Discussing the article: "Building a Hidden Risk of Ruin Auditor in MQL5"

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Aggregate metrics alone do not reveal how a trade sequence manages risk. This MQL5 tool analyzes closed positions to flag four structural patterns: post-loss volume escalation, overlapping same-direction entries, asymmetric payoffs, and a classical risk-of-ruin figure. The results are merged into a configurable A-F grade with concise recommendations to guide further review.

An equity curve answers "what happened to the balance." It cannot answer, "What would have happened if the losing streak had been one trade longer?" A martingale sequence that doubles in size after every loss looks identical to a disciplined strategy for as long as it continues to double until it wins, not just once. A grid that averages into a losing move looks identical to normal trading for as long as the price eventually reverses. The statistics computed from the closed trades—win rate, profit factor, and maximum drawdown—describe the sample that survived. They say nothing about how close that sample came to not surviving because the mechanism that generated the trades is invisible once you only look at the outcomes.

The four dimensions presented in this article look at the mechanism instead of the outcome: how size changes after a loss, whether positions stack at worsening prices, whether wins and losses are lopsided, and what classical ruin mathematics says about the observed win rate and payoff ratio. A track record can look clean on every aggregate number and still fail two of these four checks. The built-in demonstration in this article is built to show exactly that case.

Author: Cristian David Castillo Arrieta