AlgoScore analyzes six deeper dimensions behind every strategy and compresses them into one score you can understand instantly.
From raw data to final score in five transparent steps.
Daily returns and account statistics pulled from verified Myfxbook track records via API every day at 01:00 UTC.
Six risk-adjusted metrics computed across two time windows: all-time and recent (365 days).
Ljung-Box significance testing on autocorrelation. Penalties applied only when statistically confirmed (p < 0.05).
Bayesian-inspired shrinkage toward neutral for short records. Longer proven history rewarded with diminishing returns. This produces the v1.2 engine score.
Up to three transparent multipliers — cash-flow/true-TWR, grid/martingale and scalability — correct for risks automation and Myfxbook can't see. The result is then mapped onto a fixed, percentile-anchored display scale (never changing the ranking) to produce the published score.
Each metric targets a different weakness that simple returns can't reveal.
Measures return relative to downside deviation only. Unlike the Sharpe ratio, upside volatility is not penalized, making it ideal for trend-following or momentum strategies.
Annualized return divided by maximum drawdown. Answers a direct question: how much return does this strategy generate per unit of worst-case loss?
Captures both the depth and duration of drawdowns from the equity peak. A strategy that stays underwater for months scores worse than one that recovers quickly.
Detects left-tail fat in the return distribution. Strategies with occasional large losses hidden behind steady small gains will show elevated negative skewness.
Tests for serial dependency in weekly returns using the Ljung-Box statistic. High autocorrelation can indicate grid trading, martingale layering, or artificial equity smoothing.
Measures persistent floating losses relative to account balance. Catches strategies that hold losing positions open for extended periods to avoid realizing losses on the equity curve.
The six metrics produce the automated v1.2 engine score. On top of it, up to three transparent multipliers correct for risks that automation and Myfxbook can't see — raw score = engine score × cash-flow × grid/martingale × scalability. Manual multipliers are only ever 1.00 or a value between 0.50 and 0.80, and every applied penalty is shown with its reason on each strategy's detail page. Finally, the raw score is expressed on a calibrated display scale anchored to the retail EA population — a fixed, strictly increasing mapping that makes the numbers intuitive (a median retail EA reads about 70) without ever changing how strategies rank.
A single engine score from four weighted components, before the manual overlay is applied.
AlgoScore ranges indicate the overall quality of a strategy.