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The Love/Hate Cartoon

Rusty Guinn

April 7, 2019·2 comments·In Brief

Every few weeks, a financial analyst publishes data showing which stocks active investors are buying and which they're avoiding. These analyses are wildly popular, fuel countless news articles, and appear to reveal something real about market behavior. But they contain a fundamental logical flaw that nearly everyone overlooks, and yet nearly everyone who should know better seems perfectly comfortable with the contradiction.

• Financial media treats a mathematical impossibility as market insight. If active management is truly zero-sum (which passive advocates insist it is), then all stock overweights and underweights must net to zero across the investor universe. Yet these regular analyses consistently show large, persistent biases in one direction. Something doesn't add up.

• The data driving these analyses carries invisible distortions. The datasets used are incomplete, periodicity is imperfect, and entire categories like derivatives are often excluded. What gets presented as "what active investors love" is actually a portrait of whatever data happened to be available to the analyst.

• The methodology itself is arbitrary and non-transparent. One analyst counts positions by frequency across fund filings. Another weights by assets under management. A third ignores cash positions entirely. Each method produces different "love/hate" lists, but all get published as equivalent truths.

• Structural biases built into manager categories are presented as market signals. Large-cap managers systematically overweight smaller stocks because meaningful mega-cap positions constrain portfolio construction. These aren't revelations of investor preference. They're mathematical artifacts of the category definition itself.

• The real question nobody asks is why the industry keeps producing analyses it knows are flawed. If these cartoons don't represent actual market behavior, what purpose do they serve? And why does even the investment community that should recognize the logical problem keep treating them as actionable intelligence?

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Comments

Mkahn22's avatar
Mkahn22almost 7 years ago

This insight is why I read ET (well, one of the reasons why I read ET) - it not only explains the topic at hand, but forces me to think harder and deeper about things I think I understand well, like, in this case, passive investing:

“You don’t have to argue with someone explaining why it’s OK that their model predicts that 70% of outcomes are worse than the median. If you believe at all in the principles that underlie a belief in passive management, the zero-sum game is your rock. If someone can’t adequately explain why they are telling you a massive cross-section of financial markets is non-zero-sum, or if they can but can’t explain why the dimensions of that cross-section aren’t just a feature of persistent structural tendencies related to the definition of that cross-section, they simply don’t have information that is of any interest to you.”

My only somewhat counterpoint to the theme of the piece - the sell-side creates a cartoon of the buy-sides’ results for its own business advantage (which is fair and accurate) - is to also recognize that the opportunity to do so - to create active-management-results analysis - exists because the buy-side has no interest in creating honest, non-bias, industry-uniform standards to measure its performance* because of its own business interests.

  • I’m not saying it would be easy or even fully doable, but come one, no one is even trying as everyone is reverse engineering its analysis methodology to produce the best / most explainable result for him or herself.

rguinn's avatar
rguinnalmost 7 years ago

I think it is very fair to say that everyone is getting a little bit of what they want here, which is the ability to prevent others from accurately assessing their performance / research. Thanks, Mark!

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rguinn's avatarMkahn22's avatar
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