Automating MetaTrader 5 Trading Reports with an MQL5 and Python Workflow
Summary
The article presents a workflow for turning MetaTrader 5 trade history into scheduled reports. An MQL5 Expert Advisor exports filtered trading data to CSV, uses timer events to schedule the process, and invokes a Python script to calculate summary statistics and create a portable report. The proposed setup also covers logging, error handling, file cleanup, environment checks, and optional notifications. Alongside implementation details, it explains report measures such as returns, drawdown, trade activity, Sharpe and profit factors, recovery, excursions, symbol-level outcomes, and time-based patterns.
The evidence is an implementation blueprint and attached components described as exporting recent history, computing selected analytics, producing a PDF, and checking for report creation; the supplied excerpt does not provide a performance study of a trading strategy. The workflow depends on configuring MetaTrader 5 and Python, and on external script execution and delivery settings. Report statistics can support review and behavioral adjustments, but they describe past trading and do not by themselves establish future results.
Key ideas
- An Expert Advisor can export trade history while Python processes the data into a report.
- Timer events provide a way to schedule recurring exports from within MetaTrader 5.
- Trading reports can summarize returns, drawdowns, costs, trade behavior, and symbol-level results.
- Separating data export from report generation makes each part easier to maintain.
- The article describes a reporting workflow, not evidence that any trading strategy is profitable.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.