Articles on manual and algorithmic trading in MetaTrader 5

In the first part of the article, I have described a modified ZigZag indicator and a class for receiving data of that type of indicators. Here, I will show how to develop indicators based on these tools and write an EA for tests that features making deals according to signals formed by ZigZag indicator. As an addition, the article will introduce a new version of the EasyAndFast library for developing graphical user interfaces.

In this article, I will share with you one of the methods of how to trade bands. This time we will consider Envelopes and will see how easy it is to create some strategies based on the Envelopes.

We continue our discussion of the patterns traders can come across while trading currency baskets. In this part, we will consider the patterns formed when using combined trend indicators. Indicators based on a currency index are to be used as the analytical tool.

Random Walk looks very similar to the real market data, but it has some significant features. In this article we will consider the properties of Random Walk, simulated using the coin-tossing game. To study the properties of the data, the trendiness indicator is developed.

The article deals with a simple approach to creating an automated trading system based on the chart linear markup and offers a ready-made Expert Advisor using the standard properties of the MetaTrader 4 and 5 objects and supporting the main trading operations.

Today, many traders switch to automated trading systems which can require additional setup or can be fully automated and ready to use. However, there is a considerable part of traders who prefer trading manually, in the old fashioned way. In this article, we will create toolkit for quick manual trading, using hotkeys, and for performing typical trading actions in one click.

In this article, we continue our learning series — this time we will learn how to design a trading system using one of the most popular and useful indicators, which is the Stochastic Oscillator indicator, to build a new block in our knowledge of basics.

In this article, we create a Breaker Block Trading System in MQL5 that identifies consolidation ranges, detects breakouts, and validates breaker blocks with swing points to trade retests with defined risk parameters. The system visualizes order and breaker blocks with dynamic labels and arrows, supporting automated trading and trailing stops.

In this new article from our series for learning how to design trading systems, I will present the Commodities Channel Index (CCI), explain its specifics, and share with you how to create a trading system based on this indicator.

In this article, we will fiddle around ChatGPT from OpenAI in order to understand its capabilities in terms of reducing the time and labor intensity of developing Expert Advisors, indicators and scripts. I will quickly navigate you through this technology and try to show you how to use it correctly for programming in MQL4 and MQL5.

In this article, we will expand the capabilities of the toolkit: we will add the ability to close trade positions upon specific conditions and will create tables for controlling market and pending orders, with the ability to edit these orders.

In this article, we create an Inverse Fair Value Gap (IFVG) detection system in MQL5 that identifies bullish/bearish FVGs on recent bars with minimum gap size filtering, tracks their states as normal/mitigated/inverted based on price interactions (mitigation on far-side breaks, retracement on re-entry, inversion on close beyond far side from inside), and ignores overlaps while limiting tracked FVGs.

The article discusses the methods for building and training ensembles of neural networks with bagging structure. It also determines the peculiarities of hyperparameter optimization for individual neural network classifiers that make up the ensemble. The quality of the optimized neural network obtained in the previous article of the series is compared with the quality of the created ensemble of neural networks. Possibilities of further improving the quality of the ensemble's classification are considered.

Analysis of the trade history and plotting distribution charts of trading results in HTML depending on position entry time. The charts are displayed in three sections - by hours, by days of the week and by months.

In this article, we build an MQL5 Expert Advisor for Fibonacci retracement trading, using either daily candle ranges or lookback arrays to calculate custom levels like 50% and 61.8% for entries, determining bullish or bearish setups based on close vs. open. The system triggers buys or sells on price crossings of levels with max trades per level, optional closure on new Fib calcs, points-based trailing stops after a min profit threshold, and SL/TP buffers as percentages of the range.

The article proposes Kagi chart indicator with various charting options and additional functions. Also, indicator charting principle and its MQL5 implementation features are considered. The most popular cases of its implementation in trading are displayed - Yin/Yang exchange strategy, pushing away from the trend line and consistently increasing "shoulders"/decreasing "waists".

Surfing the Internet, it is easy to find many strategies, which will give you a number of various recommendations. Let’s take an insider’s approach and look into the process of strategy creation, based on the differences in timezones on different continents.

The article is devoted to the practical application of the fuzzy logic concept for financial markets analysis. We propose the example of the indicator generating signals based on two fuzzy rules based on Envelopes indicator. The developed indicator uses several indicator buffers: 7 buffers for calculations, 5 buffers for the charts display and 2 color buffers.

The article describes how to create a framework for the online analysis of multidimensional data (OLAP), as well as how to implement this in MQL and to apply such analysis in the MetaTrader environment using the example of trading account history processing.

It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.

Learn how to automate Larry Williams market structure concepts in MQL5 by building a complete Expert Advisor that reads swing points, generates trade signals, manages risk, and applies a dynamic trailing stop strategy.

In my previous article, I mentioned the importance of identifying the trend which is the direction of prices. In this article I will share one of the most important concepts and indicators which is the Momentum indicator. I will share how to design a trading system based on this Momentum indicator.

The scope of use of fractional differentiation is wide enough. For example, a differentiated series is usually input into machine learning algorithms. The problem is that it is necessary to display new data in accordance with the available history, which the machine learning model can recognize. In this article we will consider an original approach to time series differentiation. The article additionally contains an example of a self optimizing trading system based on a received differentiated series.

This is the last article within the series devoted to the Reversing trading strategy. Here we will try to solve the problem, which caused the testing results instability in previous articles. We will also develop and test our own algorithm for manual trading in any market using the reversing strategy.

Determing the broker offset and GMT automatically. Instead of asking the support of your broker, from whom you will probably receive an insufficient answer (who would be willing to explain a missing hour), we simply look ourselves how they time their prices in the weeks of the time changes — but not cumbersome by hand, we let a program do it — why do we have a PC after all.

In this part, we expand the trading signal searching and editing system, as well as introduce the possibility to use custom indicators and add program localization. We have previously created a basic system for searching signals, but it was based on a small set of indicators and a simple set of search rules.

Many traders on Moscow Exchange would like to automate their trading algorithms, but they do not know where to start. The MQL5 language offers a huge range of trading functions, and it additionally provides ready classes that help users to make their first steps in algo trading.

In this article, we will develop a grider EA for trading in a trend direction within a range. Thus, the EA is to be suited mostly for Forex and commodity markets. According to the tests, our grider showed profit since 2018. Unfortunately, this is not true for the period of 2014-2018.

I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated profitable trading on completely different instruments traded on fundamentally different markets.