Articles on the MQL5 programming and use of technical indicators

In this article, we will learn about Bollinger Bands which is one of the most popular indicators in the trading world. We will consider technical analysis and see how to design an algorithmic trading system based on the Bollinger Bands indicator.

The article describes the Fibo levels-based trading system developed by Joe DiNapoli. The idea behind the system and the main concepts are explained, as well as a simple indicator is provided as an example for more clarity.

Automation of trading strategies involving graphical patterns requires the ability to search for extreme points on the charts for further processing and interpretation. Existing tools do not always provide such an ability. The algorithms described in the article allow finding all extreme points on charts. The tools discussed here are equally efficient both during trends and flat movements. The obtained results are not strongly affected by a selected timeframe and are only defined by a specified scale.

In this article, we will consider the creation of two indicators: the tick indicator, which plots the tick chart of the price and tick candle indicator, which plot candles with the specified number of ticks. Each of the indicators writes the incoming prices into a file, and uses the saved data after the restart of the indicator (these data also can be used by the other programs)

This article is dedicated to the Three Line Break chart, suggested by Steve Nison in his book "Beyond Candlesticks". The greatest advantage of this chart is that it allows filtering minor fluctuations of a price in relation to the previous movement. We are going to discuss the principle of the chart construction, the code of the indicator and some examples of trading strategies based on it.

This article will describe advanced adaptive indicators and their implementation in MQL5: Adaptive Cyber Cycle, Adaptive Center of Gravity and Adaptive RVI. All indicators were originally presented in "Cybernetic Analysis for Stocks and Futures" by John F. Ehlers.

Support Vector Machines have long been used in fields such as bioinformatics and applied mathematics to assess complex data sets and extract useful patterns that can be used to classify data. This article looks at what a support vector machine is, how they work and why they can be so useful in extracting complex patterns. We then investigate how they can be applied to the market and potentially used to advise on trades. Using the Support Vector Machine Learning Tool, the article provides worked examples that allow readers to experiment with their own trading.

In the previous article, we considered application of Merrill patterns to various data, such as to a price value on a currency symbol chart and values of standard MetaTrader 5 indicators: ATR, WPR, CCI, RSI, among others. Now, let us try to create a strategy construction set based on Merrill patterns.

In this article, we start the development of the indicator buffer classes for the DoEasy library. We will create the base class of the abstract buffer which is to be used as a foundation for the development of different class types of indicator buffers.

A time series is a dynamic system, in which values of a random variable are received continuously or at successive equally spaced points in time. Transition from 2D to 3D market analysis provides a new look at complex processes and research objects. The article describes visualization methods providing 3D representation of two-dimensional data.

The article deals with the algorithm of developing stock indicators based on real volumes using the CopyTicks() and CopyTicksRange() functions. Some subtle aspects of developing such indicators, as well as their operation in real time and in the strategy tester are also described.

In this article, I will tell you how to successfully trade by merging a very well-known strategy and a neural network. It will be about the Thomas DeMark's Sequential strategy with the use of an artificial intelligence system. Only the first part of the strategy will be applied, using the Setup and Intersection signals.

Most of traders agree that the current market state analysis starts with the evaluation of higher chart timeframes. The analysis is performed downwards to lower timeframes until the one, at which deals are performed. This analysis method seems to be a mandatory part of professional approach for successful trading. In this article, we will discuss multi-timeframe indicators and their creation ways, as well as we will provide MQL5 code examples. In addition to the general evaluation of advantages and disadvantages, we will propose a new indicator approach using the MTF mode.

The article describes how to implement Interprocess Communication between MetaTrader 5 client terminals using named pipes. For the use of the named pipes, the CNamedPipes class is developed. For the test of its use and to measure the connection throughput, the tick indicator, the server and client scripts are presented. The use of named pipes is sufficient for real-time quotes.

Scalping automatic systems are rightfully regarded the pinnacle of algorithmic trading, but at the same time their code is the most difficult to write. In this article we will show how to build strategies based on analysis of incoming ticks using the built-in debugging tools and visual testing. Developing rules for entry and exit often require years of manual trading. But with the help of MetaTrader 5, you can quickly test any such strategy on real history.

The article demonstrates the development of the ZigZag indicator in accordance with one of the sample specifications described in the article "How to prepare Requirements Specification when ordering an indicator". The indicator is built by extreme values defined using an oscillator. There is an ability to use one of five oscillators: WPR, CCI, Chaikin, RSI or Stochastic Oscillator.

In this article we are going to show how to explore the Standard Library of Trading Strategy Classes and how to add Custom Strategies and Filters/Signals using the Patterns-and-Models logic of the MQL5 Wizard. In the end you will be able easily add your own strategies using MetaTrader 5 standard indicators, and MQL5 Wizard will create a clean and powerful code and fully functional Expert Advisor.

In MQL5 you can write an indicator both from a scratch and on the basis of another already existing indicator, in-built in the client terminal or a custom one. And here you also have two ways - to improve an indicator by adding new calculations and graphical styles to it , or to use an indicator in-built in the client terminal or a custom one via the iCustom() or IndicatorCreate() functions.

