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BACKTESTING · SAMPLE SIZE

A Profitable Crypto Backtest With 20 Trades: Is the Sample Useful?

Twenty profitable trades can come from luck as easily as from an edge. Before trusting a result, measure how uncertain it is.

By ChartsPod Editorial Team · Reviewed by ChartsPod Research
Published · Updated · 5 min read

Short answer

A backtest with 20 trades gives a very uncertain estimate of a strategy's edge. With a 60% observed win rate over 20 trades, the plausible true win rate spans roughly 39% to 81% at 95% confidence (normal approximation). Results can also depend on one or two large winners. Increase the sample (more markets, longer history, lower timeframe if the logic allows), check how much profit comes from the top trades, and require the result to survive costs and out-of-sample testing.

How uncertain is 20 trades?

TradesObserved win rateApprox. 95% range
2060%39%–81%
10060%50%–70%
40060%55%–65%

Range ≈ win rate ± 1.96 × √(p(1−p)/n). Illustrative.

Width of 95% range by sample size (percentage points)Width of 95% range by sample size (percentage points): 20 trades 42.9 pp; 100 trades 19.2 pp; 400 trades 9.6 pp.WIDTH OF 95% RANGE BY SAMPLE SIZE (PERCENTAGE POINTS)20 trades42.9 pp100 trades19.2 pp400 trades9.6 pp
Uncertainty halves when the sample quadruples. Original ChartsPod editorial graphic.

Profit concentration

Remove the best two trades and recompute. If profit turns into a loss, the strategy depends on rare events that may not repeat. Illustrative: 20 trades, total +$3,000, best two trades +$3,400; without them, −$400.

Small-sample checksSmall-sample checks: Confidence range on win rate; Profit without top 1–2 trades; Results on other markets; Results in other years; Results after costs.SMALL-SAMPLE CHECKSConfidence range on win rateProfit without top 1–2 tradesResults on other marketsResults in other yearsResults after costs
Each check asks whether the result is robust. Original ChartsPod editorial graphic.

Growing the sample honestly

Test the same rule, unchanged, on more markets and periods. Don't loosen the rule just to get more trades; that creates a different strategy. If the logic only fires rarely, accept that its edge will stay uncertain and size accordingly.

Sizing when the edge is uncertain

If you decide to trade a strategy with limited history, size it as if the edge could be at the low end of its plausible range. Start small, track live results separately from the backtest, and only increase size as live trades accumulate and stay consistent with the backtest. A live sample of 50 trades that matches the backtest is better evidence than any amount of re-optimisation on the same history.

Conclusion

Treat a 20-trade backtest as a hypothesis; widen the sample with the same rule before trusting it.

Related: Parameter Optimization: Report All Trials, Not Just the Winning Curve, Crypto Strategy Profit Factor vs Expectancy: Read Both With Costs.

Test the same rule across several markets.

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Review A Profitable Crypto Backtest With 20 Trades with bar replay before using it live.

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Questions readers ask

Is 20 trades enough?

Rarely; the estimate of edge is very wide.

How many trades do I need?

Hundreds narrow the uncertainty substantially; it depends on edge size and variance.

What if the strategy trades rarely?

Test on more markets and periods without changing the rule.

Sources and methodology

Backtesting principles follow TradingView's Pine Script documentation on strategies, repainting and non-standard charts, and ChartsPod's strategies-and-backtests guide summary, as read on 17 October 2026. All numbers are illustrative and do not describe a real strategy's performance.

  1. TradingView Pine Script: Strategies — simulated fills and assumptions.
  2. ChartsPod documentation — guides for order flow, derivatives, alerts, backtests, journal and workspaces.

This article explains research tools and workflows. It is not financial advice, does not recommend buying or selling any asset and does not predict prices. Crypto derivatives carry a risk of rapid and total loss of margin.

CHARTSPOD EDITORIAL EDITION · RESEARCH AND EDUCATION ONLY · NOT FINANCIAL ADVICE.