them; there are few things in the world as dangerous as sleepwalkers.
Ralph Ellison, “Invisible Man” (1952)

Tell people there’s an invisible man in the sky who created the universe, and the vast majority will believe you. Tell them the paint is wet, and they have to touch it to be sure.
George Carlin (1937 – 2008)

Invisible threads are the strongest ties.
Friedrich Nietzsche (1844 – 1900)

This is the concluding Epsilon Theory note of a trilogy on coping with the Golden Age of the Central Banker, where a policy-driven bull market has combined with a machine-driven market structure to play you false. The first installment – “One MILLION Dollars” – took a trader’s perspective. The second – “Rounders” – was geared for investors. Today’s note digs into the dynamics of the machine-driven market structure, which gets far less attention than Fed monetary policy but is no less important, to identify what I think is an unrecognized structural risk facing both traders and investors here in the Brave New World of modern markets.

To understand that risk, we have to wrestle with the investment strategies that few of us see but all of us feel … strategies that traffic in the invisible threads of the market, like volatility and correlation and other derivative dimensions. A few weeks ago (“Season of the Glitch”) I wrote that “If you don’t already understand what, say, a gamma hedge is, then you have ZERO chance of successfully trading your portfolio in reaction to the daily ‘news’.” Actually, the problem is worse than that. Just as dark matter (which as the name implies can’t be seen with visible light or any other electromagnetic radiation, but is perceived only through its gravitational effects) makes up some enormous portion of the universe, so do “dark strategies”, invisible to the vast majority of investors, make up some enormous portion of modern markets. Perceiving these dark strategies isn’t just a nice-to-have ability for short-term or tactical portfolio adjustments, it’s a must-have perspective for understanding the basic structure of markets today. Regardless of what the Fed does or doesn’t do, regardless of how, when, or if a “lift-off” in rates occurs, answering questions like “does active portfolio management work today?” or “is now a good time or a bad time for discretionary portfolio managers?” is impossible if you ignore derivative market dimensions and the vast sums of capital that flow along these dimensions.

How vast? No one knows for sure. Like dark matter in astrophysics, we “see” these dark strategies primarily through their gravitational pull on obviously visible securities like stocks and bonds and their more commonly visible dimensions like price and volume. But three massive structural shifts over the past decade – the concentration of investable capital within mega-allocators, the development of powerful machine intelligences, and the explosion in derivative trading activity – provide enough circumstantial evidence to convince me that well more than half of daily trading activity in global capital markets originates within derivative dimension strategies, and that a significant percentage (if you held a gun to my head I’d say 10%) of global capital allocated to public markets finds its way into these strategies.

Let me stick with that last structural change – the explosive growth in derivative trading activity – as it provides the best connection to a specific dark strategy that we can use as a “teachable moment” in how these invisible market dimensions exert such a powerful force over every portfolio, like it or not. The chart on the right, courtesy of Nanex’s Eric Scott Hunsader, shows the daily volume of US equity and index option quotes (not trades, but quotes) since mid-2003. The red dots are daily observations and the blue line is a moving average. In 2004 we would consistently see 100,000 options quotes posted on US exchanges on any given day. In 2015 we can see as many as 18 billion quotes in a single day. Now obviously this options activity isn’t being generated by humans. There aren’t millions of fundamental analysts saying, “Gee, I think there’s an interesting catalyst for company XYZ that might happen in the next 30 days. Think I’ll buy myself a Dec. call option and see what happens.” These are machine-generated quotes from machine-driven strategies, almost all of which see the world on the human-invisible wavelength of volatility rather than the human-visible wavelength of price.

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-equity

There’s one and only one reason why machine-driven options strategies have exploded in popularity over the past decade: they work. They satisfy the portfolio preference functions of mega-allocators with trillions of dollars in capital, and those allocators in turn pay lots of money to the quant managers and market makers who deliver the goods. But volatility, like love if you believe The Four Aces, is a many splendored thing. That is, there’s no single meaning that humans ascribe to the concept of volatility, so not only is the direct relationship between volatility and price variable, but so is the function that describes that relationship. The definition of gamma hasn’t changed, but its meaning has. And that’s a threat, both to guys who have been trading options for 20 years and to guys who wouldn’t know a straddle from a hole in the head.

Okay, Ben, you lost me. English, please?

The basic price relationship between a stock and its option is called delta. If the stock moves up in price by $2.00 and the option moves up in price by $1.00, then we say that the option has a delta of 0.5. All else being equal, the more in-the-money the option’s strike price, the higher the delta, and vice versa for out-of-the-money options. But that delta measurement only exists for a single point in time. As soon as the underlying stock price change is translated into an option price change via delta, a new delta needs to be calculated for any subsequent underlying stock price change. That change in delta – the delta of delta, if you will – is defined as gamma.

One basic options trading strategy is to be long gamma in order to delta hedge a market neutral portfolio. Let’s say you own 100 shares of the S&P 500 ETF, and let’s assume that an at-the-money put has a delta of 0.5 (pretty common for at-the-money options). So you could buy two at-the-money put contracts (each contract controlling 100 shares) to balance out your 100 share long position. At this point you are neutral on your overall market price exposure; so if the S&P 500 goes up by $1 your ETF is +$100 in value, but your puts are -$100, resulting in no profit and no loss. But the delta of your puts declined as your S&P ETF went up in price (the options are now slightly out-of-the-money), which means that you are no longer market neutral in your portfolio but are slightly long. To bring the portfolio back into a market neutral position you need to sell some of your ETF. Now let’s say that the S&P goes down by $2. You’ve rebalanced the portfolio to be market neutral, so you don’t lose any money on this market decline, but now the delta of your puts has gone up, so you need to buy some S&P ETF to bring it back into market neutral condition. Here’s the point: as the market goes back and forth, oscillating around that starting point, you are constantly buying the ETF low and selling it high without taking on market risk, pocketing cash all the way along.

There are a thousand variations on this basic delta hedging strategy, but what most of them have in common is that they eliminate the market risk that most of us live with on a daily basis in favor of isolating an invisible thread like gamma. It feels like free money while it works, which attracts a lot of smart guys (and even smarter machines) into the fray. And it can work for a long time, particularly so long as the majority of market participants and their capital are looking at the big hazy market rather than a thread that only you and your fellow cognoscenti can “see”.

But what we’re experiencing in these dark strategies today is the same structural evolution we saw in commodity market trading 20 or 30 years ago. In the beginning you have traders working their little delta hedging strategies and skinning dimes day after day. It’s a good life for the traders plucking their invisible thread, it’s their sole focus, and the peak rate of return from the strategy comes in this period. As more and larger participants get involved – first little hedge funds, then big multistrat hedge funds, then allocators directly – the preference function shifts from maximizing the rate of return in this solo pursuit and playing the Kelly criterion edge/odds game (read “Fortune’s Formula” by William Poundstone if you don’t know what this means) in favor of incorporating derivative dimension strategies as non-correlated return streams to achieve an overall portfolio target rate of return while hewing to a targeted volatility path. This is a VERY different animal than return growth rate maximization. To make matters even muddier, the natural masters of this turf – the bank prop desks – have been regulated out of existence.

