How to Backtest a Trading Strategy (And What the Numbers Actually Mean)

What Backtesting Is

Backtesting runs your trading rules against historical price data to see how they would have performed. If your rules say "buy when RSI drops below 30 and MACD shows a bullish crossover," backtesting finds every instance of that pattern in the past and calculates the outcome.

It's not a guarantee of future performance. But it's the only systematic way to evaluate a strategy before going live.

The Metrics That Matter

### Win Rate

The percentage of trades that were profitable. A 60% win rate sounds good — but if your average loss is 3x your average win, a 60% win rate is still a losing strategy.

Win rate alone means nothing.

### Profit Factor

Total gross profit divided by total gross loss. A profit factor above 1.5 is generally considered good. Below 1.0 means the strategy lost money in backtesting — stop there.

### Maximum Drawdown

The largest peak-to-trough decline in your portfolio during the backtest period. This is the number that determines whether you can psychologically survive the strategy in real life.

A strategy with a 40% maximum drawdown might be mathematically profitable over time. But will you actually hold through a 40% loss? Most people won't. They panic-sell at the bottom.

Choose a maximum drawdown you can live with. Anything over 20% starts requiring serious conviction.

### Sharpe Ratio

Return relative to risk. A Sharpe ratio above 1.0 is good. Above 2.0 is excellent. Below 0.5 means the returns don't justify the volatility.

### CAGR (Compound Annual Growth Rate)

What the strategy returned per year on average. Compare this to a benchmark like the S&P 500 (roughly 10% historically). If your strategy's CAGR is 8% with a 35% maximum drawdown, a simple index fund is a better trade.

Overfitting: The Biggest Backtest Trap

Overfitting is when you tweak your strategy parameters until the backtest looks perfect — and then it fails completely in live trading.

If you ran 50 variations of your strategy and picked the one that happened to backtest best, you've found statistical noise, not signal.

The fix: test on out-of-sample data. Use data from 2020–2022 to build the strategy, then test on 2023–2024 data you didn't use during construction.

Enki's 90-Day Backtesting

Enki lets you run any configured doctrine against 90 days of real historical data before risking capital. The output includes P&L, win rate, max drawdown, and Sharpe ratio — the four numbers that actually matter.

Start there. Don't go live until the numbers make sense.