There are two sides to the Epsilon Theory coin — looking at market-shaping current events through the lens of game theory and history, and looking at market behaviors through the lens of information theory. The former is all about the malleability of meaning within markets; the latter is all about the constancy of patterns within markets. A stand-alone example of each is provided here.
The central banks of the West announced today that their temporary swap lines would be made permanent. Like QE itself, the meaning of this emergency policy instrument instituted in the crisis of 2008-2009 has changed from a massive short-term intervention against an acute and life-threatening economic injury to a massive permanent insurance policy against a chronic and annoying economic condition.
There are known knowns; there are things we know we know.We also know there are known unknowns; that is to say, we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.
– Donald Rumsfeld
There is an unmistakable Zen-like quality to this, my favorite of Donald Rumsfeld’s often cryptic statements. I like it so much because what Rumsfeld is describing perfectly in his inimitable fashion are the three forms of game theoretic decisions:
Decision-making under certainty – the known knowns. This is the sure thing, like betting on the sun coming up tomorrow, and it is a trivial sub-set of decision-making under risk where probabilities collapse to zero or 1.
Decision-making under risk – the known unknowns, where we are reasonably confident that we know the potential future states of the world and the rough probability distributions associated with those outcomes. This is the logical foundation of Expected Utility, the formal language of microeconomic behavior, and mainstream economic theory is predicated on the prevalence of decision-making under risk in our everyday lives.
Decision-making under uncertainty – the unknown unknowns, where we have little sense of either the potential future states of the world or, obviously, the probability distributions associated with those unknown outcomes. This is the decision-making environment faced by a Stranger in a Strange Land, where traditional cause-and-effect is topsy-turvy and personal or institutional experience counts for little, where good news is really bad news and vice versa. Sound familiar?
The sources of today’s market uncertainty are the same as they have always been throughout history – pervasive credit deleveraging and associated political strife. In the Middle Ages, these periods of deleveraging and strife were typically the result of political pursuit of wars of conquest … Edward III and his 14th century exploits in The Hundred Years War, say, or Edward IV and his 15th century exploits in The War of the Roses. Today, our period of deleveraging and strife is the result of political pursuit of la dolce vita … a less bloody set of exploits, to be sure, but no less expensive or impactful on markets. PIMCO co-CIO, Mohamed El-Erian, has a great quote to summarize this state of affairs – “Investors are in the back seat, politicians in the front seat, and it is very foggy through the windscreen.” – and the events of the past two weeks in Washington serve to confirm this observation … yet again. Of course, central banks are political institutions and central bankers are political animals, and the largest monetary policy experiment ever devised by humans should be understood in this political context. The simple truth is that no one knows how the QE story ends or what twists and turns await us. The crystal ball is broken and it’s likely to stay broken for years and years.
We are enduring a world of massive uncertainty, which is not at all the same thing as a world of massive risk. We tend to use the terms “risk” and “uncertainty” interchangeably, and that may be okay for colloquial conversation. But it’s not okay for smart decision-making, whether the field is foreign policy or investment, because the process of rational decision-making under conditions of risk is very different from the process of rational decision-making under conditions of uncertainty. The concept of optimization is meaningful and precise in a world of risk; much less so in a world of uncertainty.That’s because optimization is, by definition, an effort to maximize utility given a set of potential outcomes with known (or at least estimable) probability distributions. Optimization works whether you have a narrow range of probabilities or a wide range. But if you have no idea of the shape of underlying probabilities, it doesn’t work at all. As a result, applying portfolio management, risk management, or asset allocation techniques developed as exercises in optimization – and that includes virtually every piece of analytical software on the market today – may be sub-optimal or downright dangerous in an uncertain market. That danger also includes virtually every quantitatively trained human analyst!
All of these tools and techniques and people will still generate a risk-based “answer” even in the most uncertain of times because they are constructed and trained on the assumption that probability estimations and long-standing historical correlations have a lot of meaning regardless of circumstances. It’s not their fault, and their math isn’t wrong. They just haven’t been programmed to step back and evaluate whether their finely honed abilities are the right tool for the environment we’re in today.
My point is not to crawl under a rock and abandon any attempt to optimize a portfolio or an allocation…for most professional investors or allocators this is professional suicide. My point is that investment decisions designed to optimize – regardless of whether the target of that optimization is an exposure, a portfolio, or an allocation – should incorporate a more agnostic and adaptive perspective in an uncertain market. We should be far less confident in our subjective assignment of probabilities to future states of the world, with far broader margins of error in those subjective evaluations than we would use in more “normal” times. Fortunately, there are decision-making strategies designed explicitly to incorporate this sort of perspective, to treat probabilities in an entirely different manner than that embedded in mainstream economic theory. One in particular – Minimax Regret – eliminates the need to assign any probability distribution whatsoever to potential outcomes.
Minimax Regret, developed in 1951 by Leonard “Jimmie” Savage, is a cornerstone of what we now refer to as behavioral economics. Savage played a critical role, albeit behind the scenes, in the work of three immortals of modern social science. He was John von Neumann’s right-hand man during World War II, a close colleague of Milton Friedman’s (the second half of the Friedman-Savage utility function), and the person who introduced Paul Samuelson to the concept of random walks and stochastic processes in finance (via Louis Bachelier) … not too shabby! Savage died in 1971 at the age of 53, so he’s not nearly as well-known as he should be, but his Foundations of Statistics remains a seminal work for anyone interested in decision-making in general and Bayesian inference in particular.
