Combinatorics and probability for trading (Part IV): Bernoulli Logic
In this article, I decided to highlight the well-known Bernoulli scheme and to show how it can be used to describe trading-related data arrays. All this will then be used to create a self-adapting trading system. We will also look for a more generic algorithm, a special case of which is the Bernoulli formula, and will find an application for it.
Learn how to design a trading system by Standard Deviation
Here is a new article in our series about how to design a trading system by the most popular technical indicators in MetaTrader 5 trading platform. In this new article, we will learn how to design a trading system by Standard Deviation indicator.
Pair trading
In this article, we will consider pair trading, namely what its principles are and if there are any prospects for its practical application. We will also try to create a pair trading strategy.
Creating an MQL5 Expert Advisor Based on the Daily Range Breakout Strategy
In this article, we create an MQL5 Expert Advisor based on the Daily Range Breakout strategy. We cover the strategy’s key concepts, design the EA blueprint, and implement the breakout logic in MQL5. In the end, we explore techniques for backtesting and optimizing the EA to maximize its effectiveness.
Developing a trading Expert Advisor from scratch (Part 19): New order system (II)
In this article, we will develop a graphical order system of the "look what happens" type. Please note that we are not starting from scratch this time, but we will modify the existing system by adding more objects and events on the chart of the asset we are trading.
Controlling the Slope of Balance Curve During Work of an Expert Advisor
Finding rules for a trade system and programming them in an Expert Advisor is a half of the job. Somehow, you need to correct the operation of the Expert Advisor as it accumulates the results of trading. This article describes one of approaches, which allows improving performance of an Expert Advisor through creation of a feedback that measures slope of the balance curve.
Learn how to design a trading system by Williams PR
A new article in our series about learning how to design a trading system by the most popular technical indicators by MQL5 to be used in the MetaTrader 5. In this article, we will learn how to design a trading system by the Williams' %R indicator.
Learn how to design a trading system by OBV
This is a new article to continue our series for beginners about how to design a trading system based on some of the popular indicators. We will learn a new indicator that is On Balance Volume (OBV), and we will learn how we can use it and design a trading system based on it.
Trader-friendly stop loss and take profit
Stop loss and take profit can have a significant impact on trading results. In this article, we will look at several ways to find optimal stop order values.
Swaps (Part I): Locking and Synthetic Positions
In this article I will try to expand the classic concept of swap trading methods. I will explain why I have come to the conclusion that this concept deserves special attention and is absolutely recommended for study.
MQL5 Cookbook: Handling BookEvent
This article considers BookEvent - a Depth of Market event, and the principle of its processing. An MQL program, handling states of Depth of Market, serves as an example. It is written using the object-oriented approach. Results of handling are displayed on the screen as a panel and Depth of Market levels.
Combinatorics and probability theory for trading (Part II): Universal fractal
In this article, we will continue to study fractals and will pay special attention to summarizing all the material. To do this, I will try to bring all earlier developments into a compact form which would be convenient and understandable for practical application in trading.
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.
An Example of Developing a Spread Strategy for Moscow Exchange Futures
The MetaTrader 5 platform allows developing and testing trading robots that simultaneously trade multiple financial instruments. The built-in Strategy Tester automatically downloads required tick history from the broker's server taking into account contract specifications, so the developer does not need to do anything manually. This makes it possible to easily and reliably reproduce trading environment conditions, including even millisecond intervals between the arrival of ticks on different symbols. In this article we will demonstrate the development and testing of a spread strategy on two Moscow Exchange futures.
How to deal with lines using MQL5
In this article, you will find your way to deal with the most important lines like trendlines, support, and resistance by MQL5.
Learn how to design a trading system by Accelerator Oscillator
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.
Simple Mean Reversion Trading Strategy
Mean reversion is a type of contrarian trading where the trader expects the price to return to some form of equilibrium which is generally measured by a mean or another central tendency statistic.
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.
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.
A scientific approach to the development of trading algorithms
The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on these patterns. Development ideals are demonstrated using examples.
Combinatorics and probability for trading (Part V): Curve analysis
In this article, I decided to conduct a study related to the possibility of reducing multiple states to double-state systems. The main purpose of the article is to analyze and to come to useful conclusions that may help in the further development of scalable trading algorithms based on the probability theory. Of course, this topic involves mathematics. However, given the experience of previous articles, I see that generalized information is more useful than details.
Automating Trading Strategies in MQL5 (Part 24): London Session Breakout System with Risk Management and Trailing Stops
In this article, we develop a London Session Breakout System that identifies pre-London range breakouts and places pending orders with customizable trade types and risk settings. We incorporate features like trailing stops, risk-to-reward ratios, maximum drawdown limits, and a control panel for real-time monitoring and management.
