Here is how most traders adopt a new indicator: they see it work twice on a chart, feel a rush of excitement, and immediately size up. Two losing trades later, they blame the indicator. The indicator was never the problem — the absence of any structured backtesting was. Trusting a signal without testing it is like hiring someone based on their LinkedIn photo.

Backtesting means running your indicator's rules against historical price data and recording every signal it would have generated. The key word is rules — precise, unambiguous entry and exit conditions. Not "RSI looks low." Something like: RSI(14) crosses above 30 after being below 30 for at least two consecutive closes, exit when RSI crosses above 70 or price drops 2% from entry.

CONCEPTA backtest is only as good as the rules fed into it — vague conditions produce meaningless results.
WARNINGCurve-fitting your indicator settings to past data is not validation — it is glorified data mining.
KEY IDEATest across at least 200 signals and multiple market conditions before drawing any conclusions.

The minimum sample size most systematic traders use is 200 trades. Fewer than that and your results are statistically unreliable — one good streak or one bad streak skews everything. Split your historical data: use 70% to develop the rules, keep the remaining 30% as out-of-sample data you test on afterward. If performance collapses on the out-of-sample set, the indicator does not generalise — it memorised.

Backtest: In-Sample vs Out-of-SampleIn-SampleWin Rate: 61%Out-of-SampleWin Rate: 44%30%60%Performancedrop = likelycurve-fit

Two other numbers matter enormously: maximum drawdown and expectancy. Maximum drawdown tells you the worst peak-to-trough equity loss your rules would have produced — if it exceeds what you could psychologically tolerate, the strategy is dead before it starts. Expectancy is (win rate × average win) minus (loss rate × average loss). A positive expectancy figure, calculated honestly, is the foundation every indicator-based approach needs before live deployment. Solid grounding on backtesting methodology is available at Investopedia, and the statistical concept of overfitting explains precisely why curve-fitted results collapse in live markets. For a deeper look at how expectancy is calculated, the expected value framework at Investopedia is worth the ten minutes.

An indicator that has not been backtested is just a rumour with a pretty line drawn through it. Test it, stress it, then decide.

This content is for educational purposes only and does not constitute financial product advice. Past performance is not indicative of future results. Profit Logic Ltd (ACN 688 669 936) accepts no responsibility for errors or omissions in this content or anywhere on this website. Always seek advice from a licensed financial adviser before making investment decisions.