As the name suggests, the Minimax Regret strategy seeks to minimize your maximum regret in any decision process. This is not at all the same thing as minimizing your maximum loss. The concept of regret is a much more powerful and flexible concept than mere loss, because it injects an element of subjectivity into a decision calculus. Is regret harder to program into a computer algorithm than simple loss? Sure. But that’s exactly what makes it much more human, and that’s why I think you may find the methodology more useful.
Minimax Regret downplays (or eliminates) the role that probability distributions play in the decision-making process. While any sort of Expected Utility or optimization approach seeks to evaluate outcomes in the context of the odds associated with those outcomes coming to pass, Minimax Regret says forget the odds … how would you feel if you pay the cost of Decision A and Outcome X occurs? What about Decision A and Outcome Y? Outcome Z? What about Decision B and Outcome X, Y, or Z? Make that subjective calculation for every potential combination of decision + outcome you can imagine, and identify the worst possible outcome “branch” associated with each decision “tree”. Whichever decision tree holds the best of these worst possible outcome branches is the rational decision choice from a Minimax Regret perspective.
This is different from maximum loss calculation in many respects. For example, if the maximum loss outcome is rather apocalyptic, where it is extremely costly to prepare and you’re still pretty miserable even if you did prepare, most people will not experience this as a maximum regret outcome even if they make no preparations whatsoever to mitigate its impact. On the other hand, many people will experience substantial regret, perhaps even maximum regret, if the outcome is a large gain in which they do not share because they failed to prepare for it. Minimax Regret is a subjective decision-making strategy that captures the disutility of both missed opportunities as well as suffered losses, which makes it particularly appropriate for investment decisions that must inevitably incorporate the subjective feelings of greed and fear.
Minimax Regret requires a decision-maker to know nothing about the likelihood of this future state of the world or that future state. Because of its subjective foundations, however, it requires its practitioners to know a great deal about his or her utility for this future state of the world or that future state. The motto of Minimax Regret is not Know the World…it’s Know Thyself.
It’s also an appropriate decision-making strategy where you DO know the odds associated with the potential decision-outcomes, but where you have so few opportunities to make decisions that the stochastic processes of the underlying probability distributions don’t come into play. To use a poker analogy, my decision-making process should probably be different if I’m only going to be dealt one hand or if I’m playing all night. The former is effectively an environment of uncertainty and the latter an environment of risk, even though the risk attributes are clearly defined in both. This is an overwhelming issue in decision-making around, say, climate change policy, where we are only dealt a single hand (unless that Mars terraforming project picks up speed) and where both decisions and outcomes take decades to reveal themselves. It’s less of an issue in most investment contexts, but can certainly rear its ugly head in illiquid securities or strategies.
Is this a risk-averse strategy? In theory, no, but in practice, yes, because the most regret-filled outcomes tend to be those that are more likely to be low probability outcomes. If the “real” probability distributions of future outcomes were magically revealed to us … if we could just get our crystal ball working again … then an Expected Utility analysis of pretty much any Minimax Regret decision-making process would judge it as risk-averse. But that’s just the point … our crystal ball isn’t working, and it won’t so long as we have profound political fragmentation within and between the major economic powers of the world.
I’m not saying that Minimax Regret is the end-all and be-all. The truth is that the world is never entirely uncertain or without historical correlations that provide useful indications of what may be coming down the pike, and there are plenty of other ways to be more agnostic and adaptive in our investment decision-making without abandoning probability estimation entirely. But there’s no doubt that our world is more uncertain than it was five years ago, and there’s no doubt that there’s an embedded assumption of probabilistic specification in both the tools and the people that dominate modern risk management and asset allocation theory. Minimax Regret is a good example of an alternative decision-making approach that takes this uncertainty and lack of probabilistic specification seriously without sacrificing methodological rigor. As a stand-alone decision algorithm it’s a healthy corrective or decision-making supplement, and I believe it’s possible to incorporate its subjective Bayesian tenets directly into more mainstream techniques. Stay tuned…
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Mr. Incredible: You mean you killed off real heroes so that you could *pretend* to be one?
Syndrome: Oh, I’m real. Real enough to defeat you! And I did it without your precious gifts, your oh-so-special powers. I’ll give them heroics. I’ll give them the most spectacular heroics the world has ever seen! And when I’m old and I’ve had my fun, I’ll sell my inventions so that *everyone* can have powers. *Everyone* can be super! And when everyone’s super … [chuckles evilly] … no one will be.
Captain, although your abilities intrigue me, you are quite honestly inferior. Mentally, physically.
– Khan Noonien Singh, “Star Trek: Space Seed” (1967)
The whole country has been involved in this, I think, since after the All-Star break. If people say it’s bringing the country together, I’m happy to bring the country together.
– Mark McGwire (1998)
I’m not here to talk about the past.
– Mark McGwire (2005)
“In some respects, insider trading is a form of financial steroid. It is unfair; it is offensive; it is unlawful; and it puts a black mark on the entire enterprise.”
– Preet Bharara, U.S. Attorney for the Southern District of New York
When I played pro football, I never set out to hurt anyone deliberately – unless it was, you know, important, like a league game or something.
