Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network
Neural networks are an ultimate tool in traders' toolkit. Let's check if this assumption is true. MetaTrader 5 is approached as a self-sufficient medium for using neural networks in trading. A simple explanation is provided.
Creating an EA that works automatically (Part 12): Automation (IV)
If you think automated systems are simple, then you probably don't fully understand what it takes to create them. In this article, we will talk about the problem that kills a lot of Expert Advisors. The indiscriminate triggering of orders is a possible solution to this problem.
How to create a custom True Strength Index indicator using MQL5
Here is a new article about how to create a custom indicator. This time we will work with the True Strength Index (TSI) and will create an Expert Advisor based on it.
Creating an EA that works automatically (Part 11): Automation (III)
An automated system will not be successful without proper security. However, security will not be ensured without a good understanding of certain things. In this article, we will explore why achieving maximum security in automated systems is such a challenge.
Creating an EA that works automatically (Part 10): Automation (II)
Automation means nothing if you cannot control its schedule. No worker can be efficient working 24 hours a day. However, many believe that an automated system should operate 24 hours a day. But it is always good to have means to set a working time range for the EA. In this article, we will consider how to properly set such a time range.
Creating an EA that works automatically (Part 09): Automation (I)
Although the creation of an automated EA is not a very difficult task, however, many mistakes can be made without the necessary knowledge. In this article, we will look at how to build the first level of automation, which consists in creating a trigger to activate breakeven and a trailing stop level.
Experiments with neural networks (Part 4): Templates
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. Simple explanation.
How to create a custom indicator (Heiken Ashi) using MQL5
In this article, we will learn how to create a custom indicator using MQL5 based on our preferences, to be used in MetaTrader 5 to help us read charts or to be used in automated Expert Advisors.
Neural networks made easy (Part 36): Relational Reinforcement Learning
In the reinforcement learning models we discussed in previous article, we used various variants of convolutional networks that are able to identify various objects in the original data. The main advantage of convolutional networks is the ability to identify objects regardless of their location. At the same time, convolutional networks do not always perform well when there are various deformations of objects and noise. These are the issues which the relational model can solve.
How to detect trends and chart patterns using MQL5
In this article, we will provide a method to detect price actions patterns automatically by MQL5, like trends (Uptrend, Downtrend, Sideways), Chart patterns (Double Tops, Double Bottoms).
Category Theory in MQL5 (Part 6): Monomorphic Pull-Backs and Epimorphic Push-Outs
Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.
Backpropagation Neural Networks using MQL5 Matrices
The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.
Alan Andrews and his methods of time series analysis
Alan Andrews is one of the most famous "educators" of the modern world in the field of trading. His "pitchfork" is included in almost all modern quote analysis programs. But most traders do not use even a fraction of the opportunities that this tool provides. Besides, Andrews' original training course includes a description not only of the pitchfork (although it remains the main tool), but also of some other useful constructions. The article provides an insight into the marvelous chart analysis methods that Andrews taught in his original course. Beware, there will be a lot of images.
How to use MQL5 to detect candlesticks patterns
A new article to learn how to detect candlesticks patterns on prices automatically by MQL5.
Moral expectation in trading
This article is about moral expectation. We will look at several examples of its use in trading, as well as the results that can be achieved with its help.
Neural networks made easy (Part 35): Intrinsic Curiosity Module
We continue to study reinforcement learning algorithms. All the algorithms we have considered so far required the creation of a reward policy to enable the agent to evaluate each of its actions at each transition from one system state to another. However, this approach is rather artificial. In practice, there is some time lag between an action and a reward. In this article, we will get acquainted with a model training algorithm which can work with various time delays from the action to the reward.
Creating a comprehensive Owl trading strategy
My strategy is based on the classic trading fundamentals and the refinement of indicators that are widely used in all types of markets. This is a ready-made tool allowing you to follow the proposed new profitable trading strategy.
Creating an EA that works automatically (Part 08): OnTradeTransaction
In this article, we will see how to use the event handling system to quickly and efficiently process issues related to the order system. With this system the EA will work faster, so that it will not have to constantly search for the required data.
Data Science and Machine Learning(Part 14): Finding Your Way in the Markets with Kohonen Maps
Are you looking for a cutting-edge approach to trading that can help you navigate complex and ever-changing markets? Look no further than Kohonen maps, an innovative form of artificial neural networks that can help you uncover hidden patterns and trends in market data. In this article, we'll explore how Kohonen maps work, and how they can be used to develop smarter, more effective trading strategies. Whether you're a seasoned trader or just starting out, you won't want to miss this exciting new approach to trading.
