Building a Seasonality Indicator for Intraday and Calendar Patterns
Summary
The document explains how to build an MQL5 indicator that groups historical returns by calendar day, weekday, or hour. It describes a separate-window histogram of average returns, an optional forecast line and points for upcoming bars, and text statistics identifying the strongest and weakest periods. User settings control the seasonality grouping, history depth, return units, positive-only display, and forecast styling.
The calculation compares returns within each time bucket and aggregates them into average values for display. The article provides implementation structure and code examples for inputs, buffers, labels, initialization, and chart presentation, but the supplied text omits part of the calculation details. It gives no empirical validation that seasonal effects persist or produce trading profits. Results depend on the chosen asset, timeframe, sample length, and data quality, so the indicator should be treated as a descriptive historical analysis rather than a reliable forecast on its own.
Key ideas
- The indicator groups historical returns by day of month, weekday, or hour.
- Average returns are displayed as a histogram, with optional forecast graphics and period statistics.
- Inputs let users choose the analysis window, return format, and display options.
- Historical seasonal averages describe past data and do not establish that patterns will persist.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.