– Dick Butkus, Chicago Bears (1965 – 1973)
Fortunately for a quarterback, you can play for a long time because you don’t get hit very often.
– Tom Brady, New England Patriots (2000 – ???)
Earlier this month, Massachusetts State Secretary William Galvin imposed a $30 million fine on Citigroup because an equity analyst shared his research on an Apple iPhone supplier with analysts at a couple of investment funds before he published the research publicly. To be clear, this was not a case of the analyst telling the hedge funds his true views and writing fraudulent pieces for public consumption, à la Merrill Lynch analyst Henry Blodgett and many others, which resulted in the 2003 Global Research Analyst Settlement between the SEC and most Wall Street sell-side firms, as well as the launching of Eliot Spitzer’s political career. Nor was this a case of the analyst leaking inside information from the company he covered to the hedge funds, à la some of the protagonists in the Galleon Group prosecutions that began in 2009. This was the analyst’s own work and research, perfectly aligned with what he would publish publicly. But because Citigroup is a party to the 2003 Global Research Analyst Settlement, whereby “CIR [Citigroup Research] equity research analysts cannot preview in writing unpublished, or disavow in writing published research views to personnel outside of CIR”, the analyst was a dead man walking as soon as he emailed his “New Forecast” numbers to external analysts.
This is the same issue that tripped up prominent equity analyst Mark Mahaney (also of Citigroup) in October last year, when he emailed a reporter in a way that indicated his unpublished projections of YouTube’s revenue growth and profitability. Again, no disconnect between public and private communications and no revelation of inside information, but a clear violation of both the 2003 consent decree and bank policy, for which Mahaney was summarily fired. As he should have been. It’s not like Mahaney was unaware of the prohibition against this sort of communication (as he wrote in an email later cited by the bank, “This could get me in trouble. Shoot.”), and it’s pretty clear that the analyst in this week’s case was similarly aware of the rules, seeing as he rushed the published report out the door immediately after emailing the hedge funds.
My point is not that these guys were treated unfairly or that sell-side equity research rules should be changed back to their pre-2003 form. These are the rules of the game today, everyone knows that these are the rules, and if you don’t want to play within these rules you should find another game.
Let me put it this way … Do you enjoy seeing a defensive back level a wide receiver with a big hit? Are you annoyed by your team’s defensive lineman being flagged for roughing the passer if he lays a fingernail on pretty boy Tom Brady? Me, too.
But the game of football as played by Dick Butkus is gone. It’s not coming back. Get over it. Certainly the NFL players and coaches have gotten over it, because they have to deal with the game as it is – not as it was or how they wish it were – in order to succeed. Ditto for baseball. Is it completely arbitrary to make a distinction between “illegal” performance-enhancing regimens like a course of anabolic steroids and “legal” performance-enhancing regimens like Lasix surgery or tendon replacement? Of course it is. But there’s nothing “natural” about any choices a rule-making organization might impose. Any game is defined by the rules in force, explicitly and tacitly, at a given point in time. If you want to play in that game, you play by that set of unnatural rules and not some other set of unnatural rules. Period. Nostalgia is a luxury for observers, not participants, whether you’re talking about the game of sports or the game of thrones or the game of markets.
My point (other than to say “For the love of God, don’t use email when the law specifically enjoins only written communications”) is that the rules governing the flow of private information within capital markets – and the way those rules are enforced – create structural changes in markets. Those structural changes, in turn, shape not only investor behavior but also investment returns. Alpha generation in public equity markets has been crippled by the current regulatory regime, which is engaged in an intentional effort to criminalize private information regarding public companies. This is an institutionalized effort to “level the playing field”, as every U.S. Attorney and Senator and President and Attorney General and Governor likes to say. This is not a Democratic or Republican effort. It is an entirely natural and rational effort by any politician in the aftermath of a nationwide economic crisis. It is an effort that will not go away and will in all likelihood get more pronounced. The rules of the game are changing, and if you don’t change the way you play the game to match these new rules, you will be bounced out of the game as fast as Butkus would be if he played football today.
I’m not concerned with the public theatre of all this. There are show trials in the aftermath of every lost war, and the aggregate cost of the Great Recession to the US economy was the rough equivalent of losing a decent-sized war. No one is going to shed a tear over Raj Rajaratnam or Stevie Cohen or their ilk, so let the perp walks and the ritual executions begin. Certainly it’s a little comical at times. How many shots did the photographer have to take of US Attorney Preet Bharara before his media handlers decided that he evinced just the right degree of steely determination as he gazes out the window with the DOJ seal in the background?
On the other hand, here’s a photograph of the seven monitors that Stevie Cohen keeps on his desk at SAC.
In their response to the SEC “failure to supervise” charge against SAC, Cohen’s lawyers actually make the argument that having so many monitors proves that Cohen could not possibly have been paying attention to the incriminating emails sent to him, that in fact this is prima facie evidence that Cohen is a trader extraordinaire, a wizard who made his billions by keeping his finger on the beating pulse of the market. Maybe the only thing funnier than the lawyers’ argument was the way in which the news was picked up by The Wall Street Job Report, with an article titled “Steve Cohen has seven monitors at his desk. Should you, too?” Conclusion: seven is probably “excessive”, although “multiple studies suggest that having a second or third screen makes workers more productive.” I mean, you just can’t make this stuff up.