It’s like poker in Las Vegas today versus poker in Las Vegas 20 years ago. The rules and the cards and the in-game behaviors haven’t changed a bit, but the players and the institutions are totally different, both in quantity and (more importantly) what they’re trying to get out of the game. Everyone involved in Las Vegas poker today – from the casinos to the pros to the whales to the dentist in town for a weekend convention – is playing a larger game. The casino is trying to maximize the overall resort take; the pro is trying to create a marketable brand; the whale is looking for a rush; the dentist is looking for a story to take home. There’s still real money to be won at every table every night, but the meaning of that money and that gameplay isn’t what it used to be back when it was eight off-duty blackjack dealers playing poker for blood night after night. And so it is with dark investment strategies. The meaning of gamma trading has changed over the past decade in exactly the same way that the meaning of Las Vegas poker has changed. And these things never go back to the way they were.

So why does this matter?

For traders managing these derivative strategies (and the multistrats and allocators who hire them), I think this structural evolution in market participant preference functions is a big part of why these strategies aren’t working as well for you as you thought they would. It’s not quite the same classic methodological problem as (over)fitting a model to a historical data set and then inevitably suffering disappointment when you take that model outside of the sample, but it’s close. My intuition (and right now it’s only intuition) is that the changing preference functions and, to a lesser extent, the larger sums at work are confounding the expectations you’d reasonably derive from an econometric analysis of historical data. Every econometric tool in the kit has at its foundation a bedrock assumption: hold preferences constant. Once you weaken that assumption, all of your confidence measures are shot.

For everyone, trader and investor and allocator alike, the explosive growth in both the number and purpose of dark strategy implementations creates the potential for highly crowded trades that most market participants will never see developing, and even those who are immersed in this sort of thing will often miss. The mini-Flash Crash of Monday, August 24th is a great example of this, as the prior Friday saw a record imbalance of put gamma exposure in the S&P 500 versus long gamma exposure. Why did this imbalance exist? I have no idea. It’s not like there’s a fundamental “reason” for creating exposure on one of these invisible threads that you’re going to read about in Barron’s. It’s simply the aggregation of portfolio overlays by the biggest and best institutional investors in the world. But when that imbalance doesn’t get worked off on Friday, and when you have more bad news over the weekend, and when the VIX doesn’t price on Monday morning … you get the earthquake we all felt 6 weeks ago. For about 15 minutes the invisible gamma thread was cut, and everyone who was long gamma did what you always do when you’re suddenly adrift. You sell.

I can already hear the response of traditional investors: “Somebody should do something about those darn quants. Always breaking windows and making too much noise. Bunch of market hooligans, if you ask me. Fortunately I’m sitting here in my comfortable long-term perspective, and while the quants are annoying in the short-term they really don’t impact me.”

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-statler-waldorf

I think this sort of Statler and Waldorf attitude is a mistake for two reasons.

First, you can bet that whenever an earthquake like this happens, especially when it’s triggered by two invisible tectonic plates like put gamma and call gamma and then cascades through arcane geologies like options expiration dates and ETF pricing software, both the media and self-interested parties will begin a mad rush to find someone or something a tad bit more obvious to blame. This has to be presented in soundbite fashion, and there’s no need for a rifle when a shotgun will make more noise and scatters over more potential villains. So you end up getting every investment process that uses a computer – from high frequency trading to risk parity allocations to derivative hedges – all lumped together in one big shotgun blast. Never mind that HFT shops, for which I have no love, kept their machines running and provided liquidity into this mess throughout (and enjoyed their most profitable day in years as a result). Never mind that risk parity allocation strategies are at the complete opposite end of the fast-trading spectrum than HFTs, accounting for a few percent (at most!) of average daily trading in the afflicted securities. No, no … you use computers and math, so you must be part of the problem. This may be entertaining to the Statler and Waldorf crowd and help the CNBC ratings, but it’s the sort of easy prejudice and casual accusation that makes my skin crawl. It’s like saying that “the bankers” caused the Great Recession or that “the [insert political party here]” are evil. Give me a break.

Second, there’s absolutely a long-term impact on traditional buy-and-hold strategies from these dark strategies, because they largely determine the shape of the implied volatility curves for major indices, and those curves have never been more influential. Here’s an example of what I’m talking about showing the term structure for S&P 500 volatility prior to the October jobs report (“Last Week”), the following Monday (“Now”), and prior years as marked.

epsilon-theory-invisible-threads-matrix-edition-october-13-2015-NFP

Three observations:

  1. The inverted curve of S&P 500 volatility prior to the jobs report is a tremendous signal of a potential reversal, which is exactly what we got on Friday. I don’t care what your investment time horizon is, that’s valuable information. Solid gold.
  2. Today’s volatility term structure indicates to me that mega-allocators are slightly less confident in the ability of the Powers That Be to hold things together in the long run than they were in October 2013 or 2014, but not dramatically less confident. The faith in central banks to save the day seems largely undiminished, despite all the Fed dithering and despite the breaking of the China growth story. What’s dramatic is the flatness of the curve the Monday after the jobs report, which suggests a generic expectation of more short-term shocks. Of course, that also provides lots of room (and profits) to sell the front end of the volatility curve and drive the S&P 500 up, which is exactly what’s happened over the past week. Why is this important for long-term investors? Because if you were wondering if the market rally since the October jobs report indicated that anything had changed on a fundamental level, here’s your answer. No.  
  3. In exactly the same way that no US Treasury investor or allocator makes any sort of decision without taking a look at the UST term structure, I don’t think any major equity allocator is unaware of this SPX term structure. Yes, it’s something of a self-fulfilling prophecy or a house of mirrors or a feedback loop (choose your own analogy), as it’s these same mega-allocators that are establishing the volatility term structure in the first place, but that doesn’t make its influence any less real. If you’re considering any sort of adjustment to your traditional stock portfolio (and I don’t care how long you say your long-term perspective is … if you’re invested in public markets you’re always thinking about making a change), you should be looking at these volatility term structures, too. At the very least you should understand what these curves mean.

I suppose that’s the big message in this note, that you’re doing yourself a disservice if you don’t have a basic working knowledge of what, say, a volatility surface means. I’m not saying that we all have to become volatility traders to survive in the market jungle today, any more than we all have to become game theorists to avoid being the sucker at the Fed’s communication policy table. And if you want to remove yourself as much as possible from the machines, then find a niche in the public markets where dark strategies have little sway. Muni bonds, say, or MLPs. The machines will find you eventually, but for now you’re safe. But if you’re a traditional investor whose sandbox includes big markets like the S&P 500, then you’re only disadvantaging yourself by ignoring this stuff.

Ignorance is not bliss, and I say that with great empathy for Cypher’s exhaustion after 9 years on the Matrix battlefield. After all, we’ve now endured more than 9 years on the ZIRP battlefield. Nor am I suggesting that anyone fight the Fed, much less fight the machine intelligences that dominate market structure and its invisible threads. Not only will you lose both fights, but neither is an adversary that deserves “fighting”. At the same time, though, I also think it’s crazy to ignore or blindly trust the Fed and the machine intelligences. The only way I know to maintain that independence of thought, to reject the Cypher that lives in all of us … is to identify the invisible threads that enmesh us, some woven by machines and some by politicians, and start disentangling ourselves. That’s what Epsilon Theory is all about, and I hope you find it useful.

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When the Story Breaks

The Three Types of Fear:

  • The Gross-out: the sight of a severed head tumbling down a flight of stairs. It’s when the lights go out and something green and slimy splatters against your arm.
  • The Horror: the unnatural, spiders the size of bears, the dead waking up and walking around. It’s when the lights go out and something with claws grabs you by the arm.
  • And the last and worst one: Terror, when you come home and notice everything you own has been taken away and replaced by an exact substitute. It’s when the lights go out and you feel something behind you, you hear it, you feel its breath against your ear, but when you turn around, there’s nothing there.

