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Introduction to Backtesting

What is Backtesting?​

Backtesting is the process of testing a trading strategy against historical market data to evaluate its performance before risking real capital. It allows you to see how your strategy would have performed in the past, giving you insights into its potential profitability and risk characteristics.

Why Backtest Your Strategy?​

Fast and Cost-Effective Testing​

  • No Real Money at Risk: Test strategies without risking actual capital
  • Instant Results: Analyze years of trading in minutes
  • Multiple Scenarios: Test different market conditions and timeframes quickly
  • Strategy Optimization: Fine-tune parameters to improve performance

Performance Validation​

  • Historical Performance: See how your strategy performed during bull markets, bear markets, and ranging conditions
  • Risk Assessment: Understand maximum drawdowns and volatility
  • Trade Statistics: Analyze win rates, profit factors, and average trades
  • Comparison: Compare your strategy against simple buy-and-hold

Limitations of Backtesting​

While backtesting is valuable, it's important to understand its limitations:

1. Past Performance ≠ Future Results​

Historical performance doesn't guarantee future success. Market conditions change, and what worked in the past may not work going forward.

2. Slippage and Execution​

Real-world trading involves:

  • Order Slippage: You may not always get the exact price you want
  • Liquidity Issues: Large orders can move the market
  • Order Book Depth: Available liquidity varies throughout the day
  • Network Latency: Delays between signal generation and order execution

While Kelor simulates slippage, actual trading conditions may vary.

3. Market Impact​

Backtesting assumes your orders don't affect market prices, which may not be true for larger position sizes.

4. Overfitting Risk​

Optimizing a strategy too much based on historical data can lead to poor real-world performance. A strategy that's "perfect" for past data may fail on new data.

5. Survivorship Bias​

Historical data may not include delisted or failed assets, potentially skewing results.

6. Regime Changes​

Market structure and behavior can change due to:

  • Regulatory changes
  • Technology improvements
  • Market participant evolution
  • Global economic shifts

Best Practices​

To get the most value from backtesting:

  1. Test on Multiple Timeframes: Don't rely on a single time period
  2. Use Out-of-Sample Data: Keep some data aside for validation
  3. Be Realistic: Use conservative estimates for fees, slippage, and starting capital
  4. Paper Trade First: After backtesting, test with paper trading before going live
  5. Monitor Live Performance: Compare live results with backtest expectations

Next Steps​

Now that you understand backtesting fundamentals, learn how to: