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How to Create an Interactive MQL5 Dashboard/Panel Using the Controls Class (Part 1): Setting Up the Panel
How to Create an Interactive MQL5 Dashboard/Panel Using the Controls Class (Part 1): Setting Up the Panel
In this article, we create an interactive trading dashboard using the Controls class in MQL5, designed to streamline trading operations. The panel features a title, navigation buttons for Trade, Close, and Information, and specialized action buttons for executing trades and managing positions. By the end of the article, you will have a foundational panel ready for further enhancements in future installments.
Data Science and ML (Part 31): Using CatBoost AI Models for Trading
Data Science and ML (Part 31): Using CatBoost AI Models for Trading
CatBoost AI models have gained massive popularity recently among machine learning communities due to their predictive accuracy, efficiency, and robustness to scattered and difficult datasets. In this article, we are going to discuss in detail how to implement these types of models in an attempt to beat the forex market.
Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs(I)-Fine-tuning
Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs(I)-Fine-tuning
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager
Developing a multi-currency Expert Advisor (Part 12): Developing prop trading level risk manager
In the EA being developed, we already have a certain mechanism for controlling drawdown. But it is probabilistic in nature, as it is based on the results of testing on historical price data. Therefore, the drawdown can sometimes exceed the maximum expected values (although with a small probability). Let's try to add a mechanism that ensures guaranteed compliance with the specified drawdown level.
How to create a trading journal with MetaTrader and Google Sheets
How to create a trading journal with MetaTrader and Google Sheets
Create a trading journal using MetaTrader and Google Sheets! You will learn how to sync your trading data via HTTP POST and retrieve it using HTTP requests. In the end, You have a trading journal that will help you keep track of your trades effectively and efficiently.
Risk manager for algorithmic trading
Risk manager for algorithmic trading
The objectives of this article are to prove the necessity of using a risk manager and to implement the principles of controlled risk in algorithmic trading in a separate class, so that everyone can verify the effectiveness of the risk standardization approach in intraday trading and investing in financial markets. In this article, we will create a risk manager class for algorithmic trading. This is a logical continuation of the previous article in which we discussed the creation of a risk manager for manual trading.
Introduction to MQL5 (Part 6): A Beginner's Guide to Array Functions in MQL5 (II)
Introduction to MQL5 (Part 6): A Beginner's Guide to Array Functions in MQL5 (II)
Embark on the next phase of our MQL5 journey. In this insightful and beginner-friendly article, we'll look into the remaining array functions, demystifying complex concepts to empower you to craft efficient trading strategies. We’ll be discussing ArrayPrint, ArrayInsert, ArraySize, ArrayRange, ArrarRemove, ArraySwap, ArrayReverse, and ArraySort. Elevate your algorithmic trading expertise with these essential array functions. Join us on the path to MQL5 mastery!
Risk manager for manual trading
Risk manager for manual trading
In this article we will discuss in detail how to write a risk manager class for manual trading from scratch. This class can also be used as a base class for inheritance by algorithmic traders who use automated programs.
Example of Auto Optimized Take Profits and Indicator Parameters with SMA and EMA
Example of Auto Optimized Take Profits and Indicator Parameters with SMA and EMA
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 also significant drawdowns, indicating potential for further refinement.
Data Science and ML (Part 28): Predicting Multiple Futures for EURUSD, Using AI
Data Science and ML (Part 28): Predicting Multiple Futures for EURUSD, Using AI
It is a common practice for many Artificial Intelligence models to predict a single future value. However, in this article, we will delve into the powerful technique of using machine learning models to predict multiple future values. This approach, known as multistep forecasting, allows us to predict not only tomorrow's closing price but also the day after tomorrow's and beyond. By mastering multistep forecasting, traders and data scientists can gain deeper insights and make more informed decisions, significantly enhancing their predictive capabilities and strategic planning.
MQL5 Wizard Techniques you should know (Part 23): CNNs
MQL5 Wizard Techniques you should know (Part 23): CNNs
Convolutional Neural Networks are another machine learning algorithm that tend to specialize in decomposing multi-dimensioned data sets into key constituent parts. We look at how this is typically achieved and explore a possible application for traders in another MQL5 wizard signal class.