In the following article I am describing a process of implementing Moving Mini-Max indicator based on a paper by Z.G.Silagadze 'Moving Mini-max: a new indicator for technical analysis'. The idea of the indicator is based on simulation of quantum tunneling phenomena, proposed by G. Gamov in the theory of alpha decay.

Automate the collection of interest rate data to improve the performance of an Expert Advisor.

When developing trading algorithms, we often encounter a problem: how to determine where a trend/flat begins and ends? In this article, we try to create a universal indicator, in which we try to combine signals for different types of strategies. We will try to simplify the process of obtaining trade signals in an expert as much as possible. An example of combining several indicators in one will be given.

When writing an indicator that uses the short form of the OnCalculate() function call, you might miss the fact that an indicator can be calculated not only by price data, but also by data of some other indicator (no matter whether it is a built-in or custom one). Do you want to improve an indicator for its correct application to the other indicator's data? In this article we'll review all the steps required for such modification.

In this article, we will learn a new tool from our series: we will learn how to design a trading system based on one of the most popular technical indicators Moving Average Convergence Divergence (MACD).

In this article, we will consider popular candlestick patterns and will try to find out if they are still relevant and effective in today's markets. Candlestick analysis appeared more than 20 years ago and has since become quite popular. Many traders consider Japanese candlesticks the most convenient and easily understandable asset price visualization form.

This article presents Pivot Mean Oscillator (PMO), an implementation of the cumulative moving average (CMA) as a trading indicator for the MetaTrader platforms. In particular, we first introduce Pivot Mean (PM) as a normalization index for timeseries that computes the fraction between any data point and the CMA. We then build PMO as the difference between the moving averages applied to two PM signals. Some preliminary experiments carried out on the EURUSD symbol to test the efficacy of the proposed indicator are also reported, leaving ample space for further considerations and improvements.

This article deals with the theory and practical application of the algorithm for forecasting time series, based on support-vector method. It also proposes its implementation in MQL and provides test indicators and Expert Advisors. This technology has not been implemented in MQL yet. But first, we have to get to know math for it.

The article discusses the possibility of plotting statistical distribution histograms of market conditions with the help of the graphical memory meaning no indicator buffers and arrays are applied. Sample histograms are described in details and the "hidden" functionality of MQL5 graphical objects is shown.

There are 6 drawing styles in MQL4 and 18 drawing styles in MQL5. Therefore, it may be worth writing an article to introduce MQL5's drawing styles. In this article, we will consider the details of drawing styles in MQL5. In addition, we will create an indicator to demonstrate how to use these drawing styles, and refine the plotting.

For a long time multi-currency analysis and multi-currency trading has been of interest to people. The opportunity to implement a full fledged multi-currency regime became possible only with the public release of MetaTrader 5 and the MQL5 programming language. In this article we propose a way to analyze and process all incoming ticks for several symbols. As an illustration, let's consider a multi-currency RSI indicator of the USDx dollar index.

There are many strategies that can be used to filter generated signals based on any strategy, even by using the moving average itself which is the subject of this article. So, the objective of this article is to share with you some of Moving Average Strategies and how to design an algorithmic trading system.

In the previous article, we created the application framework, which we will use as the basis for all further work. In this part, we will proceed with the development: we will create the visual part of the application and will configure basic interaction of interface elements.

This is the first article in a series, in which I am going to describe a toolkit which enables manual application of chart graphics by utilizing keyboard shortcuts. It is very convenient: you press one key and a trendline appears, you press another key — this will create a Fibonacci fan with the necessary parameters. It will also be possible to switch timeframes, to rearrange layers or to delete all objects from the chart.

The article dwells on gaps — significant differences between a close price of a previous timeframe and an open price of the next one, as well as on forecasting a daily bar direction. Applying the GetOpenFileName function by the system DLL is considered as well.

This is the must read article for anyone wanting to improve their programming career. This article series is aimed at making you the best programmer you can possibly be, no matter how experienced you are. The discussed ideas work for MQL5 programming newbies as well as professionals.

The trade Signals service develops in leaps and bounds. Trusting our funds to a signal provider, we would like to minimize the risk of losing our deposit. So how to puzzle out in this forest of trade signals? How to find the one that would produce profits? This paper proposes to create a tool for visually analyzing the history of trades on trade signals in a symbol chart.

In this article, we will discuss the idea of creating a multicurrency monitor of trading signals and will develop a future application structure along with its prototype, as well as create its framework for further operation. The article presents a step-by-step creation of a flexible multicurrency application which will enable the generation of trading signals and which will assist traders in finding the desired signals.

On the occasion of the MQL5 Freelance Service fourth birthday, we have prepared an info-graphic demonstrating the service results for the entire time of its existence. The figures speak for themselves: more than 10 000 orders worth about $600,000 in total have been executed to date, while 3 000 customers and 300 developers have already used the service.