Makaleler
Using PSAR, Heiken Ashi, and Deep Learning Together for Trading MetaTrader 5 için
This project explores the fusion of deep learning and technical analysis to test trading strategies in forex. A Python script is used for rapid experimentation, employing an ONNX model alongside traditional indicators like PSAR, SMA, and RSI to predict EUR/USD movements. A MetaTrader 5 script then
Example of CNA (Causality Network Analysis), SMOC (Stochastic Model Optimal Control) and Nash Game Theory with Deep Learning MetaTrader 5 için
We will add Deep Learning to those three examples that were published in previous articles and compare results with previous. The aim is to learn how to add DL to other EA
How to Implement Auto Optimization in MQL5 Expert Advisors MetaTrader 5 için
Step by step guide for auto optimization in MQL5 for Expert Advisors. We will cover robust optimization logic, best practices for parameter selection, and how to reconstruct strategies with back-testing. Additionally, higher-level methods like walk-forward optimization will be discussed to enhance
Example of Stochastic Optimization and Optimal Control MetaTrader 5 için
This Expert Advisor, named SMOC (likely standing for Stochastic Model Optimal Control), is a simple example of an advanced algorithmic trading system for MetaTrader 5. It uses a combination of technical indicators, model predictive control, and dynamic risk management to make trading decisions. The
Example of Causality Network Analysis (CNA) and Vector Auto-Regression Model for Market Event Prediction MetaTrader 5 için
This article presents a comprehensive guide to implementing a sophisticated trading system using Causality Network Analysis (CNA) and Vector Autoregression (VAR) in MQL5. It covers the theoretical background of these methods, provides detailed explanations of key functions in the trading algorithm
Application of Nash's Game Theory with HMM Filtering in Trading MetaTrader 5 için
This article delves into the application of John Nash's game theory, specifically the Nash Equilibrium, in trading. It discusses how traders can utilize Python scripts and MetaTrader 5 to identify and exploit market inefficiencies using Nash's principles. The article provides a step-by-step guide on
Example of Auto Optimized Take Profits and Indicator Parameters with SMA and EMA MetaTrader 5 için
This article presents a sophisticated Expert Advisor for forex trading, combining machine learning with technical analysis. It focuses on trading Apple stock, featuring adaptive optimization, risk management, and multiple strategies. Backtesting shows promising results with high profitability but
Twitter Sentiment Analysis with Sockets MetaTrader 5 için
This innovative trading bot integrates MetaTrader 5 with Python to leverage real-time social media sentiment analysis for automated trading decisions. By analyzing Twitter sentiment related to specific financial instruments, the bot translates social media trends into actionable trading signals. It
Portfolio Optimization in Python and MQL5 MetaTrader 5 için
This article explores advanced portfolio optimization techniques using Python and MQL5 with MetaTrader 5. It demonstrates how to develop algorithms for data analysis, asset allocation, and trading signal generation, emphasizing the importance of data-driven decision-making in modern financial
Sentiment Analysis and Deep Learning for Trading with EA and Backtesting with Python MetaTrader 5 için
In this article, we will introduce Sentiment Analysis and ONNX Models with Python to be used in an EA. One script runs a trained ONNX model from TensorFlow for deep learning predictions, while another fetches news headlines and quantifies sentiment using AI