Algorithmic Trading Articles — Guides & Examples

Automating Trading Strategies in MQL5 (Part 9): Building an Expert Advisor for the Asian Breakout Strategy

In this article, we build an Expert Advisor in MQL5 for the Asian Breakout Strategy by calculating the session's high and low and applying trend filtering with a moving average. We implement dynamic object styling, user-defined time inputs, and robust risk management. Finally, we demonstrate backtesting and optimization techniques to refine the program.

Automating Trading Strategies in MQL5 (Part 8): Building an Expert Advisor with Butterfly Harmonic Patterns

In this article, we build an MQL5 Expert Advisor to detect Butterfly harmonic patterns. We identify pivot points and validate Fibonacci levels to confirm the pattern. We then visualize the pattern on the chart and automatically execute trades when confirmed.

Neural Networks in Trading: Injection of Global Information into Independent Channels (InjectTST)

Most modern multimodal time series forecasting methods use the independent channels approach. This ignores the natural dependence of different channels of the same time series. Smart use of two approaches (independent and mixed channels) is the key to improving the performance of the models.

Neural Networks in Trading: Practical Results of the TEMPO Method

We continue our acquaintance with the TEMPO method. In this article we will evaluate the actual effectiveness of the proposed approaches on real historical data.

William Gann methods (Part I): Creating Gann Angles indicator

What is the essence of Gann Theory? How are Gann angles constructed? We will create Gann Angles indicator for MetaTrader 5.

Price Action Analysis Toolkit Development (Part 14): Parabolic Stop and Reverse Tool

Embracing technical indicators in price action analysis is a powerful approach. These indicators often highlight key levels of reversals and retracements, offering valuable insights into market dynamics. In this article, we demonstrate how we developed an automated tool that generates signals using the Parabolic SAR indicator.

Master MQL5 from beginner to pro (Part IV): About Arrays, Functions and Global Terminal Variables

The article is a continuation of the series for beginners. It covers in detail data arrays, the interaction of data and functions, as well as global terminal variables that allow data exchange between different MQL5 programs.

Animal Migration Optimization (AMO) algorithm

The article is devoted to the AMO algorithm, which models the seasonal migration of animals in search of optimal conditions for life and reproduction. The main features of AMO include the use of topological neighborhood and a probabilistic update mechanism, which makes it easy to implement and flexible for various optimization tasks.

Automating Trading Strategies in MQL5 (Part 7): Building a Grid Trading EA with Dynamic Lot Scaling

In this article, we build a grid trading expert advisor in MQL5 that uses dynamic lot scaling. We cover the strategy design, code implementation, and backtesting process. Finally, we share key insights and best practices for optimizing the automated trading system.

Price Action Analysis Toolkit Development (Part 13): RSI Sentinel Tool

Price action can be effectively analyzed by identifying divergences, with technical indicators such as the RSI providing crucial confirmation signals. In the article below, we explain how automated RSI divergence analysis can identify trend continuations and reversals, thereby offering valuable insights into market sentiment.

Developing a Replay System (Part 59): A New Future

Having a proper understanding of different ideas allows us to do more with less effort. In this article, we'll look at why it's necessary to configure a template before the service can interact with the chart. Also, what if we improve the mouse pointer so we can do more things with it?

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (II): Modularization

In this discussion, we take a step further in breaking down our MQL5 program into smaller, more manageable modules. These modular components will then be integrated into the main program, enhancing its organization and maintainability. This approach simplifies the structure of our main program and makes the individual components reusable in other Expert Advisors (EAs) and indicator developments. By adopting this modular design, we create a solid foundation for future enhancements, benefiting both our project and the broader developer community.

Custom Indicator: Plotting Partial Entry, Exit and Reversal Deals for Netting Accounts

In this article, we will look at a non-standard way of creating an indicator in MQL5. Instead of focusing on a trend or chart pattern, our goal will be to manage our own positions, including partial entries and exits. We will make extensive use of dynamic matrices and some trading functions related to trade history and open positions to indicate on the chart where these trades were made.

