How to Read Backtest Output Without Fooling Yourself
A backtest output is a report card that shows how a strategy would have performed on past data, and reading it well means knowing which numbers actually matter. Start with the big picture: total return, then the equity curve, which is a line showing how the account grew or shrank over time. A smooth, steady rise is more trustworthy than a jagged one that got lucky. Then check the risk side: maximum drawdown, the worst peak-to-low drop, tells you how painful the ride was. Next look at the trade stats: number of trades, win rate, average win, average loss, and expectancy, which together say whether the edge is real and how it's built. Finally confirm the sample is large and the test included fees and slippage. A great return means little if it came from ten trades with no costs.
A structured approach to evaluating backtest output without falling for common biases, including cherry-picked start dates and curve-fitting.
Key points
- The equity curve shows how the account grew over time, and a steady climb is more trustworthy than a jagged, lucky-looking one.
- Maximum drawdown tells you the worst drop, which is often more important than the headline return.
- Number of trades reveals whether the results rest on a solid sample or just a handful of lucky bets.
- Win rate, average win, and average loss combine into expectancy, the single number for whether each trade adds money.
- Profit factor, which is gross profit divided by gross loss, describes reward against risk rather than raw return.
- Always check that fees and slippage were included, because ignoring costs can turn a losing strategy into a fake winner.
Frequently asked questions
What are the most important numbers in a backtest?
Start with the equity curve and maximum drawdown to judge the risk, then look at the number of trades and expectancy to judge whether the edge is real and large enough. Total return matters, but it's misleading without those other numbers next to it.
What is a profit factor?
Profit factor is total money made on winning trades divided by total money lost on losing trades. A value above 1 means the strategy made more than it lost, and higher is better, though a very high number from few trades is a warning sign rather than a trophy.
What does the equity curve tell me?
It shows your account balance over the life of the test as a single line. You're looking for a fairly steady upward slope. Sharp spikes, long flat stretches, or one giant jump that carries the whole result are all reasons to dig deeper.
Why do fees and slippage matter in a backtest?
Because they're real costs you'll actually pay. Slippage is the difference between the price you expected and the price you got. Many strategies look profitable until you subtract these, so a test that ignores them can be badly misleading.
Where do I see all these numbers for a strategy?
When the AlgoAgent runs a backtest, it lays out the equity curve, drawdown, trade count, win rate, and expectancy in one place, so you can read the whole report card together instead of hunting for each number.
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This content is for educational purposes only and does not constitute financial advice. Trading involves risk, including possible loss of capital.