Codes
Risk calculator for MT 5 for MetaTrader 5
The indicator calculates your risk as a percentage and gives you the lot size that is acceptable for your risk. You only need to specify the risk in per cent and the stop size in pips
Probability Theory Expert Advisor for Forex for MetaTrader 5
Probability Theory Advisor
Price / Volume indicator for MetaTrader 5
One of the simpler chips for machine learning
Advanced compound interest calculator for the trader for MetaTrader 5
A compound interest calculator for the trader. Calculates, based on your parameters, your risk of ruin, and the optimal risk per trade. Gives a forecast of your capital size in a year, month, and at the end of the term
Articles
Architecture for Collective Trading Decisions by AI Agents for MetaTrader 5
The article describes the architecture of a multi-agent trading system based on the grok-4-fast language model, in which, instead of a single system prompt, four independent analysts with fundamentally different roles operate: a bull, a bear, a risk manager, and an arbiter. Three analysts run in
How to Implement Competition Among LLM Agents in MetaTrader 5 for MetaTrader 5
The article describes a competitive architecture for MetaTrader 5 in which ten LLM agents, each with different trading rules, manage their own capital and open independent positions using unique magic numbers. The system prompt and the agent's trading aggressiveness are adjusted based on PnL results
How to Connect an LLM to an MQL5 Expert Advisor via a Python Server for MetaTrader 5
The article examines three key obstacles to integrating LLMs with MetaTrader 5: the lack of direct access, strict rate limits, and API key security given the architectural limitations of MQL5. A configuration is proposed that uses a local Python server as a bridge between the Expert Advisor and
LLM-Based Trading Agent with Embedded Top Trader Philosophy for MetaTrader 5
The article provides a critical analysis of an LLM strategy in which forecasting the direction is separated from trading decisions, and demonstrates why this leads to a disconnect between metrics and PnL. We will describe procedures for dataset balancing, feature engineering, prompt and response
Development and Forward Testing of an Autonomous LLM Agent for Trading with SEAL for MetaTrader 5
A hybrid architecture based on Llama 3.2 and SEAL is being tested on eight currency pairs (M15), with forward-period data isolation and information leakage control. The methodology combines adversarial self-play, curriculum learning, and class balancing to ensure stable training. The experiments
How to Create and Adapt an RL Agent with an LLM and Quantum Encoding for Algorithmic Trading in MQL5 for MetaTrader 5
The article proposes a hybrid approach to algorithmic trading based on quantum encoding of market states, Double DQN with a prioritized experience replay buffer, and an LLM acting as a contextual EA. The SEAL methodology enables asynchronous continued training of the agent without halting trading. A
Implementing a Continuous LLM Adaptation System for Algorithmic Trading for MetaTrader 5
SEAL (Self-Evolving Adaptive Learning) is a system for the continuous adaptation of large language models (LLMs) for algorithmic trading, designed to address the problem of rapid model degradation in changing markets. Instead of periodic retraining, which takes hours and erases old patterns, SEAL
Bidirectional LSTM and Quantum Computing for Predicting the Direction of Price Movement for MetaTrader 5
The article presents a reproducible implementation of a hybrid quantum-neural network model for algorithmic trading on Forex without using real quantum hardware. A fixed three-qubit quantum circuit in IBM Qiskit converts sliding-window statistics (mean returns, volatility, and range) into a
Combining 3D Bars, Quantum Computing, and Machine Learning into a Unified Trading System for MetaTrader 5
The article presents the full integration of the 3D-bar module into a quantum-enhanced trading system for forecasting the movement of currency pairs. The system combines stationary four-dimensional features, an 8-qubit quantum encoder, and CatBoost gradient boosting with 52+ features. The system is
Combining LLM, CatBoost, and Quantum Computing into a Unified Trading System for MetaTrader 5
The article proposes a synthesis of new technologies to overcome the limitations of classical indicators in market data analytics. It shows how language models and quantum encoding can reveal hidden market patterns that traditional methods overlook. The experiment confirms the value of new