METATRADER 4

MetaTrader Backtesting: Best Practices for Algorithmic Traders




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MetaTrader 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:

MetaTrader Backtesting – Best Practices for Algorithmic Traders

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:
https://www.darwinex.com/?utm_source=youtube&utm_medium=video-description&utm_content=metatrader-backtest-tutorial-best-practices-algorithmic-traders

1.9M in performance fees paid to date:
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Topics: #metatrader #algorithmictrading #backtesting

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