Discussing the article: "Building a Correlation-Aware Multi-EA Portfolio Scorer in MQL5"

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Check out the new article: Building a Correlation-Aware Multi-EA Portfolio Scorer in MQL5.

Most algo traders optimize Expert Advisors individually but never measure how they behave together on a single account. Correlated strategies amplify drawdowns instead of reducing them, and coverage gaps leave portfolios blind during entire trading sessions. This article builds a complete portfolio scorer in MQL5 that reads daily P&L from backtest CSV files, computes a full Pearson correlation matrix, maps trading activity by hour and weekday, evaluates asset class diversity, and outputs a composite grade from A+ to F. All source code is included; no external libraries are required.

Many MQL5 developers optimize individual strategies but do not evaluate how the strategies interact in a portfolio. This is the equivalent of a chef who masters ten recipes but never considers whether they belong on the same menu. A portfolio of five gold scalpers is not diversification—it is concentration disguised as variety.

In this article, we will build a practical MQL5 script that solves this problem. By the end, you will have a working portfolio scorer that:

  • Reads equity curves from multiple EA backtest reports.
  • Calculates a Pearson correlation matrix between every pair of strategies.
  • Analyzes trading hour and day-of-week coverage across the portfolio.
  • Produces a single composite score that tells you whether your portfolio is robust or dangerously overlapping.
  • No external libraries are needed. No Python, no R. Everything runs natively inside MetaTrader 5.


    Author: Cristian David Castillo Arrieta

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