MetaTrader Backtesting: Best Practices for Algorithmic Traders
79MetaTrader backtesting can be tricky business for algorithmic traders. Follow these best practices to engineer robust, reliable trading strategies.
Risk Disclosure:
https://www.darwinex.com/legal/risk-disclaimer
This tutorial introduces best practices for backtesting trading strategies using MetaTrader's Strategy Tester or any other tool / programming language such as Python, Java, R, C++ etc.
Read the associated blog post here:
http://blog.darwinex.com/dos-donts-metatrader-4-backtesting/
This tutorial covers:
1) Data Handling
- Segmenting Historical Data
- Selecting Length of Historical Data
- Backtesting Timeframes Lower Than H1 (hourly)
- MetaTrader 4 Historical Data – Effects of Interpolation
- Re-validating MetaTrader 4 History Center Data
2) Parameter Selection
- Using Robust Parameter Ranges
- Estimating Impact of Variable Spread & Slippage
- Maintaining Stable Underlying Strategy VaR
3) Variable Factors
- Correlation of Strategy Returns to Market Volatility
- Testing for Market Correlation
- Optimizing Position Sizes for Capacity
- Trading High Impact News
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Topics: #metatrader #algorithmictrading #backtesting