Articles on machine learning in trading
Creating AI-based trading robots: native integration with Python, matrices and vectors, math and statistics libraries and much more.
Find out how to use machine learning in trading. Neurons, perceptrons, convolutional and recurrent networks, predictive models — start with the basics and work your way up to developing your own AI. You will learn how to train and apply neural networks for algorithmic trading in financial markets.
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Neural Networks in Trading: Iterative Forecast Refinement Models (Conclusion)
Introducing the RAFT framework — a powerful tool for analyzing and forecasting financial time series. Its flexible and optimized architecture ensures accurate forecasts, stable performance, and faster data processing. RAFT reduces the risk of errors and makes it easier to create effective trading strategies.
How to Train an MLP Using Markov Chain Features in MQL5
The article describes the two-level MarkovMLPOscillator indicator: a three-state Markov chain uses historical data to construct a transition matrix and generate 15 probabilistic features for each bar, and an MLP is trained on these features to predict price direction at a specified forecast horizon. The article covers feature generation, the validation procedure using a holdout set, and parameter settings. The result is an interpretable oscillator with a color histogram, a smoothed signal, and a display of the current transition matrix.
Optimal Trade Exit in MQL5: Longstaff-Schwartz Least-Squares Monte Carlo for Continuation-Value Estimation
This article models position exits as an American option and implements the Longstaff–Schwartz least‑squares Monte Carlo in native MQL5. The engine calibrates drift and volatility from recent returns, simulates forward price paths, and uses backward induction to compare immediate exercise to continuation. It integrates into an EA with hard time and price backstops and a live indicator, and is tested on four symbol/timeframe combinations with mixed, reproducible Strategy Tester results.