Backtesting term
Win rate
Win rate is the percentage of trades that close in profit. It's also the single easiest number in a strategy's marketing to manufacture without adding a shred of real edge.
Win rate is the share of trades that close green. It's the first stat every strategy seller quotes, and the most misleading one they could pick. A system can win 95 percent of the time and still be a certain loser, if the rare losses are large enough to swallow every small win that came before them. The number sounds like an edge. It's usually just an accounting trick.
That gap is the whole design behind grid and martingale systems: by averaging down and refusing to close a red position, a bot manufactures a gorgeous win rate while one sustained trend quietly builds the loss that erases the account. We tested 76 grid and DCA systems against real bid/ask spreads on real markets. All of them failed. Not most. All. The win rate on the way up was never the issue; the open drawdown on the way down was.
High win rate is a design choice, not an edge. Any system willing to hold a loser long enough, or widen a stop far enough, can print green tickets almost at will. Small wins are cheap to manufacture. The cost just moves downstream, into size instead of frequency, and lands on the one trade nobody wants to talk about.
So we don't score a strategy on how often it wins. We score it on what the winners make against what the losers cost, the profit factor, read together with how deep the account dips along the way. A strategy with a mediocre win rate and a strong profit factor is doing real work. A strategy with a stunning win rate and a thin profit factor is one bad week from zero.
Ask any bot advertising a 99 percent win rate what its worst single loss looks like. If the answer is vague, or the trade is still open, that's the whole review in one question.
The win-rate illusion in grid/DCA bots →
The research behind this
- Sharpe (1994). “The Sharpe Ratio.” Journal of Portfolio Management 21(1). — Defines return per unit of risk, the reference point for judging whether a high win rate is actually rewarded relative to what it risks.
- Aronson (2006). “Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals.” Wiley. — Shows how picking the best-looking rule from many candidates biases results, the same trap behind choosing a system for its win rate alone.
External research, linked for context and further reading. FoxAlgo is independent and not affiliated with these authors or publishers.
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