What the market actually prices in

Every sharp market move seems to trace back to something nobody saw coming — a sudden war, a policy shock, some discontinuity with no precedent to price against. That’s the part of market behavior I keep coming back to: the future isn’t unknowable because we’re bad at analysis, it’s unknowable because the thing that actually moves prices is, by definition, the thing nobody could have modeled in advance.

Which is why I’m skeptical of any strategy built on watching how the market behaved last time and assuming it will behave that way again. If a pattern is visible enough to spot on a chart, or explainable in a five-minute video, it’s visible enough that someone else has already traded on it — and once enough people do, the pattern gets priced away before it’s useful. History doesn’t repeat cleanly enough to trade on casually; it mostly just rhymes enough to make a convincing story after the fact.

But “you can’t trade on a hunch” is different from “there is no edge.” Real, persistent inefficiencies do exist — patterns and premia that survive being known about, either because they only pay off if you can hold through long stretches of being wrong, or because exploiting them profitably takes more infrastructure than any single chart or backtest can capture. Finding and harvesting those is a fundamentally different exercise than pattern-matching a chart. It takes rigorous, systematic, data-driven research: testing an idea across decades of data and dozens of markets, controlling for how a signal decays once too many people find it, and sizing every bet so that being wrong on any one of them doesn’t matter much.

That’s the actual case for active management done well — not someone with a strong opinion about where the market goes next, but a process built to separate real, durable signal from noise at scale, and to keep doing that as the noise itself adapts. It’s also exactly why I’d trust that kind of process over a hot tip from a video or a confidently-written blog post — including, a little uncomfortably, this one. The distance between “I noticed a pattern” and “I found something real” is a lot of rigorous work, and most of us, myself included, aren’t equipped to do that work on the side.

There’s decent academic evidence behind that skepticism about “visible” patterns, and it’s more specific than just a hunch. McLean and Pontiff tested 97 variables that academic papers had shown to predict U.S. stock returns, then checked how well each kept predicting after publication — average return predictability fell by about 26% out-of-sample and post-publication, which they read as investors learning about an anomaly from the research itself and trading it away. A newer working paper on Fama-French factors going back to 1963 fits that same decay to a hyperbolic curve rather than a straight line, and finds momentum’s edge specifically has faded from roughly 10% a year in the 1990s to something closer to 2% more recently — with the pace of the fade picking up since about 2015, tracking the growth of factor ETFs that made the same trade available to anyone with a brokerage account. Tellingly, the same paper found that trying to trade on visible crowding — buying the factors that look least crowded, selling the ones that look most crowded — didn’t produce better risk-adjusted returns than just holding the factor itself. Once a signal is legible enough to build a second-order strategy around, the market seems to have already priced that in too.

What’s harder to arbitrage away is a premium that only pays off if you can stomach being wrong for a long stretch. Momentum is the standard example: well documented across more than eighty years of U.S. data and (per Tobias Moskowitz’s summary of the literature) in international markets outside the original U.S. sample, and yet it hasn’t disappeared the way you’d expect a fully-known free lunch to. Part of the explanation is structural rather than informational — momentum strategies occasionally suffer sharp, correlated crashes exactly when everyone is forced to unwind similar positions at once, which is a cost most individual and even institutional investors are poorly positioned to sit through. A separate NBER paper on return-chasing found something related: some of what looks like a tradeable momentum “anomaly” is actually slower-moving investors chasing the return-chasers, in a pattern that occasionally ends in a predictable crash — durable, in other words, partly because riding it out requires tolerating a blowup you can see coming but can’t easily time.

August 5, 2024 was a fresh reminder of the other half of the argument — the unmodelable part. Japan’s Nikkei 225 fell about 12.4% in a single session, its worst day since the 1987 Black Monday crash, as a rate hike from the Bank of Japan collided with a weak U.S. jobs report and unwound a huge, crowded yen carry trade almost overnight. Nobody had that exact combination on a five-minute chart the week before. That’s the asymmetry this post is really about: the patterns that are visible enough to spot get competed away, often faster than a decade ago; the moves that actually reprice the world tend to arrive from a direction the chart never showed you.

Further reading