Articles on the MQL5 programming and use of trading robots

We continue studying distributed Q-learning. Today we will look at this approach from the other side. We will consider the possibility of using quantile regression to solve price prediction tasks.

Are you tired of constantly trying to predict the stock market? Do you wish you had a crystal ball to help you make more informed investment decisions? Self-trained neural networks might be the solution you've been looking for. In this article, we explore whether these powerful algorithms can help you "ride the wave" and outsmart the stock market. By analyzing vast amounts of data and identifying patterns, self-trained neural networks can make predictions that are often more accurate than human traders. Discover how you can use this cutting-edge technology to maximize your profits and make smarter investment decisions.

This is a new article in the series in which we learn how to design a trading system based on popular technical indicators. This time we will cover Bill Williams' Market Facilitation Index (BW MFI).

In this article series, I use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 is approached as a self-sufficient tool for using neural networks in trading.

This article tries to answer the question: how can we choose the right expert advisors? Which are the best for our portfolio, and how can we filter the large trading bots list available on the market? This article will present twenty clear and strong criteria to reject an expert advisor. Each criterion will be presented and well explained to help you make a more sustained decision and build a more profitable expert advisor collection for your profits.

Markov chains are a powerful mathematical tool that can be used to model and forecast time series data in various fields, including finance. In financial time series modelling and forecasting, Markov chains are often used to model the evolution of financial assets over time, such as stock prices or exchange rates. One of the main advantages of Markov chain models is their simplicity and ease of use.

A new article in our series about learning how to design a trading system based on popular technical indicators will be about the Gator Oscillator technical indicator and how to create a trading system through simple strategies.

In the previous article, we started exploring non-gradient optimization methods. We got acquainted with the genetic algorithm. Today, we will continue this topic and will consider another class of evolutionary algorithms.

Today I want to introduce you to a slightly different learning method. We can say that it is borrowed from Darwin's theory of evolution. It is probably less controllable than the previously discussed methods but it allows training non-differentiable models.

In this article, we will learn how to make the MetaTrader 5 platform talk. What if we make the EA more fun? Financial market trading is often too boring and monotonous, but we can make this job less tiring. Please note that this project can be dangerous for those who experience problems such as addiction. However, in a general case, it just makes things less boring.

In this article, you will find your way to deal with the most important lines like trendlines, support, and resistance by MQL5.

In the last two articles, we developed a tool for creating and editing neural network models. Now it is time to evaluate the potential use of Transfer Learning technology using practical examples.

There is still one task which our order system is not up to, but we will FINALLY figure it out. The MetaTrader 5 provides a system of tickets which allows creating and correcting order values. The idea is to have an Expert Advisor that would make the same ticket system faster and more efficient.

In the previous article, we created a tool for creating and editing the architecture of neural networks. Today we will continue working on this tool. We will try to make it more user friendly. This may see, top be a step away form our topic. But don't you think that a well organized workspace plays an important role in achieving the result.

Data mining is crucial to a data scientist and a trader because very often, the data isn't as straightforward as we think it is. The human eye can not understand the minor underlying pattern and relationships in the dataset, maybe the K-means algorithm can help us with that. Let's find out...

This article is a new one from our series about how to design a trading system based on the most popular technical indicators. We will learn a new indicator which Fractals indicator and we will learn how to design a trading system based on it to be executed in the MetaTrader 5 terminal.

Let's move on to a more complete order system directly on the chart. In this article, I will show a way to fix the order system, or rather, to make it more intuitive.

Today we will take our order system to the next level. But before that, we need to solve a few problems. Now we have some questions that are related to how we want to work and what things we do during the trading day.

In this article, we will make the final step towards the EA's performance. So, be prepared for a long read. To make our Expert Advisor reliable, we will first remove everything from the code that is not part of the trading system.

In this article, we will make the system more reliable to ensure a robust and secure use. One of the ways to achieve the desired robustness is to try to re-use the code as much as possible so that it is constantly tested in different cases. But this is only one of the ways. Another one is to use OOP.

In this article, we'll complete our series about how to design a trading system based on the most popular technical indicator. We'll learn how to create a trading system based on the Alligator indicator.

We continue to study unsupervised learning algorithms. This time I suggest that we discuss the features of autoencoders when applied to recurrent model training.

In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading.

We will make the order system more flexible. Here we will consider changes to the code that will make it more flexible, which will allow us to change position stop levels much faster.

Today we will continue to develop the new order system. It is not that easy to implement a new system as we often encounter problems which greatly complicate the process. When these problems appear, we have to stop and re-analyze the direction in which we are moving.

We continue to study unsupervised learning algorithms. Some readers might have questions regarding the relevance of recent publications to the topic of neural networks. In this new article, we get back to studying neural networks.

A new article from our series about how to create simple trading systems by the most popular technical indicators. We will learn about a new one which is the Accelerator Oscillator indicator and we will learn how to design a trading system using it.