Testing and optimization of binary options strategies in MetaTrader 5
In this article, I will check and optimize binary options strategies in MetaTrader 5.
Learn how to design a trading system by Fibonacci
In this article, we will continue our series of creating a trading system based on the most popular technical indicator. Here is a new technical tool which is the Fibonacci and we will learn how to design a trading system based on this technical indicator.
Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)
Revolutionize your financial market analysis with Principal Component Analysis (PCA)! Discover how this powerful technique can unlock hidden patterns in your data, uncover latent market trends, and optimize your investment strategies. In this article, we explore how PCA can provide a new lens for analyzing complex financial data, revealing insights that would be missed by traditional approaches. Find out how applying PCA to financial market data can give you a competitive edge and help you stay ahead of the curve
Creating an EA that works automatically (Part 07): Account types (II)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. The trader should always be aware of what the automatic EA is doing, so that if it "goes off the rails", the trader could remove it from the chart as soon as possible and take control of the situation.
Neural networks made easy (Part 33): Quantile regression in distributed Q-learning
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.
Creating an EA that works automatically (Part 06): Account types (I)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.
Data Science and Machine Learning (Part 11): Naïve Bayes, Probability theory in Trading
Trading with probability is like walking on a tightrope - it requires precision, balance, and a keen understanding of risk. In the world of trading, the probability is everything. It's the difference between success and failure, profit and loss. By leveraging the power of probability, traders can make informed decisions, manage risk effectively, and achieve their financial goals. So, whether you're a seasoned investor or a novice trader, understanding probability is the key to unlocking your trading potential. In this article, we'll explore the exciting world of trading with probability and show you how to take your trading game to the next level.
Learn how to design a trading system by Bill Williams' MFI
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).
Revisiting Murray system
Graphical price analysis systems are deservedly popular among traders. In this article, I am going to describe the complete Murray system, including its famous levels, as well as some other useful techniques for assessing the current price position and making a trading decision.
Creating an EA that works automatically (Part 05): Manual triggers (II)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. At the end of the previous article, I suggested that it would be appropriate to allow manual use of the EA, at least for a while.
Creating an EA that works automatically (Part 04): Manual triggers (I)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode.
Creating an EA that works automatically (Part 03): New functions
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we started to develop an order system that we will use in our automated EA. However, we have created only one of the necessary functions.
Creating an EA that works automatically (Part 02): Getting started with the code
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. In the previous article, we discussed the first steps that anyone needs to understand before proceeding to creating an Expert Advisor that trades automatically. We considered the concepts and the structure.
How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot
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.
Develop a Proof-of-Concept DLL with C++ multi-threading support for MetaTrader 5 on Linux
We will begin the journey to explore the steps and workflow on how to base development for MetaTrader 5 platform solely on Linux system in which the final product works seamlessly on both Windows and Linux system. We will get to know Wine, and Mingw; both are the essential tools to make cross-platform development works. Especially Mingw for its threading implementations (POSIX, and Win32) that we need to consider in choosing which one to go with. We then build a proof-of-concept DLL and consume it in MQL5 code, finally compare the performance of both threading implementations. All for your foundation to expand further on your own. You should be comfortable building MT related tools on Linux after reading this article.
MQL5 Wizard techniques you should know (Part 05): Markov Chains
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.
Learn how to design a trading system by Gator Oscillator
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.
Neural networks made easy (Part 32): Distributed Q-Learning
We got acquainted with the Q-learning method in one of the earlier articles within this series. This method averages rewards for each action. Two works were presented in 2017, which show greater success when studying the reward distribution function. Let's consider the possibility of using such technology to solve our problems.
Developing a trading Expert Advisor from scratch (Part 31): Towards the future (IV)
We continue to remove separate parts from our EA. This is the last article within this series. And the last thing to be removed is the sound system. This can be a bit confusing if you haven't followed these article series.
Magic of time trading intervals with Frames Analyzer tool
What is Frames Analyzer? This is a plug-in module for any Expert Advisor for analyzing optimization frames during parameter optimization in the strategy tester, as well as outside the tester, by reading an MQD file or a database that is created immediately after parameter optimization. You will be able to share these optimization results with other users who have the Frames Analyzer tool to discuss the results together.
Neural networks made easy (Part 31): Evolutionary algorithms
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.