FREE MT5 Optimization Risk Adjusted Results – Python script

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This Python script provides a comprehensive analysis tool for MetaTrader 5 (MT5) strategy optimization results, helping traders identify the best parameter sets based on a balanced evaluation of both profitability and risk metrics.

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Description

Key Features

Data Processing

  • Accepts CSV files exported from MT5 optimization results (requires initial XML-to-CSV conversion via Excel)

  • Handles numeric conversion and cleans the input data automatically

Composite Scoring System

  • Implements a weighted scoring model that evaluates five key metrics:

    • Profit (25% weight)

    • Profit Factor (25%)

    • Recovery Factor (20%)

    • Sharpe Ratio (15%)

    • Equity Drawdown % (15% negative weight – lower values score higher)

Normalization Approach

  • Normalizes each metric against its maximum value in the dataset

  • Special handling for drawdown (lower values receive higher scores)

  • Combines metrics into a single composite score for easy comparison

Output Features

  • Identifies and displays the best overall parameter set with all key metrics

  • Shows all strategy parameters used in the optimization

  • Generates two output files:

    1. Full sorted results with composite scores

    2. Top 10 parameter sets for quick review

User Interface

  • Simple file dialog interface for selecting input and saving output

  • Clear console output showing the best parameter combination

Risk-Adjusted Selection

  • Balances profitability metrics with risk metrics

  • Favours parameter sets with strong performance across all dimensions

  • Helps avoid overfitting by considering multiple performance aspects

How to Use

  1. Export optimization results from MT5 as XML

  2. Convert to CSV via Excel

  3. Run this script and select the CSV file

  4. Review the console output showing the best parameter set

  5. Save the full analysis and top 10 results for further review

The script helps traders move beyond simple profit-based selection to identify parameter sets that offer the best risk-adjusted performance.

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