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Why strategies stop working (and what to do about it)

02 Jul 20266 min readStrategy

One of the hardest lessons in systematic trading is that a strategy which worked beautifully for months can simply stop. Nothing obvious breaks; the equity curve just flattens and then drifts down. Understanding why edges fade — and how to respond without panicking — is part of trading any system, automated or not.

[01]Markets change regime

Markets move through regimes: trending and ranging, calm and volatile, liquid and thin. A strategy is usually an implicit bet on one of these conditions. When the regime that suited it gives way to another, the same rules that printed profits start bleeding them — not because the strategy is wrong, but because the weather changed and it was dressed for a different season.

[02]Edges get crowded

An edge is also a resource that others can discover and compete away. As more participants trade the same inefficiency, it shrinks; the move that used to be reliable gets front-run or arbitraged until the margin is gone. Popularity is quietly corrosive to a simple, static strategy.

[03]Rough patch or broken system?

The practical difficulty is telling ordinary drawdown — which every strategy has — from genuine decay. This is where honest expectations set in advance are priceless: if you know the normal range of losing streaks from robust testing, a drawdown inside that range is noise, while one well beyond it is a signal to step back and review. Deciding the threshold before you are emotional about it is the whole trick.

[04]Why adaptability matters

This is a large part of the case for AI-assisted systems: rather than one frozen rule set that must be manually rewritten when conditions shift, a model can re-weight its inputs as the market changes. It is not immune to decay — nothing is — but adaptability buys resilience that a static script cannot offer. The discipline of monitoring and reviewing still belongs to you.

This is educational content, not financial advice. Past performance never guarantees future results; monitor any system, expect drawdowns, and manage risk on your own terms.

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