Building an MQL5 Dashboard for Pearson, Spearman, and Kendall Correlations

Summary

This article explains an MQL5 dashboard for examining pairwise relationships among a user-selected set of financial symbols. It computes correlations from price changes using Pearson for linear association, Spearman for rank-based monotonic association, or Kendall for ranking concordance over a chosen timeframe and bar window. The interface presents results in a matrix and offers a threshold-based standard view with p-value significance markers or a continuous heatmap, alongside timeframe controls and a legend.

The article outlines symbol handling, statistical calculations, visual rendering, and updates when new ticks arrive or users change settings. It describes the dashboard as a tool for inspecting interdependencies relevant to diversification, hedging, and multi-asset analysis. The evidence is implementation-oriented: it reports that the interface was compiled and displayed, but gives no quantitative validation of the estimates or trading outcomes. Correlations and significance indicators summarize historical co-movement; the dashboard alone does not establish causality, predictive value, or stable relationships across periods.

Key ideas

• Pearson, Spearman, and Kendall capture different forms of pairwise association between asset returns.
• A correlation matrix can help inspect diversification and hedging relationships across selected symbols.
• The dashboard offers threshold coloring with significance stars and a gradient heatmap view.
• Timeframe controls and configurable history let users compare relationships across analysis windows.
• The article demonstrates the interface but does not validate predictive performance or trading results.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.