Your ML Model Doesn’t Compete With the Market. It Competes With Other Models
Imagine you build a trading model that predicts the next market move correctly 60% of the time. That sounds impressive. Now imagine that every serious trading firm has the same model. The accuracy is still 60%. The model has not become worse. But the edge may be gone.
This is one of the strangest things about machine learning in finance. In most ML domains, a useful model stays useful even if somebody else independently builds the same thing. In markets, the fact that other participants know the same pattern can destroy its economic value. That means a financial model should not be evaluated only by asking whether it predicts the market. A more important question is: what does this model know that competing models have not already priced in?
That turns financial ML into a relative game.
This is where game theory offers a useful lens. Markets are strategic environments:...
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