Advantages of MQL5 Signals
Trading Signals service recently introduced in MetaTrader 5 allows traders to copy trading operations of any signals provider. Users can select any signal, subscribe to it and all deals will be copied at their accounts. Signals providers can set their subscription prices and receive a fixed monthly fee from their subscribers.
Automating Trading Strategies in MQL5 (Part 25): Trendline Trader with Least Squares Fit and Dynamic Signal Generation
In this article, we develop a trendline trader program that uses least squares fit to detect support and resistance trendlines, generating dynamic buy and sell signals based on price touches and open positions based on generated signals.
Drawing Indicator's Emissions in MQL5
In this article, we will consider the emission of indicators - a new approach to the market research. The calculation of emission is based on the intersection of different indicators: more and more points with different colors and shapes appear after each tick. They form numerous clusters like nebulae, clouds, tracks, lines, arcs, etc. These shapes help to detect the invisible springs and forces that affect the movement of market prices.
Neural networks made easy (Part 26): Reinforcement Learning
We continue to study machine learning methods. With this article, we begin another big topic, Reinforcement Learning. This approach allows the models to set up certain strategies for solving the problems. We can expect that this property of reinforcement learning will open up new horizons for building trading strategies.
Social Trading with the MetaTrader 4 and MetaTrader 5 Trading Platforms
What is social trading? It is a mutually beneficial cooperation of traders and investors whereby successful traders allow monitoring of their trading and potential investors take the opportunity to monitor their performance and copy trades of those who look more promising.
Everything you need to learn about the MQL5 program structure
Any Program in any programming language has a specific structure. In this article, you will learn essential parts of the MQL5 program structure by understanding the programming basics of every part of the MQL5 program structure that can be very helpful when creating our MQL5 trading system or trading tool that can be executable in the MetaTrader 5.
Automating Trading Strategies in MQL5 (Part 36): Supply and Demand Trading with Retest and Impulse Model
In this article, we create a supply and demand trading system in MQL5 that identifies supply and demand zones through consolidation ranges, validates them with impulsive moves, and trades retests with trend confirmation and customizable risk parameters. The system visualizes zones with dynamic labels and colors, supporting trailing stops for risk management.
Implementing a Bollinger Bands Trading Strategy with MQL5: A Step-by-Step Guide
A step-by-step guide to implementing an automated trading algorithm in MQL5 based on the Bollinger Bands trading strategy. A detailed tutorial based on creating an Expert Advisor that can be useful for traders.
Learn how to design a trading system by Bull's Power
Welcome to a new article in our series about learning how to design a trading system by the most popular technical indicator as we will learn in this article about a new technical indicator and how we can design a trading system by it and this indicator is the Bull's Power indicator.
Multiple indicators on one chart (Part 04): Advancing to an Expert Advisor
In my previous articles, I have explained how to create an indicator with multiple subwindows, which becomes interesting when using custom indicators. This time we will see how to add multiple windows to an Expert Advisor.
Multicurrency monitoring of trading signals (Part 3): Introducing search algorithms
In the previous article, we developed the visual part of the application, as well as the basic interaction of GUI elements. This time we are going to add internal logic and the algorithm of trading signal data preparation, as well us the ability to set up signals, to search them and to visualize them in the monitor.
Automating Trading Strategies in MQL5 (Part 16): Midnight Range Breakout with Break of Structure (BoS) Price Action
In this article, we automate the Midnight Range Breakout with Break of Structure strategy in MQL5, detailing code for breakout detection and trade execution. We define precise risk parameters for entries, stops, and profits. Backtesting and optimization are included for practical trading.
Automating Trading Strategies in MQL5 (Part 10): Developing the Trend Flat Momentum Strategy
In this article, we develop an Expert Advisor in MQL5 for the Trend Flat Momentum Strategy. We combine a two moving averages crossover with RSI and CCI momentum filters to generate trade signals. We also cover backtesting and potential enhancements for real-world performance.
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.
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
Building and testing Keltner Channel trading systems
In this article, we will try to provide trading systems using a very important concept in the financial market which is volatility. We will provide a trading system based on the Keltner Channel indicator after understanding it and how we can code it and how we can create a trading system based on a simple trading strategy and then test it on different assets.
Automating Trading Strategies in MQL5 (Part 3): The Zone Recovery RSI System for Dynamic Trade Management
In this article, we create a Zone Recovery RSI EA System in MQL5, using RSI signals to trigger trades and a recovery strategy to manage losses. We implement a "ZoneRecovery" class to automate trade entries, recovery logic, and position management. The article concludes with backtesting insights to optimize performance and enhance the EA’s effectiveness.
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.