But the real issue here is not the show trials. The real issue is the regulatory evisceration of the day-to-day process by which investment managers and analysts acquire information about public companies.
Galvin is not stopping with the $30 million fine of Citigroup. He is “looking at whether there are other enforcement actions possible” against SAC, Citadel, GLG, and T. Rowe Price for asking the questionabout the Citigroup analyst’s views on the iPhone supply chain. In particular, Galvin called SAC’s efforts “extremely aggressive” and is considering whether to hand over his evidence to federal prosecutors and the SEC. Well, this certainly sounds interesting, so I went through the Massachusetts complaint to see just what sort of hardball tactics SAC employed. Here you go:
44. On the morning of Dec. 13, 2012, an employee of SAC Capital, a CGMI client holding Apple stock, began emailing Kevin Chang, asking “Hey Kevin, are you picking up any order cuts to iPhone?”
45. Also on the morning of Dec. 13, 2012, an employee of SAC Capital’s CR Intrinsic division emailed Kevin Chang, asking “Hi Kevin, Macquarie just downgraded Hon Hai and cited very weak demand for the iPhone (down 35-40%) into the March qtr. Have you picked up any checks that would suggest this is the case? I think when we exchanged emails a bit earlier you were still pretty bullish about March estimates? Thanks!”
46. Also on the morning of Dec.13, 2012, an employee of SAC Capital’s LP division emailed Kevin Chang, asking “Hello Kevin, do you have some time to speak? Not sure if you are in Taiwan?”
47. Also on the morning of Dec. 13, 2012, an employee of SAC Capital’s Sigma Capital division emailed Kevin Chang, asking “A competitor had a negi note on HH today. I was wondering if you had a few minutes tonight (ET), am for you, to catch up on your general thoughts.”
48. On Dec. 13, 2012, prior to the publication of Kevin Chang’s Dec. 14 Hon Hai Report, another employee of the hedge fund emailed Kevin Chang, copying a Citi Equities employee, with the subject of the email as “[Employee Name] at SAC request for conference call today URGENT.”
49. In this email chain, the SAC employee asked, “Kevin are you available?” The Citi Equities employee replied to this chain, asking, “Kevin, have been told this morning that you are in Japan. Is there a possibility of calling [the hedge fund employee] on his mobile number at [U.S. phone number] or in his office at [U.S. phone number]. Any help is greatly appreciated.” Lastly the employee of the hedge fund replied to both Kevin Chang and the Citi Equities employee, stating, “Thanks very much – mobile is best at [U.S. phone number].”
That’s it. Pretty ferocious, huh? Only two of the five emails said thank you, which struck me as terribly impolite and just the sort of aggressive, take-no-prisoners behavior that SAC is so well-known for. And I think we’re all aware that when a SAC analyst says “I was wondering if you had a few minutes to catch up on your general thoughts?” that’s code for “we are holding your wife and kids hostage.”
Are there rules for what sell-side analysts can say and when they can say it? Yes, if your firm is in the business of selling or marketing securities and particularly if your firm is governed by the 2003 general consent decree. What Galvin is suggesting is that there should also be rules for what the buy-side can ask and when they can ask it, or at least that there should be a burden placed on the buy-side to confirm that they are not receiving or acting on information “illegally” provided by a sell-side analyst. That legal burden already exists if an investor receives material and non-public information about a publicly-traded company from anyone, including sell-side analysts. This is the current definition of insider trading. What’s germinating here is an expansion of the definition of insider trading to include material and non-public opinions developed by an employee of a regulated broker dealer. That may sound like a minor thing, but I can promise you that it’s not.
If we are entering a regulatory environment where the questions posed by these SAC analysts will be characterized as criminal behavior, then any active investment strategy based on the fundamental analysis of companies is finished. Dead. This is the mother of all chilling effects. Asking these questions is what fundamental analysts DO … all day, every day. They call and email and visit sell-side analysts a lot, management (usually someone in investor relations) occasionally, and each other rarely. This is how a buy-side analyst “knows his companies”. This is how a stock-picking investment strategy develops an “edge”. If coming into possession of a sell-side analyst’s opinion might land you in jail … if every investor must not only ask “is this opinion right?”, but also “is it legal for me to have this opinion?” … well, these conversations will stop happening. We will all read the same research reports at the same time, get on the same conference calls, attend the same publicly broadcast meetings. We will receive these opinions legally, which is to say publicly, and everyone will know exactly the same things at exactly the same time about public companies directly, as well as what everyone on the sell-side thinks about those public companies. No investor will “know his companies” any better than the next guy, which means there will be no edge to any stock-picking investment strategy. Which means that there is no alpha in these strategies. Sorry, but that’s a cold, hard fact.
Here’s the thing. This is exactly what politicians want from their regulatory efforts. They want a world of pure beta and zero alpha. This is the ultimate “level playing field”, where no one knows anything that everyone else doesn’t also know. The presumption within regulatory bodies today is that you must be cheating if you are generating alpha. How’s that? Alpha generation requires private information. Private information, however acquired, is defined as insider information. Insider information is cheating. Thus, alpha generation is cheating. QED.