From Basic to Intermediate: Variables (III)

Today we will look at how to use predefined MQL5 language variables and constants. In addition, we will analyze another special type of variables: functions. Knowing how to properly work with these variables can mean the difference between an application that works and one that doesn't. In order to understand what is presented here, it is necessary to understand the material that was discussed in previous articles.

Deconstructing examples of trading strategies in the client terminal

The article uses block diagrams to examine the logic of the candlestick-based training EAs located in the Experts\Free Robots folder of the terminal.

Building a Keltner Channel Indicator with Custom Canvas Graphics in MQL5

In this article, we build a Keltner Channel indicator with custom canvas graphics in MQL5. We detail the integration of moving averages, ATR calculations, and enhanced chart visualization. We also cover backtesting to evaluate the indicator’s performance for practical trading insights.

Developing a Replay System (Part 57): Understanding a Test Service

One point to note: although the service code is not included in this article and will only be provided in the next one, I'll explain it since we'll be using that same code as a springboard for what we're actually developing. So, be attentive and patient. Wait for the next article, because every day everything becomes more interesting.

Cascade Order Trading Strategy Based on EMA Crossovers for MetaTrader 5

The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.

Neural Networks in Trading: Lightweight Models for Time Series Forecasting

Lightweight time series forecasting models achieve high performance using a minimum number of parameters. This, in turn, reduces the consumption of computing resources and speeds up decision-making. Despite being lightweight, such models achieve forecast quality comparable to more complex ones.

Automating Trading Strategies in MQL5 (Part 6): Mastering Order Block Detection for Smart Money Trading

In this article, we automate order block detection in MQL5 using pure price action analysis. We define order blocks, implement their detection, and integrate automated trade execution. Finally, we backtest the strategy to evaluate its performance.

Adaptive Social Behavior Optimization (ASBO): Two-phase evolution

We continue dwelling on the topic of social behavior of living organisms and its impact on the development of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will dive into the two-phase evolution, test the algorithm and draw conclusions. Just as in nature a group of living organisms join their efforts to survive, ASBO uses principles of collective behavior to solve complex optimization problems.

How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA

Smart Money Concept (Break Of Structure) coupled with the RSI Indicator to make informed automated trading decisions based on the market structure.

Creating a Trading Administrator Panel in MQL5 (Part IX): Code Organization (I)

This discussion delves into the challenges encountered when working with large codebases. We will explore the best practices for code organization in MQL5 and implement a practical approach to enhance the readability and scalability of our Trading Administrator Panel source code. Additionally, we aim to develop reusable code components that can potentially benefit other developers in their algorithm development. Read on and join the conversation.

Feature Engineering With Python And MQL5 (Part III): Angle Of Price (2) Polar Coordinates

In this article, we take our second attempt to convert the changes in price levels on any market, into a corresponding change in angle. This time around, we selected a more mathematically sophisticated approach than we selected in our first attempt, and the results we obtained suggest that our change in approach may have been the right decision. Join us today, as we discuss how we can use Polar coordinates to calculate the angle formed by changes in price levels, in a meaningful way, regardless of which market you are analyzing.

Developing a Replay System (Part 58): Returning to Work on the Service

After a break in development and improvement of the service used for replay/simulator, we are resuming work on it. Now that we've abandoned the use of resources like terminal globals, we'll have to completely restructure some parts of it. Don't worry, this process will be explained in detail so that everyone can follow the development of our service.

Neural Networks in Trading: Reducing Memory Consumption with Adam-mini Optimization

One of the directions for increasing the efficiency of the model training and convergence process is the improvement of optimization methods. Adam-mini is an adaptive optimization method designed to improve on the basic Adam algorithm.

Master MQL5 from Beginner to Pro (Part III): Complex Data Types and Include Files

This is the third article in a series describing the main aspects of MQL5 programming. This article covers complex data types that were not discussed in the previous article. These include structures, unions, classes, and the 'function' data type. It also explains how to add modularity to your program using the #include preprocessor directive.

Neural Networks in Trading: Spatio-Temporal Neural Network (STNN)

In this article we will talk about using space-time transformations to effectively predict upcoming price movement. To improve the numerical prediction accuracy in STNN, a continuous attention mechanism is proposed that allows the model to better consider important aspects of the data.

