Curates advanced publications for algorithmic traders and developers, featuring MQL5 implementations of machine learning models, optimization algorithms, and technical indicators. Content spans high-performance computing for trading (OpenCL, GPU acceleration), risk management systems for prop trading, statistical validation methods to prevent overfitting, and practical Expert Advisor development. The channel bridges academic quantitative finance with production-ready code, covering order flow analysis, supply/demand automation, and hybrid Python-MQL5 workflows for modern automated trading.
developers, quantitative traders, algotraders
tutorials, technical analysis, code implementations, educational
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MetaQuotes has once again demonstrated its leadership in creating innovative solutions for the financial industry. At the Forex Expo Dubai 2025, held on October 6–7, the company received two prestigio…
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DADA targets time-series anomalies in markets without retraining per instrument by avoiding fixed autoencoder compression and learning robust structure via masked reconstruction. Its core is an adapt…
Part 8 folds the Optuna HPO system into the production training stack, resulting in one ModelDevelopmentPipeline that can run either sklearn search (Grid/RandomizedSearchCV) or Optuna via a single mod…
Battle Royale Optimizer (BRO) is a game-inspired metaheuristic that reframes population search as competition rather than cooperation. Each candidate solution “duels” its nearest neighbor; the better…
Part 9 builds a footprint order-flow indicator in MQL5 to expose what candlesticks hide: traded volume at each price level inside every bar, split into bid (selling) and ask (buying), plus per-level d…
Automated S/R tools often treat zones as static objects, creating analysis gaps after breakouts. A common case is resistance breaking on a strong bullish close, followed by a retest where the same lev…