Why would politicians want an alpha-free market? Because a “fair” market with a “level playing field” is an enormously popular Narrative for every US Attorney who wants to be Attorney General, every Attorney General who wants to be Governor, and every Governor who wants to be President…which is to say all US Attorneys and all Attorneys General and all Governors. Because criminalizing private information in public markets ensures a steady stream of rich criminals for show trials in the future. Because the political stability of the American regime depends on a widely dispersed, non-zero-sum price appreciation of all financial assets – beta – not the concentrated, zero-sum price appreciation of idiosyncratic securities. Because public confidence in the government’s control of public institutions like the market must be restored at all costs, even if that confidence is misplaced and even if the side-effects of that restoration are immense. Here’s a telling quote:
Insider trading tells everybody at precisely the wrong time that everything is rigged, and only people who have a billion dollars and have access to and are best friends with people who are on boards of directors of major companies – they’re the only ones who can make a true buck.
– Preet Bharara, U.S. Attorney, Southern District of New York
What does that mean, that it’s “precisely the wrong time” for insider trading to exist? Why isn’t insider trading an equally bad thing anytime? It’s precisely the wrong time because the financial collapse of 2008 and the subsequent federal bail-out of everyone from AIG to GM to GE to Goldman Sachs revealed that the system IS rigged. Now I think that anyone with half a brain should thank God that the system is rigged, because the alternative was a good old-fashioned Götterdämmerung, but it’s pretty hard to deny that the events of 2008 – 2009 revealed the raw sinews of power that exist beneath our pleasing Narrative of democratic rule and a “level playing field”. Now the Narrative must be restored. We’ve seen the iron fist … time to put the velvet glove back on. There is no more important task for the American regime.
Fortunately for Bharara and unfortunately for active equity managers, there are tools available to regulators and prosecutors today that were not available in, say, the 1930’s to enforce an alpha-free market. These are the tools of Big Data and electronic surveillance, and as we have seen with recent revelations around the NSA and its collection and analysis of all US telecommunications, it is a powerful toolkit, indeed. On the Big Data side, in 2009 the SEC established an Office of Quantitative Research and an Office of Risk Assessment and Interactive Data within its Economic and Risk Analysis Division, and – for operational surveillance – an Office of Analytics and Research within its Trading and Markets Division. Just this July, the SEC announced a new Center for Risk and Quantitative Analysis, which will directly “provide guidance to the Enforcement Division’s leadership.” This is the SEC’s equivalent of the CIA. These Offices are extremely well funded, draw some really top-notch people from the private sector, and coordinate closely with the FBI. Today’s SEC may not quite be the functional equivalent of the NSA from a data gathering and pattern inference perspective, but it’s nothing to sneeze at, either. The NSA is a little bigger and faster, that’s all. On the traditional surveillance side, Bharara and his colleagues in the DOJ have been given amazing latitude by the courts to pursue widespread wire taps across a wide swath of the financial services industry.
The importance of these surveillance and data analysis capabilities cannot be overemphasized, as they transformed sleepy regulatory edicts that were on the books but extremely hard to prosecute – such as the 2003 Global Research Analyst Settlement or, more importantly, Reg FD, originally adopted way back in August, 2000 – into powerful weapons. Take, for example, Reg FD, which requires publicly traded companies to eliminate selective disclosure of any information that could be deemed to be material and non-public. Not only does Reg FD place a burden on company management not to disclose material and non-public information to anyone unless it is disclosed to everyone, but as described above it also places a burden on the receiving party (typically the investor) not to act on the improperly disclosed information. Prior to 2009 it was very difficult for the SEC or FBI to identify any but the most egregious infractions of Reg FD, such as an email leaked by a disgruntled employee or a massive dumping or purchase of a stock. Since 2009, however, the SEC can sift through all of the trading in a company’s stock, look for what they consider to be suspicious patterns (i.e., alpha generation), and then work backwards to create a link with, say, a 1-on-1 meeting at a sell-side conference between the company’s CFO and an analyst from the trading firm. As a result, company management today is extremely tightlipped, not just on the obvious topics such as quarterly earnings or some other business metric, but on anything other than what has been very publicly disclosed. Before 2009 you could almost always get a read on the “body language” of senior management, the overall behavioral equivalent of a wink or nod to the general business conditions facing the company. Those days are gone, and that makes the stock-picker’s job – particularly at really large asset managers – so much harder.
Why is the loss of body language and other seemingly generic signaling so important? Because there’s only one question you truly need answered if you’re a good stock-picker who has done his homework on a company. That question is NOT “what are your earnings going to be this quarter?” or “how are gross margins looking?” or “did you hit your revenue guidance?” The only question that really matters is what Laurence Olivier’s Nazi dentist asked Dustin Hoffman in The Marathon Man: Is it safe?
If you’ve never seen The Marathon Man…well, let’s just say that you may never have the same level of comfort in the dentist’s chair after watching it. Olivier needs to know if his transit route for a shipment of diamonds has been blown – Is it safe? – and he believes that Hoffman knows the answer. Hoffman doesn’t, but that doesn’t stop Olivier from torturing Hoffman in ways that only a skilled Nazi dentist could devise.
Fortunately for senior company management, institutional investors may be annoying, but they are rarely torture experts. The question, though, is identical. A big fund has had a position in your stock for a couple of years. They’ve done their work and they have a positive, long-term investment opinion. They don’t need you to confirm their investment opinion in every detail (although that would certainly be nice if you were so inclined), and they’re patient investors. You’ve gotten to know them over time, and while you wouldn’t call them friends you’ve developed something of a warm familiarity and more than a little mutual trust. They’re on your side. Now you’re on a private call or at a conference 1-on-1 meeting, and the CIO of the fund tells you that they are planning on turning their current position into a very large position. He has only one question. Is it safe?