Developing Zone Recovery Martingale strategy in MQL5
Developing Zone Recovery Martingale strategy in MQL5
The article discusses, in a detailed perspective, the steps that need to be implemented towards the creation of an expert advisor based on the Zone Recovery trading algorithm. This helps aotomate the system saving time for algotraders.
Practicing the development of trading strategies
Practicing the development of trading strategies
In this article, we will make an attempt to develop our own trading strategy. Any trading strategy must be based on some kind of statistical advantage. Moreover, this advantage should exist for a long time.
Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part II)
Building A Candlestick Trend Constraint Model (Part 5): Notification System (Part II)
Today, we are discussing a working Telegram integration for MetaTrader 5 Indicator notifications using the power of MQL5, in partnership with Python and the Telegram Bot API. We will explain everything in detail so that no one misses any point. By the end of this project, you will have gained valuable insights to apply in your projects.
Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU
Integrate Your Own LLM into EA (Part 4): Training Your Own LLM with GPU
With the rapid development of artificial intelligence today, language models (LLMs) are an important part of artificial intelligence, so we should think about how to integrate powerful LLMs into our algorithmic trading. For most people, it is difficult to fine-tune these powerful models according to their needs, deploy them locally, and then apply them to algorithmic trading. This series of articles will take a step-by-step approach to achieve this goal.
Building A Candlestick Trend Constraint Model (Part 7): Refining our model for EA development
Building A Candlestick Trend Constraint Model (Part 7): Refining our model for EA development
In this article, we will delve into the detailed preparation of our indicator for Expert Advisor (EA) development. Our discussion will encompass further refinements to the current version of the indicator to enhance its accuracy and functionality. Additionally, we will introduce new features that mark exit points, addressing a limitation of the previous version, which only identified entry points.
Creating an Interactive Graphical User Interface in MQL5 (Part 1): Making the Panel
Creating an Interactive Graphical User Interface in MQL5 (Part 1): Making the Panel
This article explores the fundamental steps in crafting and implementing a Graphical User Interface (GUI) panel using MetaQuotes Language 5 (MQL5). Custom utility panels enhance user interaction in trading by simplifying common tasks and visualizing essential trading information. By creating custom panels, traders can streamline their workflow and save time during trading operations.
Triangular arbitrage with predictions
Triangular arbitrage with predictions
This article simplifies triangular arbitrage, showing you how to use predictions and specialized software to trade currencies smarter, even if you're new to the market. Ready to trade with expertise?
MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library
MQL5 Trading Toolkit (Part 1): Developing A Positions Management EX5 Library
Learn how to create a developer's toolkit for managing various position operations with MQL5. In this article, I will demonstrate how to create a library of functions (ex5) that will perform simple to advanced position management operations, including automatic handling and reporting of the different errors that arise when dealing with position management tasks with MQL5.
Creating Time Series Predictions using LSTM Neural Networks: Normalizing Price and Tokenizing Time
Creating Time Series Predictions using LSTM Neural Networks: Normalizing Price and Tokenizing Time
This article outlines a simple strategy for normalizing the market data using the daily range and training a neural network to enhance market predictions. The developed models may be used in conjunction with an existing technical analysis frameworks or on a standalone basis to assist in predicting the overall market direction. The framework outlined in this article may be further refined by any technical analyst to develop models suitable for both manual and automated trading strategies.
Balancing risk when trading multiple instruments simultaneously
Balancing risk when trading multiple instruments simultaneously
This article will allow a beginner to write an implementation of a script from scratch for balancing risks when trading multiple instruments simultaneously. Besides, it may give experienced users new ideas for implementing their solutions in relation to the options proposed in this article.
A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy
A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy
A comprehensive guide to developing an automated trading algorithm based on the Break of Structure (BoS) strategy. Detailed information on all aspects of creating an advisor in MQL5 and testing it in MetaTrader 5 — from analyzing price support and resistance to risk management