Algorithmic Trading Articles for Expert advisors

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.

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.

Building A Candlestick Trend Constraint Model(Part 3): Detecting changes in trends while using this system

This article explores how economic news releases, investor behavior, and various factors can influence market trend reversals. It includes a video explanation and proceeds by incorporating MQL5 code into our program to detect trend reversals, alert us, and take appropriate actions based on market conditions. This builds upon previous articles in the series.

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.

Implementing the Deus EA: Automated Trading with RSI and Moving Averages in MQL5

This article outlines the steps to implement the Deus EA based on the RSI and Moving Average indicators for guiding automated trading.

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.

MQL5 Wizard Techniques you should know (Part 41): Deep-Q-Networks

The Deep-Q-Network is a reinforcement learning algorithm that engages neural networks in projecting the next Q-value and ideal action during the training process of a machine learning module. We have already considered an alternative reinforcement learning algorithm, Q-Learning. This article therefore presents another example of how an MLP trained with reinforcement learning, can be used within a custom signal class.

MQL5 Wizard Techniques you should know (Part 31): Selecting the Loss Function

Loss Function is the key metric of machine learning algorithms that provides feedback to the training process by quantifying how well a given set of parameters are performing when compared to their intended target. We explore the various formats of this function in an MQL5 custom wizard class.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 1): Sending Messages from MQL5 to Telegram

In this article, we create an Expert Advisor (EA) in MQL5 to send messages to Telegram using a bot. We set up the necessary parameters, including the bot's API token and chat ID, and then perform an HTTP POST request to deliver the messages. Later, we handle the response to ensure successful delivery and troubleshoot any issues that arise in case of failure. This ensures we send messages from MQL5 to Telegram via the created bot.

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.

Developing a multi-currency Expert Advisor (Part 11): Automating the optimization (first steps)

To get a good EA, we need to select multiple good sets of parameters of trading strategy instances for it. This can be done manually by running optimization on different symbols and then selecting the best results. But it is better to delegate this work to the program and engage in more productive activities.

MQL5 Wizard Techniques you should know (Part 29): Continuation on Learning Rates with MLPs

We wrap up our look at learning rate sensitivity to the performance of Expert Advisors by primarily examining the Adaptive Learning Rates. These learning rates aim to be customized for each parameter in a layer during the training process and so we assess potential benefits vs the expected performance toll.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 7): Command Analysis for Indicator Automation on Charts

In this article, we explore how to integrate Telegram commands with MQL5 to automate the addition of indicators on trading charts. We cover the process of parsing user commands, executing them in MQL5, and testing the system to ensure smooth indicator-based trading

Neural Networks Made Easy (Part 88): Time-Series Dense Encoder (TiDE)

In an attempt to obtain the most accurate forecasts, researchers often complicate forecasting models. Which in turn leads to increased model training and maintenance costs. Is such an increase always justified? This article introduces an algorithm that uses the simplicity and speed of linear models and demonstrates results on par with the best models with a more complex architecture.

Introduction to MQL5 (Part 7): Beginner's Guide to Building Expert Advisors and Utilizing AI-Generated Code in MQL5

Discover the ultimate beginner's guide to building Expert Advisors (EAs) with MQL5 in our comprehensive article. Learn step-by-step how to construct EAs using pseudocode and harness the power of AI-generated code. Whether you're new to algorithmic trading or seeking to enhance your skills, this guide provides a clear path to creating effective EAs.

MQL5 Trading Toolkit (Part 2): Expanding and Implementing the Positions Management EX5 Library

Learn how to import and use EX5 libraries in your MQL5 code or projects. In this continuation article, we will expand the EX5 library by adding more position management functions to the existing library and creating two Expert Advisors. The first example will use the Variable Index Dynamic Average Technical Indicator to develop a trailing stop trading strategy expert advisor, while the second example will utilize a trade panel to monitor, open, close, and modify positions. These two examples will demonstrate how to use and implement the upgraded EX5 position management library.

MQL5 Wizard Techniques you should know (Part 40): Parabolic SAR

The Parabolic Stop-and-Reversal (SAR) is an indicator for trend confirmation and trend termination points. Because it is a laggard in identifying trends its primary purpose has been in positioning trailing stop losses on open positions. We, however, explore if indeed it could be used as an Expert Advisor signal, thanks to custom signal classes of wizard assembled Expert Advisors.

Learn how to trade the Fair Value Gap (FVG)/Imbalances step-by-step: A Smart Money concept approach

A step-by-step guide to creating and implementing an automated trading algorithm in MQL5 based on the Fair Value Gap (FVG) trading strategy. A detailed tutorial on creating an expert advisor that can be useful for both beginners and experienced traders.

MQL5 Wizard Techniques you should know (Part 39): Relative Strength Index

The RSI is a popular momentum oscillator that measures pace and size of a security’s recent price change to evaluate over-and-under valued situations in the security’s price. These insights in speed and magnitude are key in defining reversal points. We put this oscillator to work in another custom signal class and examine the traits of some of its signals. We start, though, by wrapping up what we started previously on Bollinger Bands.

Neural Networks Made Easy (Part 87): Time Series Patching

Forecasting plays an important role in time series analysis. In the new article, we will talk about the benefits of time series patching.

Developing a multi-currency Expert Advisor (Part 9): Collecting optimization results for single trading strategy instances

Let's outline the main stages of the EA development. One of the first things to be done will be to optimize a single instance of the developed trading strategy. Let's try to collect all the necessary information about the tester passes during the optimization in one place.