Stephen King

Brody: You’re gonna need a bigger boat.

“Jaws” (1975)

Back in my portfolio manager days, I was a really good short seller. I say that as a factual observation, not a brag, as it’s not a skill set that’s driven by some great intellectual or character virtue. On the contrary, most short sellers are, like me, highly suspicious of all received wisdom (even when it is, in fact, wise) and have weirdly over-developed egos that feed on the notion of “I’m right even though the world says I’m wrong”. But what set me apart as a short seller were two accidents of experience. First, I didn’t come out of Wall Street, so I wasn’t infected with the long-bias required of those business models. Second, my professional career prior to investing was all about studying mass behaviors and the informational flows that drive those behaviors.

Here’s why that’s important. The biggest difference between shorting and going long is that shorts tend to work in a punctuated fashion. One day I’ll write a full note on the Information Theory basis for this market fact, but the intuition is pretty simple. There’s a constant flow of positive information around both individual stocks (driven by corporate management) and the market as a whole (driven by the sell-side), and as a result the natural tendency of prices is a slow grind up. But occasionally you’ll receive an informational shock, which is almost always a negative, and the price of a stock or the overall market will take a sharp, punctuated decline. The hardest decision for a short seller is what to do when you get this punctuated decline. Do you cover the short, pocket a modest gain, and look to re-establish the position once it grinds higher, as it typically does? Or do you press the short on this informational validation for your original negative thesis? It’s an entirely different mindset than that of most long-only investors, who – because they have the luxury of both time and informational flow on their side – not only tend to add to their positions when the stock is working (my thesis is right, and I’m raising my target price!) but also tend to add when it’s not working (my thesis is right, and this stock is on sale!).

Solving the short seller’s dilemma requires answering one simple question: is the story broken?Is the informational shock sufficient to force long-only investors to doubt not just their facts, but – much more crucially – their beliefs, thus turning them into sellers, too? The facts of the informational shock are almost immaterial in resolving the short seller’s dilemma. Your personal beliefs about those facts are certainly immaterial. The only thing that matters is whether or not the river of information coming out of the sell-side has shifted course in a way that swamps the old belief structures and establishes new Common Knowledge.

The China growth story is now broken. To be clear, I am NOT saying that China’s economy is broken. On the contrary, I’m a China bull. What I’m saying is that what everyone believes that everyone believes about Chinese growth – the Common Knowledge about Chinese growth – has now shifted dramatically for the worse. What I’m also saying is that China-related stocks and markets are going to have a very hard time working until the investors who believed in the China growth story are replaced by investors who believe in a different China story, probably a China value story. That can take a long time and it can be a very painful transition, as any value investor who ever bought a mega-cap tech stock can attest. But it will happen, and that’s a very powerful – and ultimately positive – transformation. Ditto for Emerging Markets in general.

In the meantime, what we’ve been experiencing in markets is the plain and simple fear that always accompanies a broken story. The human reaction to a broken story is an emotional response akin to a sudden loss of faith. It’s a muted form of what Stephen King defined as Terror … the sudden realization that the helpful moorings you took for granted are actually not supporting you at all, but are at best absent and at worst have been replaced by invisible forces with ill intent. The antidote to Terror? Call the boogeyman by his proper name. It’s the end of the China growth story, one of the most powerful investment Narratives of the past 20 years. And that’s very painful, as the end of something big and powerful always is. It will require investors to adapt and adjust if they want to thrive. But it’s not MORE than that. It’s not a sign of the investment apocalypse. It’s the end of one investable story, soon to be replaced with another investable story. Because that’s what we humans do.

Here’s a great illustration of what fear looks like in markets, courtesy of Salient’s Deputy CIO and all-around brilliant guy, Rusty Guinn.

epsilon-theory-when-the-story-breaks-august-25-2015-volatility

These are the cumulative pro forma (i.e., purely hypothetical) returns generated by selling (shorting) the high volatility S&P 500 stocks and buying an off-setting amount of the low volatility stocks (0% net exposure, 200% gross exposure). The factor is up 10% YTD and 15% from the lows in May. Now just to be clear, this is not an actual investment strategy, but is simply a tool we use to identify what factors are working in the market at any point in time. There are any number of ways to construct this indicator, but they all show the same thing – investors have been embracing low volatility (low risk) stocks ever since Greece started to break the European stability story this summer, and that dynamic has continued with the complete breakdown of the China growth story. This is what a flight to safety looks like when you don’t trust bonds because you think the Fed is poised for “lift-off”. This is the fear factor.

Three final Narrative-related points…

First, while the breakdown in the China growth story has reached a tipping point over the past week, this is just the culmination in what has been a two year deterioration of the entire Emerging Market growth story. The belief system around EM’s has been crumbling ever since the Taper Tantrum in the summer of 2013, and it’s the subject of one of the most popular Epsilon Theory notes, “It Was Barzini All Along”. Everything I wrote then is even more applicable today.

Second, I see very little weakness in either the US growth story (best house in a bad neighborhood, mediocre growth but zero chance of recession) or the Narrative of Central Bank Omnipotence. Do I think that the Fed is being stymied in its desire to raise short rates in order to reload its monetary policy gun with conventional ammo? Yes, absolutely. Do I see a significant diminution in the overwhelming investor belief that the Fed and the ECB control market outcomes? No, I don’t. Trust me, I’m keeping my eyes peeled (see “When Does the Story Break?”), because in many respects this is the only question that matters. If this story breaks, then in the immortal words of Chief Brody when he first saw the shark, “You’re gonna need a bigger boat.”

Third, while I’m relatively sanguine about the China growth story breaking down, as I’m confident that there’s a value story waiting in the wings here, I’ll be much more nervous if the China political competence story continues to deteriorate. This is a completely different Narrative than the growth story, and it’s the story that one-party States rely on to prevent even the thought of a viable political opposition. In highly authoritarian one-party nations – like Saddam’s Iraq or the Shah’s Iran – you’ll typically see the competence Narrative focused on the omnipresent secret police apparatus. In less authoritarian one-party nations – like Lee Kuan Yew’s Singapore or Deng Xiaoping’s China – the competence Narrative is more often based on delivering positive economic outcomes to a wide swath of citizens (not that these regimes are a slouch in the secret police department, of course). From a political perspective, this competence Narrative is THE source of legitimacy and stability for a one-party State. In a multi-party system, you can vote the incompetents (or far more likely, the perceived incompetents) out of office and replace them peacefully with another regime. That’s not an option in a one-party State, and if the competency story breaks the result is always a very dicey and usually a violent power transition. I am seeing more and more trial balloons being floated in the Western media (usually with some sort of Murdoch provenance) that indicate “dissatisfaction” with this or that cadre. And it’s not just a markets story any more, as grumblings over the Tianjin fire disaster appear to me to have grown louder over the past week. I haven’t seen this sort of signaling coming out of China in 20 years, and it certainly bears close watching.

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It’s Still Not About the Nail

Reader reaction to the March 31 Epsilon Theory note, “It’s Not About the Nail”, was probably the strongest and most positive for any note to date. The message in a nutshell: financial advisors of all stripes and sizes would be well-served to do more than serve up old-school diversification platitudes in this Brave New World of a bull market that everyone hates, and the behavioral insights of regret minimization are an effective framework for making that adaptation.