Before Reg FD you told the CIO everything he wanted to know. Not just whether it was safe, but all the degrees of safeness and what the fund should look for to see how that safety developed. After Reg FD in 2000 but before the 2009 SEC jihad you still felt pretty comfortable communicating an answer with a hem and a haw, maybe a reference to a prior period in the company’s history or a generic expression of caution or excitement … body language. Today you duck the conversation entirely and have the IR VP sit in for you. You have large group meetings with lots of people in the room. You say nothing that has not already been said, word for word, in a 10-Q or an 8-K filing.
Now put yourself in the CIO’s shoes. You still have to take big swings with your portfolio, both because you’ve got a lot of money to put to work and you have to distinguish yourself against your benchmark. Maybe you can seek safety in the consensual validation of other managers, a Common Knowledge answer to the “Is it safe?” question, which is why there is such a pronounced herding behavior among active managers today in stocks like Apple. Or maybe you move towards an activist strategy, where you can once again acquire private information about a company and influence management directly, albeit at the significant risk of locking yourself into an investment you cannot easily exit. The bottom line is that without an answer to the “Is it safe?” question you’ve got less private information and more risk for the same reward.
Over time and across the population of active investment managers, more risk for the same reward translates directly into less alpha. Such is the “level playing field” of full disclosure, a structural shift in market rules that will persist no matter what happens to corporate earnings or Fed monetary policy.
In future notes I’ll explore the portfolio and risk management implications of these changing rules. Is alpha even possible under these new rules? I believe it is, but not through the old lenses, or at least not easily. Alpha still depends on private information, and I intend to look for that private information through the lens of behavioral patterns, not through the traditional lens of company-specific information or opinions. I hope you’ll join me in that search at Follow Epsilon Theory.
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The pursuit of greater predictability and transparency in Fed communications is a mistake, particularly in the context of broad guarantees concerning world-shaking policies. We learned this lesson early in the Cold War through the hard knocks of Korea and Vietnam (not to mention the scares of Berlin and Cuba), and it seems a shame that we appear determined to learn these lessons the hard way all over again.
“We’re gonna win the game. I guarantee it.”
– Joe Namath, 3 days before Super Bowl III
“Our torments also may in length of time Become our Elements.”
– John Milton, “Paradise Lost”
“When did the future switch from being a promise to being a threat?”
– Chuck Palahniuk, “Invisible Monsters”
“Some say the world will end in fire, Some say in ice. From what I’ve tasted of desire, I hold with those who favor fire.”
– Robert Frost, “Fire and Ice”
S = k * log W
– Ludwig Boltzman’s entropy formula, as carved on his gravestone
So how does the Story end?
We are in the throes of the greatest monetary policy experiment the world has ever seen, and there are two popular Narrative arcs competing to project the ultimate resolution of the Story of QE. On the one hand we have the Happy Ending, where the Fed unwinds its $4 trillion balance sheet over time and we return to the halcyon days of either the 1990’s or the mid-2000’s, depending on your political persuasion. In this story arc the Fed voluntarily abdicates its throne as master of all things market-related in favor of its former role as a beneficial eminence grise, and we all live happily ever after. On the other hand we have the Shocking Ending, where the Fed loses control over inflation expectations and the long-end of the yield curve, and we return to the sad days of either Jimmy Carter or Weimar Germany, depending on your political persuasion. In this story arc the Fed flails around like a Mad God, leaving ruin in its wake and gold at $10,000 per ounce.
Status quo opinion leaders are enormously invested in the Happy Ending, for obvious reasons, and insurgent opinion leaders are equally invested in the Shocking Ending, for equally obvious reasons. For all I know, either one of these story arcs may turn out to be right. I don’t have a crystal ball, sad to say, and I can imagine a fact pattern that would drive the political and economic outcome to either extreme scenario. In fact, when a persuasive opinion leader talks about the path to either extreme scenario, it all sounds quite plausible to me until, of course, I hear a still more persuasive opinion leader talk about the opposite scenario.
We are, as social animals, evolved over millions of years and culturally trained over tens of thousands of years to respond to these story arcs, the more dramatic the better. It’s no accident that you find myths and cultural story arcs in every human society in every age, and you are kidding yourself if you think that mythology is any less prevalent or powerful in our modern “scientific” world. Robert Frost speaks for most of us, I believe, in his experience of desire and his preference for a world that ends in fire rather than ice, but what’s most striking is that Frost casts these as the only two options for how the story ends.
I want to suggest a third ending to the story, one that is terribly unsatisfying from a human behavioral perspective, but one that I believe is far more likely from a historical perspective – the Entropic Ending, the long slog of a gray winding-down, neither fire nor ice, neither Happy nor Shocking, where the transformation of emergency monetary policy into permanent government program creates a low growth, low inflation political equilibrium that can last for decades. Stocks will go up and stocks will go down, but not by much either way. Perpetually disappointing growth translates into persistently dashed expectations of corporate earnings growth, but the programmatic Fed backstop of financial asset prices essentially outlaws a significant price decline. There are neither secular bull markets nor secular bear markets in an Entropic Ending, just an ossification of an increasingly mediocre status quo.