We provide a special installer for the MetaTrader 5 trading platform on macOS. It is a full-fledged wizard that allows you to install the application natively. The installer performs all the required steps: it identifies your system, downloads and installs the latest Wine version, configures it, and then installs MetaTrader within it. All steps are completed in the automated mode, and you can start using the platform immediately after installation.

Build Self Optimizing Expert Advisors in MQL5 (Part 5): Self Adapting Trading Rules

The best practices, defining how to safely us an indicator, are not always easy to follow. Quiet market conditions may surprisingly produce readings on the indicator that do not qualify as a trading signal, leading to missed opportunities for algorithmic traders. This article will suggest a potential solution to this problem, as we discuss how to build trading applications capable of adapting their trading rules to the available market data.

From Basic to Intermediate: Variables (II)

Today we will look at how to work with static variables. This question often confuses many programmers, both beginners and those with some experience, because there are several recommendations that must be followed when using this mechanism. The materials presented here are intended for didactic purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.

Chaos theory in trading (Part 2): Diving deeper

We continue our dive into chaos theory in financial markets. This time I will consider its applicability to the analysis of currencies and other assets.

Automating Trading Strategies in MQL5 (Part 5): Developing the Adaptive Crossover RSI Trading Suite Strategy

In this article, we develop the Adaptive Crossover RSI Trading Suite System, which uses 14- and 50-period moving average crossovers for signals, confirmed by a 14-period RSI filter. The system includes a trading day filter, signal arrows with annotations, and a real-time dashboard for monitoring. This approach ensures precision and adaptability in automated trading.

Neural Networks Made Easy (Part 97): Training Models With MSFformer

When exploring various model architecture designs, we often devote insufficient attention to the process of model training. In this article, I aim to address this gap.

Data Science and ML (Part 33): Pandas Dataframe in MQL5, Data Collection for ML Usage made easier

When working with machine learning models, it’s essential to ensure consistency in the data used for training, validation, and testing. In this article, we will create our own version of the Pandas library in MQL5 to ensure a unified approach for handling machine learning data, for ensuring the same data is applied inside and outside MQL5, where most of the training occurs.

Developing a multi-currency Expert Advisor (Part 16): Impact of different quote histories on test results

The EA under development is expected to show good results when trading with different brokers. But for now we have been using quotes from a MetaQuotes demo account to perform tests. Let's see if our EA is ready to work on a trading account with different quotes compared to those used during testing and optimization.

Automating Trading Strategies in MQL5 (Part 4): Building a Multi-Level Zone Recovery System

In this article, we develop a Multi-Level Zone Recovery System in MQL5 that utilizes RSI to generate trading signals. Each signal instance is dynamically added to an array structure, allowing the system to manage multiple signals simultaneously within the Zone Recovery logic. Through this approach, we demonstrate how to handle complex trade management scenarios effectively while maintaining a scalable and robust code design.

Generative Adversarial Networks (GANs) for Synthetic Data in Financial Modeling (Part 2): Creating Synthetic Symbol for Testing

In this article we are creating a synthetic symbol using a Generative Adversarial Network (GAN) involves generating realistic Financial data that mimics the behavior of actual market instruments, such as EURUSD. The GAN model learns patterns and volatility from historical market data and creates synthetic price data with similar characteristics.

Neural Network in Practice: Pseudoinverse (II)

Since these articles are educational in nature and are not intended to show the implementation of specific functionality, we will do things a little differently in this article. Instead of showing how to apply factorization to obtain the inverse of a matrix, we will focus on factorization of the pseudoinverse. The reason is that there is no point in showing how to get the general coefficient if we can do it in a special way. Even better, the reader can gain a deeper understanding of why things happen the way they do. So, let's now figure out why hardware is replacing software over time.

Mastering Log Records (Part 4): Saving logs to files

In this article, I will teach you basic file operations and how to configure a flexible handler for customization. We will update the CLogifyHandlerFile class to write logs directly to the file. We will conduct a performance test by simulating a strategy on EURUSD for a week, generating logs at each tick, with a total time of 5 minutes and 11 seconds. The result will be compared in a future article, where we will implement a caching system to improve performance.