This is a message that bears repeating, and thanks to Institutional Investor that’s what’s happening. A condensed version of “It’s Not About the Nail” can be found on the Institutional Investor website here, that piece will appear in the print magazine later this month in their “Unconventional Wisdom” column, and I’ve appended it below.

I think the reason this message strikes a chord is that it not only puts into words what a lot of people are feeling in an inchoate fashion, but also suggests a toolkit for improving the strained dialog between advisors and investors. It’s possible to take our tried and tested (but tired) notions of portfolio construction and energize them with the tools of game theory and behavioral economics, so that we get to the meaning of words like “diversification” and “de-risking”.

In the note I presented one way of thinking about all this in simple graphical terms, by taking the historical risk and reward of a portfolio or a subset of a portfolio and just seeing what the impact of a diversifying strategy would actually have been as seen in risk/reward space.

epsilon-theory-its-still-not-about-the-nail-april-14-2015-historical-risk-reward

The goal here is to move the original portfolio (the gold ball) up and to the left into the green triangle that marries both the traditional meaning of diversification (maximization of reward per unit of risk) and the behavioral meaning of de-risking in a bull market (minimization of the risk of underperformance). There ARE strategies that accomplish this goal, but the trick is finding the strategies that do this for the actual portfolio you have today, not some hypothetical portfolio or index.

We’ve built a set of tools at Salient within our systematic strategies group to analyze the historical impact of a wide range of diversifying strategies from a wide range of asset managers on actual portfolios, and then to map the impact of various diversifying strategies in risk/reward space. It’s not rocket science, and I’m sure any number of Epsilon Theory readers could develop a similar toolkit, but we’ve found it to be a very useful process for not only evaluating, but also communicating how diversifying strategies can make an existing portfolio better for an investor’s needs. Sometimes Salient strategies show up well in this analysis; sometimes they don’t. If you’re familiar with the Progressive Car Insurance commercials with Flo, you get the idea.

If you’re an investment professional and/or financial advisor with a portfolio you’d like to have analyzed in this manner, reply to this email or drop me a note at bhunt@salientpartners.com , and I’d be delighted to set it up for you.

As with all things Epsilon Theory-related, there’s no fee or obligation associated with this analysis. Thanks again to my partners and colleagues here at Salient for their commitment to releasing useful intellectual property into the wild. I think it’s a smart, non-myopic view of what it means to be an asset manager in the modern age, but a rare bird nonetheless.

All the best,
Ben


There’s a massive disconnect between advisors and investors today, and it’s reflected in both declining investment activity as well as a general fatigue with the consultant-client conversation. Consultants continue to preach the faith of diversification, and their clients continue to genuflect in its general direction. But diversification as it’s currently preached is perhaps the most oversold concept in financial advisor-dom, and the sermon isn’t connecting. Fortunately, behavioral economics offers a fresh perspective on portfolio construction, one that lends itself to what we call Adaptive Investing.

Investors aren’t asking for diversification, which isn’t that surprising after six years of a bull market. Investors only ask for diversification after the fire, as a door-closing exercise when the horse has already left the burning barn. What’s surprising is that investors are asking for de-risking, similar in some respects to diversification but different in crucial ways. What’s also surprising is that investors are asking for de-risking rather than re-risking, which is what you’d typically expect at this stage of such a powerful bull market.

Why is this the most mistrusted bull market in recorded history? Because no one thinks it’s real. Everyone believes that it’s a by-product of outrageously extraordinary monetary policy actions rather than the by-product of fundamental economic growth and productivity — and what the Fed giveth, the Fed can taketh away.

This is a big problem for the Federal Reserve, as its efforts to force greater risk-taking in markets through large-scale asset purchases and quantitative easing have failed to take hold in investor hearts and minds. Yes, we’re fully invested, but just because we have to be. To paraphrase the old saying about beauty, risk-taking is only skin deep for today’s investor, but risk-aversion goes clear to the bone.

It’s also the root of our current adviser-investor malaise. How so? Because de-risking a bull market is a very different animal than de-risking a bear market. As seen through the lens of behavioral economics, de-risking is based on regret minimization (not risk–reward maximization like diversification), and the simple fact is that regret minimization is driven by peer comparisons in a bull market. In a bear market your primary regret — the thing you must avoid at all costs — is ruin, and that provokes a very direct physical reaction. You can’t sleep. And that’s why de-risking Rule No. 1 in a bear market is so simple: Sell until you can sleep at night. Go to cash.

In a bull market, your primary regret is looking or feeling stupid, and that provokes a very conflicted, very psychological reaction. You want to de-risk because you don’t understand this market, and you’re scared of what will happen when the policy ground shifts. But you’re equally scared of being tagged “a panicker” and missing “the greatest bull market of this or any other generation.” And so you do nothing. You avoid making a decision, which means you also avoid the consultant-client conversation. Ultimately everyone — advisor and investor alike — looks to blame someone else for their own feelings of unease. No one’s happy, even as the good times roll.

So what’s to be done? Is it possible to both de-risk a portfolio and satisfy the regret minimization calculus of a bull market?

In fact, our old friend diversification is the answer, but not in its traditional presentation as a cure-all bromide. Diversification can certainly de-risk a portfolio by turning down the volatility, and it’s well suited for a bull market because it can reduce volatility without reducing market exposure. The problem is that diversification can take a long time to prove itself, and that’s rarely acceptable to investors who are seeking the immediate portfolio impact of de-risking, whether it’s the bear market or bull market variety.

What we need are diversification strategies that can react quickly. That brings me back to adaptive investing, which has two relevant points for de-risking in a bull market.

First, your portfolio should include allocations to strategies that can go short. If you’re de-risking a bull market, you need to make money when you’re right, not just lose less money. Losing less money pays off over the long haul, but the path can be bumpy.

Second, your portfolio should include allocations to trend-following strategies, which keep you in assets that are working and get you out of those that aren’t. The market is always right, and that’s never been more true — or more difficult to remember — than now in the Golden Age of the Central Banker.

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It’s Not About the Nail

epsilon-theory-its-not-about-the-nail-march-31-2015-yodaDo, or do not. There is no try.”

– Yoda, “Star Wars: Episode V – The Empire Strikes Back” (1980)

I see it all perfectly; there are two possible situations – one can either do this or that. My honest opinion and my friendly advice is this: do it or do not do it – you will regret both.
Soren Kierkegaard, “Either/Or: A Fragment of Life” (1843)

The only victories which leave no regret are those which are gained over ignorance.
Napoleon Bonaparte (1769 – 1821)

Maybe all one can do is hope to end up with the right regrets.
Arthur Miller, “The Ride Down Mt. Morgan” (1991)

Of all the words of mice and men, the saddest are, “It might have been.”
Kurt Vonnegut, “Cat’s Cradle” (1963)

One can’t reason away regret – it’s a bit like falling in love, fall into regret.
Graham Greene, “The Human Factor” (1978)

epsilon-theory-its-not-about-the-nail-march-31-2015-cash.jpgI bet there’s rich folks eatin’

In a fancy dining car.

They’re probably drinkin’ coffee

And smokin’ big cigars.

Well I know I had it comin’.

I know I can’t be free.

But those people keep-a-movin’

And that’s what tortures me.

– Johnny Cash, “Folsom Prison Blues” (1955)

epsilon-theory-its-not-about-the-nail-march-31-2015-paul-ankaRegrets…I’ve had a few.

