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On the random walk hypothesis and post-hoc explanations for describing natural processes, from "Patterns and the Stock Market":
While it's certainly entertaining to spin post-hoc explanations of market activity, it's also utterly futile. The market, after all, is a classic example of a "random walk," since the past movement of any particular stock cannot be used to predict its future movement. This inherent randomness was first proposed by the economist Eugene Fama, in the early 1960's. Fama looked at decades of stock market data in order to prove that no amount of rational analysis or knowledge (unless it was illicit insider information) could help you figure out what would happen next. All of the esoteric tools and elaborate theories used by investors to make sense of the market were pure nonsense. Wall Street was like a slot machine.
Alas, the human mind can't resist the allure of explanations, even if they make no sense. We're so eager to find correlations and causation that, when confronted with an inherently stochastic process - like the DJIA, or a slot machine - we invent factors to fixate on. The end result is a blinkered sort of overconfidence, in which we're convinced we've solved a system that has no solution.
"Is an economic recession a divergence from the market trend that eventually reverses over time? Or is it more analogous to a random walk?" asked the student.
The master struck him on the head with a walking stick. "Economic recessions are primarily qualitative; attempting to measure them is meaningless."
Quantitative fundamentals play a role in shaping market dynamics, but in a Bayesian spirit, so too does information and discourse circulating within those markets. "It's priced in," is an expression people use to describe the way that the market's dynamic is not just a sum of monetary fundamentals but also a sum of qualitative sentiment, which is far more difficult to quantify.
Sure, you could try to measure a market recession with GDP output, but if you want an even better attempt at understanding one, you may have greater success communicating with actual market participants—but even then, perspectives will be wildly subjective.
Recessions aside—one could also attempt, at any time, to use technical analysis to predict short-term stock prices. But you may also simply end up straining at gnats.
Furthermore, if someone is claiming to know the true reasons why the market went up or down, there's a significant possibility they are lying. Either by not knowing any better, or deliberately lying.
If they actually knew—if they actually possessed that knowledge—they would have used it to make money.
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