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
CFTC Data Mining in Python and Building an AI Model for MetaTrader 5
Let's try mining CFTC data, downloading COT and TFF reports via Python, connecting all this with MetaTrader 5 quotes and an AI model, and get forecasts. What are COT reports in the Forex market? How to use COT and TFF reports for forecasting
Mining Central Bank Balance Sheet Data to Get a Picture of Global Liquidity for MetaTrader 5
Mining central bank balance sheet data provides a picture of global liquidity in the Forex market and key currencies. We combine data from the Fed, ECB, BOJ and PBoC into a composite index and use machine learning to uncover hidden patterns. This approach turns raw data into real trading signals by
CAPM Model Indicator for the Forex Market for MetaTrader 5
Adaptation of the classical CAPM model for the Forex currency market in MQL5. The indicator calculates expected return and risk premium based on historical volatility. The indicators rise at peaks and bottoms, reflecting the fundamental principles of pricing. Practical application for counter-trend
ARIMA Forecasting Indicator in MQL5 for MetaTrader 5
In this article we are implementing ARIMA forecasting indicator in MQL5. It examines how the ARIMA model generates forecasts, its applicability to the Forex market and the stock market in general. It also explains what AR autoregression is, how autoregressive models are used for forecasting, and how
Self-Learning Expert Advisor with a Neural Network Based on a Markov State-Transition Matrix for MetaTrader 5
Self-training EA with a neural network based on a state matrix. We combine Markov chains with a multilayer neural network MLP developed using the ALGLIB MQL5 library. How can Markov chains and neural networks be combined for Forex forecasting
Markov Chain-Based Matrix Forecasting Model for MetaTrader 5
We are going to create a matrix forecasting model based on a Markov chain. What are Markov chains, and how can we use a Markov chain for Forex trading
Integrating Computer Vision into Trading in MQL5 (Part 2): Extending the Architecture to 2D RGB Image Analysis for MetaTrader 5
Computer vision for trading: how it works and how to develop it step by step. We create an algorithm for recognition of RGB images of price charts using the attention mechanism and a bidirectional LSTM layer. As a result, we obtain a working model for forecasting the EURUSD price with the accuracy
Quantitative Analysis of Trends: Collecting Statistics in Python for MetaTrader 5
What is quantitative trend analysis in the Forex market? We collect statistics on trends, their magnitude and distribution across the EURUSD currency pair. How quantitative trend analysis can help you create a profitable trading expert advisor
Forex Arbitrage Trading: A Matrix Trading System for Return to Fair Value with Risk Control for MetaTrader 5
The article contains a detailed description of the cross-rate calculation algorithm, a visualization of the imbalance matrix, and recommendations for optimally setting the MinDiscrepancy and MaxRisk parameters for efficient trading. The system automatically calculates the "fair value" of each
Integrating Computer Vision into Trading in MQL5 (Part 1): Creating Basic Functions for MetaTrader 5
The EURUSD forecasting system with the use of computer vision and deep learning. Learn how convolutional neural networks can recognize complex price patterns in the foreign exchange market and predict exchange rate movements with up to 54% accuracy. The article shares the methodology for creating an