Developing a multi-currency Expert Advisor (Part 10): Creating objects from a string

The EA development plan includes several stages with intermediate results being saved in the database. They can only be retrieved from there again as strings or numbers, not objects. So we need a way to recreate the desired objects in the EA from the strings read from the database.

Neural Networks Made Easy (Part 84): Reversible Normalization (RevIN)

We already know that pre-processing of the input data plays a major role in the stability of model training. To process "raw" input data online, we often use a batch normalization layer. But sometimes we need a reverse procedure. In this article, we discuss one of the possible approaches to solving this problem.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 6): Adding Responsive Inline Buttons

In this article, we integrate interactive inline buttons into an MQL5 Expert Advisor, allowing real-time control via Telegram. Each button press triggers specific actions and sends responses back to the user. We also modularize functions for handling Telegram messages and callback queries efficiently.

MQL5 Wizard Techniques you should know (Part 38): Bollinger Bands

Bollinger Bands are a very common Envelope Indicator used by a lot of traders to manually place and close trades. We examine this indicator by considering as many of the different possible signals it does generate, and see how they could be put to use in a wizard assembled Expert Advisor.

MQL5 Wizard Techniques you should know (Part 17): Multicurrency Trading

Trading across multiple currencies is not available by default when an expert advisor is assembled via the wizard. We examine 2 possible hacks traders can make when looking to test their ideas off more than one symbol at a time.

Creating a Trading Administrator Panel in MQL5 (Part II): Enhancing Responsiveness and Quick Messaging

In this article, we will enhance the responsiveness of the Admin Panel that we previously created. Additionally, we will explore the significance of quick messaging in the context of trading signals.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 5): Sending Commands from Telegram to MQL5 and Receiving Real-Time Responses

In this article, we create several classes to facilitate real-time communication between MQL5 and Telegram. We focus on retrieving commands from Telegram, decoding and interpreting them, and sending appropriate responses back. By the end, we ensure that these interactions are effectively tested and operational within the trading environment

Developing an Expert Advisor (EA) based on the Consolidation Range Breakout strategy in MQL5

This article outlines the steps to create an Expert Advisor (EA) that capitalizes on price breakouts after consolidation periods. By identifying consolidation ranges and setting breakout levels, traders can automate their trading decisions based on this strategy. The Expert Advisor aims to provide clear entry and exit points while avoiding false breakouts

Neural Networks Made Easy (Part 86): U-Shaped Transformer

We continue to study timeseries forecasting algorithms. In this article, we will discuss another method: the U-shaped Transformer.

Creating an Interactive Graphical User Interface in MQL5 (Part 2): Adding Controls and Responsiveness

Enhancing the MQL5 GUI panel with dynamic features can significantly improve the trading experience for users. By incorporating interactive elements, hover effects, and real-time data updates, the panel becomes a powerful tool for modern traders.

Neural Networks Made Easy (Part 85): Multivariate Time Series Forecasting

In this article, I would like to introduce you to a new complex timeseries forecasting method, which harmoniously combines the advantages of linear models and transformers.

Neural Networks Made Easy (Part 83): The "Conformer" Spatio-Temporal Continuous Attention Transformer Algorithm

This article introduces the Conformer algorithm originally developed for the purpose of weather forecasting, which in terms of variability and capriciousness can be compared to financial markets. Conformer is a complex method. It combines the advantages of attention models and ordinary differential equations.

Creating an MQL5-Telegram Integrated Expert Advisor (Part 4): Modularizing Code Functions for Enhanced Reusability

In this article, we refactor the existing code used for sending messages and screenshots from MQL5 to Telegram by organizing it into reusable, modular functions. This will streamline the process, allowing for more efficient execution and easier code management across multiple instances.

MQL5 Wizard Techniques you should know (Part 26): Moving Averages and the Hurst Exponent

The Hurst Exponent is a measure of how much a time series auto-correlates over the long term. It is understood to be capturing the long-term properties of a time series and therefore carries some weight in time series analysis even outside of economic/ financial time series. We however, focus on its potential benefit to traders by examining how this metric could be paired with moving averages to build a potentially robust signal.

Gain an Edge Over Any Market (Part III): Visa Spending Index

In the world of big data, there are millions of alternative datasets that hold the potential to enhance our trading strategies. In this series of articles, we will help you identify the most informative public datasets.

MQL5 Wizard Techniques you should know (Part 32): Regularization

Regularization is a form of penalizing the loss function in proportion to the discrete weighting applied throughout the various layers of a neural network. We look at the significance, for some of the various regularization forms, this can have in test runs with a wizard assembled Expert Advisor.

MQL5 Wizard Techniques you should know (Part 34): Price-Embedding with an Unconventional RBM

Restricted Boltzmann Machines are a form of neural network that was developed in the mid 1980s at a time when compute resources were prohibitively expensive. At its onset, it relied on Gibbs Sampling and Contrastive Divergence in order to reduce dimensionality or capture the hidden probabilities/properties over input training data sets. We examine how Backpropagation can perform similarly when the RBM ‘embeds’ prices for a forecasting Multi-Layer-Perceptron.

Reimagining Classic Strategies (Part VI): Multiple Time-Frame Analysis

In this series of articles, we revisit classic strategies to see if we can improve them using AI. In today's article, we will examine the popular strategy of multiple time-frame analysis to judge if the strategy would be enhanced with AI.

Neural networks made easy (Part 80): Graph Transformer Generative Adversarial Model (GTGAN)

In this article, I will get acquainted with the GTGAN algorithm, which was introduced in January 2024 to solve complex problems of generation architectural layouts with graph constraints.