But then again, too few to mention.

– Paul Anka, Frank Sinatra “My Way” (1969)

The Moving Finger writes; and, having writ,
Moves on: nor all thy Piety nor Wit
Shall lure it back to cancel half a Line,
Nor all thy Tears wash out a Word of it.
Omar Khayyam, “Rubaiyat” (1048 – 1141)

You can tell it any way you want but that’s the way it is. I should of done it and I didn’t. And some part of me has never quit wishin’ I could go back. And I can’t. I didn’t know you could steal your own life. And I didn’t know that it would bring you no more benefit than about anything else you might steal. I think I done the best with it I knew how but it still wasn’t mine. It never has been.”
Cormac McCarthy, “No Country for Old Men” (2005)

Jesse: Yeah, right, well, great. So listen, so here’s the deal. This is what we should do. You should get off the train with me here in Vienna, and come check out the capital.
Celine: What?
Jesse: Come on. It’ll be fun. Come on.
Celine: What would we do?
Jesse: Umm, I don’t know. All I know is I have to catch an Austrian Airlines flight tomorrow morning at 9:30 and I don’t really have enough money for a hotel, so I was just going to walk around, and it would be a lot more fun if you came with me. And if I turn out to be some kind of psycho, you know, you just get on the next train.

Alright, alright. Think of it like this: jump ahead, ten, twenty years, okay, and you’re married. Only your marriage doesn’t have that same energy that it used to have, y’know. You start to blame your husband. You start to think about all those guys you’ve met in your life and what might have happened if you’d picked up with one of them, right? Well, I’m one of those guys. That’s me, y’know, so think of this as time travel, from then, to now, to find out what you’re missing out on. See, what this really could be is a gigantic favor to both you and your future husband to find out that you’re not missing out on anything. I’m just as big a loser as he is, totally unmotivated, totally boring, and, uh, you made the right choice, and you’re really happy.

Celine: Let me get my bag.

Richard Linklater, “Before Sunrise” (1995)

For it falls out
That what we have we prize not to the worth
Whiles we enjoy it, but being lacked and lost,
Why, then we rack the value, then we find
The virtue that possession would not show us
While it was ours.
William Shakespeare, “Much Ado About Nothing” (1612)

When to the sessions of sweet silent thought
I summon up remembrance of things past,
I sigh the lack of many a thing I sought,
And with old woes new wail my dear time’s waste:
William Shakespeare, “Sonnet 30” (1609)

epsilon-theory-its-not-about-the-nail-march-31-2015-nirvanaNo, I don’t have a gun.

– Nirvana, “Come As You Are” (1992)

I spend a lot of my time speaking with investors and financial advisors of all stripes and sizes, and here’s what I’m hearing, loud and clear. There’s a massive disconnect between advisors and investors today, and it’s reflected in both declining investment activity as well as a general fatigue with the advisor-investor conversation. I mean “advisor-investor conversation” in the broadest possible context, a context that should be recognizable to everyone reading this note. It’s the conversation of a financial advisor with an individual investor client. It’s the conversation of a consultant with an institutional investor client. It’s the conversation of a CIO with a Board of Directors. It’s the conversation of many of us with ourselves. The wariness and weariness associated with this conversation runs in both directions, by the way.

Advisors continue to preach the faith of diversification, and investors continue to genuflect in its general direction. But the sermon isn’t connecting. Investors continue to express their nervousness with the market and dissatisfaction with their portfolio performance, and advisors continue to nod their heads and say they understand. It reminds me of Jason Headley’s brilliant short film, “It’s Not About the Nail”, with the advisor reprising Headley’s role. Yes, the advisor is listening. But most find it impossible to get past what they believe is the obvious answer to the obvious problem. Got a headache? Take the nail out of your head. Nervous about the market? Diversify your portfolio. But there are headaches and then there are headaches. There is nervousness and then there is nervousness. It’s not about the nail, and the sooner advisors realize this, the sooner they will find a way to reconnect with their clients. Even if it’s just a conversation with yourself.

epsilon-theory-its-not-about-the-nail-march-31-2015-nail

Investors aren’t asking for diversification, which isn’t that surprising after 6 years of a bull market. Investors never ask for diversification after 6 years of a bull market. They only ask for it after the Fall, as a door-closing exercise when the horse has already left the burning barn. What’s surprising is that investors are asking for de-risking, similar in some respects to diversification but different in crucial ways. What’s surprising is that investors are asking for de-risking rather than re-risking, which is what you’d typically expect at this stage of such a powerful bull market.

Investors are asking for de-risking because this is the most mistrusted bull market in recorded history, a market that seemingly everyone wants to fade rather than press. Why? Because no one thinks this market is real. Everyone believes that it’s a by-product of outrageously extraordinary monetary policy actions rather than the by-product of fundamental economic growth and productivity, and what the Fed giveth … the Fed can taketh away.

This is a big problem for the Fed, as their efforts to force greater risk-taking in markets through LSAP and QE (and thus more productive risk-taking, or at least inflation, in the real economy) have failed to take hold in investor hearts and minds. Yes, we’re fully invested, but only because we have to be. To paraphrase the old saying about beauty, risk-taking is only skin deep for today’s investor, but risk-aversion goes clear to the bone.

It’s also the root of our current advisor-investor malaise. De-risking a bull market is a very different animal than de-risking a bear market. And neither is the same as diversification.

Let’s take that second point first.

Here’s a simple representation of what diversification looks like, from a risk/reward perspective.

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-rewardFor illustrative purposes only.

The gold ball is whatever your portfolio looks like today from a historical risk/reward perspective, and the goal of diversification is to move your portfolio up and to the left of the risk/reward trade-off line that runs diagonally through the current portfolio position. Diversification is all about increasing the risk/reward balance, about getting more reward per unit of risk in your portfolio, and the goodness or poorness of your diversification effort is defined by how far you move your portfolio away from that diagonal line. In fact, as the graph below shows, each of the Good Diversification outcomes are equally good from a risk/reward balance perspective because they are equally distant from the original risk/reward balance line, and vice versa for the Poor Diversification outcomes.

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-reward-2

For illustrative purposes only.

Diversification does NOT mean getting more reward out of your portfolio per se, which means that some Poor Diversification changes to your portfolio will outperform some Good Diversification changes to your portfolio over time (albeit with a much bumpier ride).

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-reward-3

For illustrative purposes only.

It’s an absolute myth to say that any well-diversified portfolio will outperform all poorly diversified portfolios over time. But it’s an absolute truth to say that any well-diversified portfolio will outperform all poorly diversified portfolios over time on a risk-adjusted basis. If an investor is thinking predominantly in terms of risk and reward, then greater diversification is the slam-dunk portfolio recommendation. This is the central insight of Harry Markowitz and his modern portfolio theory contemporaries, and I’m sure I don’t need to belabor that for anyone reading this note.

The problem is that investors are not only risk/reward maximizers, they are also regret minimizers (see Epsilon Theory notes “Why Take a Chance” and “The Koan of Donald Rumsfeld” for more, or read anything by Daniel Kahneman). The meaning of “risk” must be understood as not only as the other side of the reward coin, but also as the co-pilot of behavioral regret. That’s a mixed metaphor, and it’s intentional. The human animal holds two very different meanings for risk in its brain simultaneously. One notion of risk, as part and parcel of expected investment returns and the path those returns are likely to take, is captured well by the concept of volatility and the toolkit of modern economic theory. The other, as part and parcel of the psychological utility associated with both realized and foregone investment returns, is captured well by the concepts of evolutionary biology and the toolkit of modern game theory.

