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Module D · Strategy & Execution·Lesson 3

Backtesting Basics

Test your strategy on historical data before risking real money

4 sections · 3 quiz questions · ~5 min read

Guided course path

Keep backtesting basics inside the live track.

You are reading a reference lesson. The live course path gives you the lesson order, checks, saved progress, and next step. Execution makes more sense after the chart bias, key levels, and timeframe context are clear.

Closest track: Technical Analysis + Price ActionFirst lesson: The top-down framework
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What Is Backtesting?

Backtesting means applying your trading strategy to historical price data to see how it would have performed. It's like a flight simulator for traders — you practice without risk to build confidence and refine your rules.
Wick climbs steps for scroll back, cover the right side, move one candle and log each trade, showing how to practice a strategy on past charts by hand.1Scrollback2Coverthe right3Move 1candle4Log eachtrade
Wick saysBacktest by hiding the future and stepping forward one candle at a time.

Manual Backtesting

Scroll back on your chart, cover the right side, and step forward candle by candle. Apply your entry rules. Record each trade as if it were live. You need at least 50-100 trades for statistically meaningful results.
Wick points at a chalkboard listing win rate, average win and loss, profit factor and max drawdown, showing what to measure when you test a strategy.Track theseWin rate, avg win/lossProfit factorMax drawdown
Wick saysTest at least 50 to 100 trades and track the same few numbers every time.

Key Metrics to Track

Track: Win Rate (%), Average Win vs Average Loss, Profit Factor (gross profit ÷ gross loss), Maximum Drawdown, and Total Return. A strategy with 45% win rate and 1:2 RR can still be very profitable.
Wick pays a coin labeled spread plus fees at a toll gate named backtest, teaching that honest testing counts trading costs on every practice trade.BacktestCount costs in every testtradeSpread, fees$
Wick saysInclude spreads and fees in your backtest, or the results will look better than real life.

Common Backtesting Mistakes

Curve fitting (over-optimizing to past data), ignoring spreads/commissions, testing too few trades, and hindsight bias (seeing what happened next while deciding entries). Be honest and strict with your rules.
Quick check

Did it stick?

Try to answer each one before you peek at the explanation.

1

How many trades should you have for a statistically meaningful backtest?

2

Curve fitting means your strategy is perfectly optimized for live trading.

3

Match each metric to what it measures:

Win Rate→Percentage of trades that profit
Max Drawdown→Largest peak-to-trough decline
Profit Factor→Gross profit ÷ gross loss