Certainly there will be moments of political theatre, as we are experiencing today with the media-driven Sturm und Drang over a government “shut-down”, where we are forced to bear witness to the heartache of a couple whose wedding at Yellowstone National Park was cancelled or the tragedy of an EPA scientist who must start his research experiment all over again. Oh, the humanity! And certainly there will be moments of market exuberance, driven by, say, the thrilling prospects of yet another LTRO program or by Chinese growth coming in at 7.5% rather than 7.0%. Neither the business cycle nor animal spirits are entirely eliminated in an Entropic Ending, but they are severely muted, and both market spikes down and market spikes up should be faded in this scenario.
At the heart of the Entropic Ending is the behavioral consequence of a sea change in the perceived meaning of the Fed and its policies, from a probabilistic promise of financial asset price support to an explicit programmatic guarantee. The Bernanke market put is nothing like the Greenspan market put, not because it is quantitatively larger but because it has been signaled and reinforced to the point of Common Knowledge certainty. From a game theoretic perspective, there is an enormous difference in what Tom Schelling called “the threat that leaves something to chance” and the threat (or promise) that is perceived to be certain in its delivery. As counter-intuitive as it may seem, behavioral equilibria driven by probabilistic promises are actually more stable than those driven by guarantees, and this is why government policy guarantees (from Social Security retirement insurance to Medicare medical insurance to, now, QE growth insurance) must be backed by the full faith and credit of the US government. Without the deepest of deep pockets to stabilize what is otherwise a weak equilibrium, these programs would all end in tears sooner rather than later, creating their own versions of the Shocking Ending. With the unconditional support of the US government, on the other hand, the Shocking Ending can be pushed off for decades. But it’s silly to believe that there is not a crushing cost associated with the ever-increasing measures required to keep a policy guarantee intact, a cost that expresses itself in lower growth and fading chances of the Happy Ending. In the end, Entropy always wins, and policy guarantees just accelerate that process.
Tom Schelling, who won the 2005 Nobel Prize in Economics for his work in game theory, was less interested in macroeconomic policy than he was in defense policy. In particular, his specialty was understanding the logical underpinnings of nuclear deterrence, and in books like The Strategy of Conflicthe laid out the foundations for a US nuclear policy that both avoided Armageddon and won the Cold War. Schelling is a largely unsung hero of that conflict, a brilliant thinker, and if you could read only one book on game theory you would make a fine choice with The Strategy of Conflict.
The broad thrust of Schelling’s work on nuclear deterrence was to question the dogma of his day, Mutual Assured Destruction (MAD). MAD is based on an unconditional guarantee…if you Russians cross certain clearly demarcated lines we Americans will blow you up, even though we understand that we will also be blown up in the process. Since it’s hard to enjoy the fruits of, say, a tank invasion through the Fulda Gap when Moscow, Stalingrad, and every other Russian city is a smoldering radioactive ruin, MAD does indeed create a strong behavioral incentive not to invade West Germany. And vice versa, the US was strongly incentivized by MAD not to invade Cuba or support the occasional anti-Soviet movement in Eastern Europe, creating a behavioral equilibrium of, if not Peace, then at least No Direct War Between The Big Boys. Unfortunately, as Schelling (and to be fair, many others as well) pointed out, there are two fundamental weaknesses with MAD.
First, while it may be somewhat credible that Americans would prefer mutual suicide to a Russian conquest of the Western United States (Red Dawn notwithstanding), can you really say the same about a Russian attack on Japan? On West Berlin? The farther out you draw the “Do Not Cross” lines, the less believable MAD becomes, and that’s a bad thing because the stability of MAD’s behavioral equilibrium is entirely determined by the certainty of the promise to respond with overwhelming force. MAD depends on a guarantee that must be maintained at all costs, which is what makes it such an expensive and fragile strategy.
Second, what happens if your adversary gets right up to the clear line you’ve drawn and just pokes at it a little? He doesn’t cross it with tanks, but engages in more subtle but still entirely unwelcome advances. If you tolerate that first little poke, isn’t it pretty obvious that you will tolerate a second poke, and a third, and so on until that original line in the sand is only useful for deterring the most obvious and overt threats? Preventing a Warsaw Pact armored column from encircling Frankfurt is certainly a worthy goal, but if that’s the only behavioral equilibrium that MAD can achieve, at the cost of hundreds of billions of dollars and the non-trivial chance of human extinction if either party makes a mistake … well, that seems like a rather poor policy choice. Stanley Kubrick crystallized the susceptibility of programmatic MAD to miscommunication and poor signaling in his classic movie Dr. Strangelove: Or How I Learned to Stop Worrying and Love the Bomb, and if there’s a better visual depiction of the absurdity of a guaranteed massive nuclear response than Slim Pickens riding a warhead down to Earth I have yet to find it.
Not only did Schelling collaborate extensively with Kubrick in making Dr. Strangelove, but also (and more importantly) his work was instrumental in transforming US strategic doctrine away from MAD and towards a probabilistic, war-fighting policy. Probabilistic in the sense that a few clear lines were replaced by many fuzzy lines, where transgressions might or might not trigger a response. War-fighting in the sense that nuclear weapons were no longer treated as an all-or-nothing “spasm”, to use Robert McNamara’s phrase, but were redesigned in all sorts of shapes and forms so that their actual use as a response to a wide range of threats was much more believable. The central insight of Schelling’s work is that a probabilistic promise to use nuclear weapons, a “threat that leaves something to chance”, combined with a range of nuclear options so that it’s easier to use them, creates a much more stable peace where nuclear weapons will never be used. Thanks in part to Schelling’s work, the US government got out of the business of making guarantees when it came to nuclear deterrence (as did the Russians, who matched our move to a war-fighting strategy pretty much step for step), and the world was far safer for it.