The problem is that diversification can only be understood as an exercise in risk/reward maximization, has next to nothing to say about regret minimization, and thus fails to connect with investors who are consumed by concerns of regret minimization. This fundamental miscommunication is almost always present in any advisor-investor conversation, but it is particularly pernicious during periods of global debt deleveraging as we saw in the 1870’s, the 1930’s, and today. Why? Because the political consequences of that deleveraging create investment uncertainty in the technical, game theoretic sense, an uncertainty which is reflected in reduced investor confidence in the efficacy of fundamental market and macroeconomic factors to drive market outcomes. In other words, the rules of the investment game change when politicians attempt to maintain the status quo – i.e., their power – when caught in the hurricane of a global debt crisis. That’s what happened in the 1870’s. That’s what happened in the 1930’s. And it’s darn sure happening today. We all feel it. We all feel like we’ve entered some Brave New World where the old market moorings make little sense, and that’s what’s driving the acute anxiety expressed today by investors both large and small. Recommending old-school diversification techniques as a cure-all for this psychological pain isn’t necessarily wrong. It probably won’t do any harm. But it’s not doing anyone much good, either. It’s not about the nail.

On the other hand, the concept of de-risking has a lot of meaning within the context of regret minimization, which makes it a good framework for exploring a more psychologically satisfactory set of portfolio allocation recommendations. But to develop that framework, we need to ask what drives investment regret. And just as we talk about different notions of volatility-based portfolio constructions under different market regimes, so do we need to talk about different notions of regret-based portfolio constructions under different market regimes.

Okay, that last paragraph was a bit of a mouthful. Let me skip the academic-ese and get straight to the point. In a bear market, regret minimization is driven by existential concerns. In a bull market, regret minimization is driven by peer comparisons.

In a bear market your primary regret – the thing you must avoid at all costs – is ruin, and that provokes a very direct, very physical reaction. You can’t sleep. And that’s why Rule #1 of de-risking in a bear market is so simple: sell until you can sleep at night. Go to cash. Here’s what de-risking in a bear market looks like, as drawn in risk/reward space.

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-reward-4

For illustrative purposes only.

Again, the gold ball is whatever your portfolio looks like today from a historical risk/reward perspective. De-risking means moving your portfolio to the left, i.e. a lower degree of risk. The question is how much reward you are forced to sacrifice for that move to the left. Perfect De-Risking sacrifices zero performance. Good luck with that if you are reducing your gross exposure. Average De-Risking is typically accomplished by selling down your portfolio in a pro rata fashion across all of your holdings, and that’s a simple, effective strategy. Good De-Risking and Poor De-Risking are the result of active choices in selling down some portion of your portfolio more than another portion of your portfolio, or – if you don’t want to go to cash – replacing something in your portfolio that’s relatively volatile with something that’s relatively less volatile.

In a bull market, on the other hand, your primary regret is looking or feeling stupid, and that provokes a very conflicted, very psychological reaction. You want to de-risk because you don’t understand this market, and you’re scared of what will happen when the policy ground shifts. But you’re equally scared of being tagged with the worst possible insults you can suffer in our business: “you’re a panicker” … “you missed the greatest bull market of this or any other generation”. Again, maybe this is a conversation you’re having with yourself (frankly, that’s the most difficult and conflicted conversation most of us will ever have). And so you do nothing. You avoid making a decision, which means you also avoid the advisor-investor conversation. Ultimately everyone, advisor and investor alike, looks to blame someone else for their own feelings of unease. No one’s happy, even as the good times roll.

So what’s to be done? Is it possible to both de-risk a portfolio and satisfy the regret minimization calculus of a bull market?

Through the lens of regret minimization, here’s what de-risking in a bull market looks like, again as depicted in risk/reward space:

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-reward-5

For illustrative purposes only.

Essentially you’ve taken all of the bear market de-risking arrows and moved them 45 degrees clockwise. What would be Perfect De-Risking in a bear market is only perceived as average in a bull market, and many outcomes that would be considered Good Diversification in pure risk/reward terms are seen as Poor De-Risking. I submit that this latter condition, what I’ve marked with an asterisk in the graph above, is exactly what poisons so many advisor-investor conversations today. It’s a portfolio adjustment that’s up and to the left from the diagonal risk/reward balance line, so you’re getting better risk-adjusted returns and Good Diversification – but it’s utterly disappointing in a bull market as peer comparison regret minimization takes hold. It doesn’t even serve as a Good De-Risking outcome as it would in a bear market.

Now here’s the good news. There are diversification outcomes that overlap with the bull market Good De-Risking outcomes, as shown in the graph below. In fact, it’s ONLY diversification strategies that can get you into the bull market Good De-Risking area. That is, typical de-risking strategies look to cut exposure, not replace it with equivalent but uncorrelated exposure as diversification strategies do, and you’re highly unlikely to improve the reward profile of your portfolio (moving up vertically from the horizontal line going through the gold ball) by reducing gross exposure. The trick to satisfying investors in a bull market is to increase reward AND reduce volatility. I never said this was easy.

epsilon-theory-its-not-about-the-nail-march-31-2015-historical-risk-reward-6

For illustrative purposes only.

The question is … what diversification strategies can move your portfolio into this promised land? Also (as if this weren’t a challenging enough task already), what diversification strategies can work quickly enough to satisfy a de-risking calculus? Diversification can take a long time to prove itself, and that’s rarely acceptable to investors who are seeking the immediate portfolio impact of de-risking, whether it’s the bear market or bull market variety.

What we need are diversification strategies that can act quickly. More to the point, we need strategies that can react quickly, all while maintaining a full head of steam with their gross exposure to non-correlated or negatively-correlated return streams. This is at the heart of what I’ve been calling Adaptive Investing.

Epsilon Theory isn’t the right venue to make specific investment recommendations. But I’ll make three general points.

First, I’d suggest looking at strategies that can go short. If you’re de-risking a bull market, you need to make money when you’re right, not just lose less money. Losing less money pays off over the long haul, but the long haul is problematic from a regret-based perspective, which tends to be quite path-sensitive. Short positions are, by definition, negatively correlated to the thing that they’re short. They have a lot more oomph than the non-correlated or weakly-correlated exposures that are at the heart of most old-school diversification strategies, and that’s really powerful in this framework. Of course, you’ve got to be right about your shorts for this to work, which is why I’m suggesting a look at strategies that CAN go short as an adaptation to changing circumstances, not necessarily strategies that ARE short as a matter of habit or requirement.

Second, and relatedly, I’d suggest looking at trend-following strategies, which keep you in assets that are working and get you out of assets that aren’t (or better yet, allow you to go short the assets that aren’t working). Trend-following strategies are inherently behaviorally-based, which is near and dear to the Epsilon Theory heart, and more importantly they embody the profound agnosticism that I think is absolutely critical to maintain when uncertainty rules the day and fundamental “rules” change on political whim. Trend-following strategies are driven by the maxim that the market is always right, and that’s never been more true – or more difficult to remember – than here in the Golden Age of the Central Banker.

