The Love/Hate Cartoon
April 7, 2019·0 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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