This question keeps more traders up at night than almost any other — and rightly so. Knowing whether your strategy genuinely has an edge, versus whether you just got lucky during a bull run, is genuinely difficult. Markets are noisy. Humans are pattern-seeking. The combination is a recipe for expensive self-deception.

The direct answer is this: a strategy works if it produces a positive expectancy over a statistically significant sample of trades, survives out-of-sample testing, and holds up under realistic conditions including slippage and commissions. One good month proves nothing. A strategy that performs consistently across 200+ trades in varied market conditions is starting to say something meaningful.

CONCEPTPositive expectancy means your average win, weighted by frequency, exceeds your average loss — that's the foundation every real edge is built on.
WARNINGCurve-fitting a strategy to historical data produces a backtest that looks brilliant and a live account that bleeds — don't mistake optimisation for validation.
KEY IDEAForward testing on a demo account after backtesting is the bridge between theory and reality — skip it and you're flying blind with real money.

Think of it like a restaurant recipe. You can taste-test a dish a hundred times in your kitchen — that's your backtest. But serving it to actual paying customers on a busy Friday night, with a different oven and time pressure? That's forward testing. Both matter. The recipe that only works in your quiet kitchen probably isn't ready for the menu.

Strategy Equity Curve: Three Phases 0 +10% +20% Backtest Forward Test Live

The three metrics traders focus on most are win rate, risk-to-reward ratio, and maximum drawdown. A strategy with a 40% win rate can still be highly profitable if winners are three times the size of losers. Maximum drawdown tells you how much pain the strategy inflicts on its worst run — and whether you'd actually stick with it when things get ugly. For deeper reading on how these concepts interrelate, backtesting on Investopedia explains the mechanics clearly, while the concept of expected value underpins why sample size matters so much. The broader mathematical framework behind it all traces back to statistical hypothesis testing — which is essentially what every serious trader is doing, whether they realise it or not.

Your practical takeaway today: pull your last 50 trades, calculate your average win, average loss, and how often each occurred. That single calculation will tell you more about your strategy than any indicator on your chart.

A strategy isn't proven by how good it feels — it's proven by what the numbers say when you stop cherry-picking which trades to count.

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.