Third, these graphs of portfolio adjustments in risk/reward space are not hypothetical exercises. Take the historical risk/reward of your current portfolio, or some portion of that portfolio such as the real assets allocation, and just see what the impact of including one or more liquid alternative strategies would be over the past few years. Check out what the impact on your portfolio would be since the Fed and the ECB embarked on divergent monetary policy courses late last summer, creating an entirely different macroeconomic regimeSeriously, it’s not a difficult exercise, and I think you’ll be surprised at what, for example, a relatively small trend-following allocation can do to de-risk a portfolio while still preserving the regret-based logic of managing a portfolio in a bull market. For both advisors and investors, this is the time to engage in a conversation about de-risking and diversification, properly understood as creatures of regret minimization as well as risk/reward maximization, rather than to avoid the conversation. As the old saying goes, risk happens fast. Well … so does regret. 

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Catch – 22

epsilon-theory-catch-22-january-12-2015-catch-22

Four times during the first six days they were assembled and briefed and then sent back. Once, they took off and were flying in formation when the control tower summoned them down. The more it rained, the worse they suffered. The worse they suffered, the more they prayed that it would continue raining. All through the night, men looked at the sky and were saddened by the stars. All through the day, they looked at the bomb line on the big, wobbling easel map of Italy that blew over in the wind and was dragged in under the awning of the intelligence tent every time the rain began. The bomb line was a scarlet band of narrow satin ribbon that delineated the forward most position of the Allied ground forces in every sector of the Italian mainland.

For hours they stared relentlessly at the scarlet ribbon on the map and hated it because it would not move up high enough to encompass the city.

When night fell, they congregated in the darkness with flashlights, continuing their macabre vigil at the bomb line in brooding entreaty as though hoping to move the ribbon up by the collective weight of their sullen prayers. “I really can’t believe it,” Clevinger exclaimed to Yossarian in a voice rising and falling in protest and wonder. “It’s a complete reversion to primitive superstition. They’re confusing cause and effect. It makes as much sense as knocking on wood or crossing your fingers. They really believe that we wouldn’t have to fly that mission tomorrow if someone would only tiptoe up to the map in the middle of the night and move the bomb line over Bologna. Can you imagine? You and I must be the only rational ones left.”

In the middle of the night Yossarian knocked on wood, crossed his fingers, and tiptoed out of his tent to move the bomb line up over Bologna.
Joseph Heller, “Catch – 22” (1961)

epsilon-theory-catch-22-january-12-2015-bohrA visitor to Niels Bohr’s country cottage, noticing a horseshoe hanging on the wall, teased the eminent scientist about this ancient superstition. “Can it be true that you, of all people, believe it will bring you luck?”

“Of course not,” replied Bohr, “but I understand it brings you luck whether you believe it or not.” 

― Niels Bohr (1885 – 1962)

Here’s an easy way to figure out if you’re in a cult: If you’re wondering whether you’re in a cult, the answer is yes.
– Stephen Colbert, “I am America (And So Can You!)” (2007)

I won’t insult your intelligence by suggesting that you really believe what you just said.
– William F. Buckley Jr. (1925 – 2008)

A new type of superstition has got hold of people’s minds, the worship of the state.
– Ludwig von Mises (1881 – 1973)

The cult is not merely a system of signs by which the faith is outwardly expressed; it is the sum total of means by which that faith is created and recreated periodically. Whether the cult consists of physical operations or mental ones, it is always the cult that is efficacious.
– Emile Durkheim, “The Elementary Forms of Religious Life” (1912)

At its best our age is an age of searchers and discoverers, and at its worst, an age that has domesticated despair and learned to live with it happily.
– Flannery O’Connor (1925 – 1964)

Man is certainly stark mad; he cannot make a worm, and yet he will be making gods by dozens.
– Michel de Montaigne (1533 – 1592)

Since man cannot live without miracles, he will provide himself with miracles of his own making. He will believe in witchcraft and sorcery, even though he may otherwise be a heretic, an atheist, and a rebel.
– Fyodor Dostoyevsky, “The Brothers Karamazov” (1880)

One Ring to rule them all; one Ring to find them.
One Ring to bring them all and in the darkness bind them.
– J.R.R. Tolkien, “The Lord of the Rings” (1954)

Nothing’s changed.
I still love you, oh, I still love you.
Only slightly, only slightly less
Than I used to.
– The Smiths, “Stop Me If You’ve Heard This One Before” (1987)

So much of education, I think, relies on reading the right book at the right time. My first attempt at Catch-22 was in high school, and I was way too young to get much out of it. But fortunately I picked it up again in my late 20’s, after a few experiences with The World As It is, and it’s stuck with me ever since. The power of the novel is first in the recognition of how often we are stymied by Catch-22’s – problems that can’t be solved because the answer violates a condition of the problem. The Army will grant your release request if you’re insane, but to ask for your release proves that you’re not insane. If X and Y, then Z. But X implies not-Y. That’s a Catch-22.

Here’s the Fed’s Catch-22. If the Fed can use extraordinary monetary policy measures to force market risk-taking (the avowed intention of both Zero Interest Rate Policy and Large Scale Asset Purchases) AND the real economy engages in productive risk-taking (small business loan demand, wage increases, business investment for growth, etc.), THEN we have a self-sustaining and robust economic recovery underway. But the Fed’s extraordinary efforts to force market risk-taking and inflate financial assets discourage productive risk-taking in the real economy, both because the Fed’s easy money is used by corporations for non-productive uses (stock buy-backs, anyone?) and because no one is willing to invest ahead of global growth when no one believes that the leading indicator of that growth – the stock market – means what it used to mean. 

If X and Y, then Z. But X denies Y. Catch-22.

There’s a Catch-22 for pretty much everyone in the Golden Age of the Central Banker. Are you a Keynesian? Your Y to go along with the Central Bank X is expansionary fiscal policy and deficit spending. Good luck getting that through your polarized Congress or Parliament or whatever if your Central Bank is carrying the anti-deflation water and providing enough accommodation to keep your economy from tanking. Are you a structural reformer? Your Y to go along with the Central Bank X is elimination of bureaucratic red tape and a shrinking of the public sector. Again, good luck with that as extraordinary monetary policy prevents the economic trauma that might give you a chance of passing those reforms through your legislative process.

Here’s the thing. A Catch-22 world is a frustrating, absurd world, a world where we domesticate despair and learn to live with it happily. It’s also a very stable world. And that’s the real message of Heller’s book, as Yossarian gradually recognizes what Catch-22 really IS. There is no Catch-22. It doesn’t exist, at least not in the sense of the bureaucratic regulation that it purports to be. But because everyone believes that it exists, then an entire world of self-regulated pseudo-religious behavior exists around Catch-22. Sound familiar?

We’ve entered a new phase in the Golden Age of the Central Banker – the cult phase, to use the anthropological lingo. We pray for extraordinary monetary policy accommodation as a sign of our Central Bankers’ love, not because we think the policy will do much of anything to solve our real-world economic problems, but because their favor gives us confidence to stay in the market. I mean … does anyone really think that the problem with the Italian economy is that interest rates aren’t low enough? Gosh, if only ECB intervention could get the Italian 10-yr bond down to 1.75% from the current 1.85%, why then we’d be off to the races! Really? But God forbid that Mario Draghi doesn’t (finally) put his money where his mouth is and announce a trillion euro sovereign debt purchase plan. That would be a disaster, says Mr. Market. Why? Not because the absence of a debt purchase plan would be terrible for the real economy. That’s not a big deal one way or another. It would be a disaster because it would mean that the Central Bank gods are no longer responding to our prayers. The faith-based system that underpins current financial asset price levels would take a body blow. And that would indeed be a disaster.

