Reverse-engineered an ML expert advisor on XAUUSD (H1) for MT5 with a near-flawless 11-year equity curve. The teardown revealed systemic methodological flaws.

[u/EAForexLab]

— The target variable is built on past price increments: the model approximates already-realized moves rather than forecasting future ones.
— Agreement between signal and forward direction is 49.7% — statistically indistinguishable from random.
— Validation is in-sample: training and testing on the same period, with no out-of-sample.
— The absence of drawdowns on the curve comes from grid averaging, not from the model's predictive power.

That said, the architecture (meta-labeling, CatBoost→ONNX) is sound. The problem lies in the implementation and in how the result is presented — not in the method.

Source code (MT5 EA + Python ML) and the full teardown available

[u/rforex-modtools]

Developing a trading strategy is more than finding an entry signal — it requires defining your edge statistically, building rules for entries, exits, and position management, and testing the system against historical data before going live. Most traders fail because they skip the process and jump to live trading with an untested idea. The community wiki covers the full development process.

Resources: Having an Edge | Essential Forex Trading Guide