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Trading Journal Analytics for Behavior, Performance, and Ruin Risk

Article MQL5 code base
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Summary

This product description outlines a trading-performance journal that combines trade review, behavioral monitoring, and statistical risk analysis. It describes a calendar that color-codes winning and losing days, plus diagnostics intended to flag behaviors such as revenge trades, fear-of-missing-out entries, panic exits, and widening a stop after entry. Performance measures include Sharpe, Sortino, Calmar, Ulcer Index, and System Quality Number, calculated separately for long and short trades.

For forward-looking risk review, the journal resamples a trader’s historical trades to generate 1,000 Monte Carlo paths, estimate drawdown trajectories, and calculate risk of ruin. It also describes dividing computational work into scheduled chunks to keep the trading terminal responsive. These are feature claims rather than a worked analysis: the document gives no formulas, sample results, assumptions for resampling, or evidence that the behavioral flags are reliable. Estimates based on past trades may also fail to reflect future market conditions or changes in execution.

Key ideas

  • A trading journal can combine performance statistics with behavioral review.
  • The listed diagnostics aim to flag revenge trading, FOMO, panic exits, and weakened stop discipline.
  • Risk measures are calculated separately for long and short trade histories.
  • Bootstrap resampling of past trades is used to project drawdowns and estimate risk of ruin.
  • The description gives no validation results or details on the simulation assumptions.

Tags

Risk managementStatisticsBacktesting

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