Monetary policy has become a pure signifier – a totem. It’s useful only in so far as it indicates that the entire edifice of Central Bank faith, both its mental and physical constructs, remains “efficacious”, to use Emile Durkheim’s path-breaking sociological analysis of a cult. All of us are Yossarian today, far too rational to think that the totem of a red line on a map actually makes a difference in whether we have to fly a dangerous mission. And yet here we are sneaking out at night to move that line on the map. All of us are Niels Bohr today, way too smart to believe that the totem of a horseshoe actually bring us good luck. And yet here we are keeping that horseshoe up on our wall, because … well … you know.

The notion of saying our little market prayers and bowing to our little market talismans is nothing new. “Hey, is that a reverse pennant pattern I see in this stock chart?” “You know, the third year of a Presidential Administration is really good for stocks.” “I thought the CFO’s body language at the investor conference was very encouraging.” “Well, with the stock trading at less than 10 times cash flow I’m getting paid to wait.” Please. I recognize aspects of myself in all four of these cult statements, and if you’re being honest with yourself I bet you do, too. No, what’s new today is that all of our little faiths have now converged on the Narrative of Central Bank Omnipotence. It’s the One Ring that binds us all. 

epsilon-theory-catch-22-january-12-2015-eye

I loved this headline article in last Wednesday’s Wall Street Journal – “Eurozone Consumer Prices Fall for First Time in Five Years” – a typically breathless piece trumpeting the “specter of deflation” racing across Europe as … oh-my-god … December consumer prices were 0.2% lower than they were last December. Buried at the end of paragraph six, though, was this jewel: “Excluding food, energy, and other volatile items, core inflation rose to 0.8%, up a notch from November.” Say what? You mean that if you measure inflation as the US measures inflation, then European consumer prices aren’t going down at all, but are increasing at an accelerating pace? You mean that the dreadful “specter of deflation” that is “cementing” expectations of massive ECB action is entirely caused by the decline in oil prices, something that from the consumer’s perspective acts like an inflationary tax cut? Ummm … yep. That’s exactly what I mean. The entire article is an exercise in Narrative creation, facts be damned. The entire article is a wail from a minaret, a paean to the ECB gods, a calling of the faithful to prayer. An entirely successful calling, I might add, as both European and US markets turned after the article appeared, followed by Thursday’s huge move up in both markets.

When I say that a Catch-22 world is a stable world, or that the cult phase of a human society is a stable phase, here’s what I mean: change can happen, but it will not happen from within. For everyone out there waiting for some Minsky Moment, where a debt bubble of some sort ultimately pops from some unexpected internal cause like a massive corporate default, leading to systemic fear and pain in capital markets … I think you’re going to be waiting for a loooong time. Are there debt bubbles to be popped? Absolutely. The energy sector, particularly its high yield debt, is Exhibit #1, and I think this could be a monster trade. But is this something that can take down the market? I don’t see it. There is such an unwavering faith in Central Bank control over market outcomes, such a universal assumption of god-like omnipotence within this realm, that any internal market shock is going to be willed away.

So is that it? Is this a brave new world of BTFD market stability? Should we double down on our whack-a-mole volatility strategies? For internal market risks like leverage and debt bubble scares … yes, I think so. But while the internal market risk factors that I monitor are quite benign, mostly green lights with a little yellow/caution peeking through, the external market risk factors that I monitor are all screaming red. These are Epsilon Theory risk factors – political shocks, trade/forex shocks, supply shocks, etc. – and they’ve got my risk antennae quivering like crazy. I’ve been doing this for a long time, and I can’t remember a time when there was such a gulf between the environmental or exogenous risks to the market and the internal or behavioral dynamics of the market. The market today is Wile E. Coyote wearing his latest purchase from the Acme Company – a miraculous bat-wing costume that prevents the usual plunge into the canyon below by sheer dint of will. There’s absolutely nothing internal to Coyote or his bat suit that prevents him from flying around happily forever. It’s only that rock wall that’s about to come into the frame that will change Coyote’s world.

epsilon-theory-catch-22-january-12-2015-coyote

My last three big Epsilon Theory notes – “The Unbearable Over-Determination of Oil”, “Now There’s Something You Don’t See Every Day, Chauncey”, and “The Clash of Civilizations” – have delved into what I think are the most pressing of these environmental or exogenous risks to the market: the “supply shock” of collapsing oil prices, a realigning Greek election, and the realpolitik dynamics of the West vs. Islam and the West vs. Russia. I gotta say, it’s been weird to write about these topics a few weeks before ALL of them come to pass. Call me Cassandra. I stand by everything I wrote in those notes, so no need to repeat all that here, but a short update paragraph on each.

First, Greece. And I’ll keep it very short. Greece is on. This will not be pretty and this will not be easy. Existential Euro doubt will raise its ugly head once again, particularly when Italy imports the Greek political experience.

Second, oil. I get a lot of questions about why oil can’t catch a break, about why it’s stuck down here with a 40 handle as the absurd media Narrative of “global supply glut forever and ever, amen” whacks it on the head day after day after day. And it is an absurd Narrative … very Heller-esque, in fact … about as realistic as “Peak Oil” has been over the past decade or two. Here’s the answer:  oil is trapped in a positive Narrative feedback loop. Not positive in the sense of it being “good”, whatever that means, but positive in the sense of the dominant oil Narrative amplifying the uber-dominant Central Bank Narrative, and vice versa. The most common prayer to the Central Banking gods is to save us from deflation, and if oil prices were not falling there would be no deflation anywhere in the world, making the prayer moot. God forbid that oil prices go up and, among other things, push European consumer prices higher. Can’t have that! Otherwise we’d need to find another prayer for the ECB to answer. By finding a role in service to the One Ring of Central Bank Omnipotence, the dominant supply-glut oil Narrative has a new lease on life, and until the One Ring is destroyed I don’t see what makes the oil Narrative shift.

Third, the Islamist attack in Paris. Look … I’ve got a LOT to say about “je suis Charlie”, both the stupefying hypocrisy of how that slogan is being used by a lot of people who should really know better, as well as the central truth of what that slogan says about the Us vs. Them nature of The World As It Is, but both are topics for another day. What I’ll mention here are the direct political repercussions in France. The National Front, which promotes a policy platform that would make Benito Mussolini beam with pride, would probably have gotten the most votes of any political party in France before the attack. Today I think they’re a shoo-in to have first crack at forming a government whenever new Parliamentary elections are held, and if you don’t recognize that this is100 times more threatening to the entire European project than the prospects of Syriza forming a government in Greece … well, I just don’t know what to say.

There’s another thing to keep in mind here in 2015, another reason why selling volatility whenever it spikes up and buying the dip are now, to my way of thinking, picking up pennies in front of a steam roller: the gods always end up disappointing us mere mortals. The cult phase is a stable system on its own terms (a social equilibrium, in the parlance), but it’s rarely what an outsider would consider to be a particularly happy or vibrant system. There’s no way that Draghi can possibly announce a bond-buying program that lives up to the hype, not with peripheral sovereign debt trading inside US debt. There’s no way that the Fed can reverse course and start loosening again, not if forward guidance is to have any meaning (and even the gods have rules they must obey). Yes, I expect our prayers will still be answered, but each time I expect we will ask in louder and louder voices, “Is that all there is?” Yes, we will still love our gods, even as they disappoint us, but we will love them a little less each time they do.

And that’s when the rock wall enters the cartoon frame.

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