How, then, to explain the opposite tendency within domestic policy, where the government tends to embrace programmatic economic guarantees rather than push them away? Specifically, why have we moved from the war-fighting ambiguity of a Greenspan put to the MAD-like guarantee of open-ended QE? There is both a human impetus to transforming a probabilistic promise into a guarantee as well as a political impetus, and the Fed Chairmen and governors who determine monetary policy are much more prone to both than the generals who determine nuclear deterrence policy.
The human impetus is familiar to anyone who is constantly in the public eye, whether it’s a sports star or a Fed Chairman. There is such a public appetite for the dramatic story arc of a guarantee, and there is such an enormous public reward for “delivering” on that guarantee and becoming a Hero, that these public guarantees are made all the time in highly public endeavors even though everyone knows that the guarantor has no certainty of success, particularly in a team sport.
For every Joe Namath or Mark Messier you have at least two Patrick Ewings, who become Goats for their failed guarantees. Despite these odds, it doesn’t prevent new guarantees from being made every day. Stranger still, it doesn’t dissipate the public and media fascination with the act of making a guarantee, even though we all know it doesn’t make any sense. Such is the power of the Hero Narrative.
Generals don’t make guarantees – not because they are smarter than sports stars or Fed Chairmen – but because, unless we’re in the midst of a big war, no one knows who they are. I would bet that not one person in 100,000 can name the current Chairman of the Joint Chiefs of Staff, much less the head of the US Strategic Command. But everyone in the world knows who Ben Bernanke is, and that creates an enormous pressure to “step up” and be who everyone wants him to be: the Hero. We all know what a Hero does, including the person thrust into the role. He must inspire his team or his troops or his country, and that means making an unconditional guarantee of success. This is the story arc of the Hero, from Gilgamesh to Arthur to Washington to Bernanke. Like it or not, it comes with the job.
The political impetus to embrace programmatic guarantees is no less powerful than the personal. Governments protect the governed from threats. This is what they do. This is how they stay in power. I don’t mean that this is how specific individuals or political parties stay in power (although this may also be true). I mean that this is how a regime – the amalgamation of political norms and institutions that constitute what it means to be a government at any given point in time – maintains the consent of the governed. Regimes do not stay in power by succeeding wildly; they stay in power by avoiding abject failure and by responding publicly to perceived threats. Once embraced, programmatic governmental guarantees never just go away on their own. Not only do they become institutionalized and thus acquire bureaucratic inertia and support, but more importantly they become part of what it means to be American, or French, or Chinese, or what have you. The threats that any regime responds to may change over the decades, but the programmatic responses to those threats accrete and remain over time.
The perceived threat in the aftermath of the Great Recession is an inchoate fear of something that will make prices go down again. Worried that Congress might make some fiscal policy error? Worried about Obamacare? Worried about a Chinese hard landing? Worried that Europe might not get out of recession? Worried about the Middle East? Better keep QE going just to be safe. The future looms large today as a threat rather than as a promise, because the American regime (and by extension, the global regime) cannot withstand another nationwide decline in US home prices or a serious decline in the US stock market. Why not? Because the programmatic guarantees already made by the American regime (pensions, retirement insurance, medical insurance, poverty insurance, housing insurance, food insurance, banking insurance, etc.) cannot withstand a deflationary environment. It is politicallyuntenable for asset prices to go down again, and so they won’t. If that comes at the cost of massively pulling forward demand for risk assets, of creating the mother of all crowding-out effects in Treasuries, of creating a $4 trillion balance sheet to fund an umbrella guarantee program, of lowering the structural growth potential of the country and the world … well, so be it. The goal of any regime, any organism, is to maximize its chances of survival. Deflation is the perceived existential threat of our age, and this is the dragon our Heroes will guarantee to slay.
Providing a programmatic guarantee against asset price deflation does NOT mean that runaway inflation is just around the corner, any more than it means Social Security will go bust or that Obamacare will bankrupt the country. You can create a compelling story arc around any of these scenarios, to be sure, and maybe they will come to pass after all, but I wouldn’t ever want to bet against the ability of the American regime to maintain the status quo Narrative well enough to survive. As Milton wrote, you can get used to anything over time, even Hell, and from that perspective, programmatic QE doesn’t look half bad.
By the same token, however, providing a programmatic guarantee against asset price deflation does NOT mean that nothing has changed structurally in the relationship between State and Market. This time IS different, in the same way that the structural relationship between State and Market changed in the aftermath of the Long Depression of the 1870’s and the Great Depression of the 1930’s. There’s no sense in rending our clothes or gnashing our teeth over what’s happened … this is the business we’ve chosen, to quote Hyman Roth, and so we better get on with our business in as clear-eyed a fashion as possible. We are all suckers for a good story, but we can improve our decision-making under uncertainty by recognizing this innate human bias, by taking a broad historical view of current events, and by calling things by their proper names.
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