What Makes a Good Financial Backtest? Avoid These Five Traps
Historical strategy results can be misleading when data selection, costs and hindsight shape the outcome.
A backtest applies defined rules to historical data. It is useful for exploring how those rules might have behaved but cannot prove future returns. Look-ahead bias occurs when information unavailable at the time of a trade influences a simulated decision; survivorship bias can arise when failed assets disappear from the dataset.
Other common errors include excluding spreads and fees, assuming guaranteed stop prices, selecting parameters because they happen to fit one period and ignoring changes in volatility regimes. A strategy optimized over many variations can discover noise rather than a repeatable signal. An impressive equity curve is not enough to establish validity.
Record the data vendor, sampling frequency, execution assumptions and out-of-sample performance. Consider stress periods and whether a modest parameter change destroys results. A forward test can reveal additional problems but is still not a guarantee. This article is research methodology, not a recommended strategy.
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