MQL5 Algo Trading

Machine learning expanded retail signal generation, but by the early 2010s automated mining increased low-value, short-lived alphas. Scale created noise, limited explainability, and weak audit trails. In 2016, Zura Kakushadze proposed formulaic alphas: trading signals expressed…

Certain trading hours are measurably better than others, but generic session rules miss broker-specific behavior. This script quantifies hourly conditions using the broker’s own M1 history over the last N days. For each hour it calculates average movement (M1 high-low range…

Machine learning expanded retail signal generation, but by the early 2010s automated mining increased low-value, short-lived alphas. Scale created noise, limited explainability, and weak audit trails. In 2016, Zura Kakushadze proposed formulaic alphas: trading signals expressed…

Broker Execution Diagnostics MT5 is a read-only script that reports symbol constraints commonly linked to invalid volume, invalid stops, and inconsistent risk calculations. Output includes digits, point, tick size, tick value, current spread (points), min/max/step volume, and a…

SAGDFN targets spatio-temporal forecasting bottlenecks by reducing redundant edges early. Significant Neighbors Sampling builds a sparse neighborhood per node using similarity-ranked candidates plus random picks to preserve diversity and limit overfitting. Sparse Spatial…

Many lot size calculators hardcode pip value assumptions that break on gold, indices, JPY crosses, and non-USD account currencies. A sizing routine should use the tick and volume properties the trade server publishes per symbol, then compute risk from those inputs. CalcLots()…