MetaTrader Backtesting: Best Practices for Algorithmic Traders

MetaTrader backtesting can be tricky business for algorithmic traders. Follow these best practices to engineer robust, reliable trading strategies.

Risk Disclosure:

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:

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

--
Are you a good trader?

We'd love to have your strategy listed on our Exchange, enabling you to earn performance fees on investor profits!

More details here:

1.9M in performance fees paid to date:

Topics: #metatrader #algorithmictrading #backtesting