Articles on data analysis and statistics in MQL5

After we send a trading order to the server, we need to check the error codes or the absence of errors. In this article, we will consider handling errors returned by the trade server and prepare for creating pending trading requests.

In this article, we will consider the class of displaying text messages. Currently, we have a sufficient number of different text messages. It is time to re-arrange the methods of their storage, display and translation of Russian or English messages to other languages. Besides, it would be good to introduce convenient ways of adding new languages to the library and quickly switching between them.

After the upgrade of the MATLAB package in 2015, it is necessary to consider a modern way of creating DLL libraries. The article uses a sample predictive indicator to illustrate the peculiarities of linking MetaTrader 5 and MATLAB using modern 64-bit versions of the platforms, which are utilized nowadays. With the entire sequence of connecting MATLAB considered, MQL5 developers will be able to create applications with advanced computational capabilities much faster, avoiding «pitfalls».

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.

This is a continuation of the idea of processing and analysis of optimization results. This time, our purpose is to select the 100 best optimization results and display them in a GUI table. The user will be able to select a row in the optimization results table and receive a multi-symbol balance and drawdown graph on separate charts.

We continue the development of the library functionality featuring trading using pending requests. We have already implemented sending conditional trading requests for opening positions and placing pending orders. In the current article, we will implement conditional position closure – full, partial and closing by an opposite position.

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.

The article deals with the creation of a program allowing to estimate the kernel density of the unknown probability density function. Kernel Density Estimation method has been chosen for executing the task. The article contains source codes of the method software implementation, examples of its use and illustrations.

The article is intended to get its readers acquainted with the Box-Cox transformation. The issues concerning its usage are addressed and some examples are given allowing to evaluate the transformation efficiency with random sequences and real quotes.

Different situations happen in trader’s life. Often, the history of successful trades allows us to restore a strategy, while looking at a loss history we try to develop and improve it. In both cases, we compare trades with known indicators. This article suggests methods of batch comparison of trades with a number of indicators.

The article deals with the approaches enabling accurate simulation of walk forward optimization using the built-in tester and auxiliary libraries implemented in MQL.

In this article, we will continue the development of trading requests, implement placing pending orders and eliminate detected shortcomings of the trading class operation.

The article deals with the development of the timeseries collection of specified timeframes for all symbols used in the program. We are going to develop the timeseries collection, the methods of setting collection's timeseries parameters and the initial filling of developed timeseries with historical data.

In this article, we are going to finish the development of the base object of all library objects, so that any library object based on it is able to interact with a user. For example, users will be able to set the maximum acceptable size of a spread for opening a position and a price level, upon reaching which an event from a symbol object is sent to the program with the spread or price level-based signal.

The technical analysis widely implements the indicators showing the basic quotes "more clearly" and allowing traders to perform analysis and forecast market prices movement. It's quite obvious that there is no sense in using the indicators, let alone applying them in creation of trading systems, unless we can solve the issues concerning initial quotes transformation and the obtained result credibility. In this article we show that there are serious reasons for such a conclusion.

Studies related to search for the fractal behavior of financial data suggest that behind the seemingly chaotic behavior of economic time series there are hidden stable mechanisms of participants' collective behavior. These mechanisms can lead to the emergence of price dynamics on the exchange, which can define and describe specific properties of price series. When applied to trading, one could benefit from the indicators which can efficiently and reliably estimate the fractal parameters in the scale and time frame, which are relevant in practice.

In previous articles, we used stochastic gradient descent to train a neural network using the same learning rate for all neurons within the network. In this article, I propose to look towards adaptive learning methods which enable changing of the learning rate for each neuron. We will also consider the pros and cons of this approach.

In this article, we will have a look at the handler of invalid trading order parameters and improve the trading event class. Now all trading events (both single ones and the ones occurred simultaneously within one tick) will be defined in programs correctly.

This is the next article within the series, in which I show how I created a convenient library for manual application of chart graphics by utilizing keyboard shortcuts. The tools used include straight lines and their combinations. In this part, we will view how the drawing tools are applied using the functions described in the first part. The library can be connected to any Expert Advisor or indicator which will greatly simplify the charting tasks. This solution DOES NOT use external dlls, while all the commands are implemented using built-in MQL tools.

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.

We continue studying the world of neural networks. In this article, we will consider another type of neural networks, recurrent networks. This type is proposed for use with time series, which are represented in the MetaTrader 5 trading platform by price charts.

The article provides an overview of the terminal's capabilities for creating and working with custom symbols, offers options for simulating a trading history using custom symbols, trend and various chart patterns.

Trading is always about making decisions in the face of uncertainty. This means that the results of the decisions are not quite obvious at the time these decisions are made. This entails the importance of theoretical approaches to the construction of mathematical models allowing us to describe such cases in meaningful manner.

In this article we will continue dealing with the OLAP technology applied to trading. We will expand the functionality presented in the first two articles. This time we will consider the operational analysis of quotes. We will put forward and test the hypotheses on trading strategies based on aggregated historical data. The article presents Expert Advisors for studying bar patterns and adaptive trading.

In the first part, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We created the COrder abstract object which is a base object for storing data on history orders and deals, as well as on market orders and positions. Now we will develop all the necessary objects for storing account history data in collections.

This article starts a new series about the creation of the DoEasy library for easy and fast program development. In the current article, we will implement the library functionality for accessing and working with symbol timeseries data. We are going to create the Bar object storing the main and extended timeseries bar data, and place bar objects to the timeseries list for convenient search and sorting of the objects.

In this article, I will create the collection class of Depths of Market of all symbols and start developing the functionality for working with the MQL5.com Signals service by creating the signal object class.

This article describes MQL5-RPC framework that enables Remote Procedure Calls from MQL5. It starts with XML-RPC basics, MQL5 implementation and follows with two real usage examples. First example is using external web service and the second one is a client to simple XML-RPC ATC 2011 Analyzer service. If you are interested on how to implement and analyze different statistics from ATC 2011 in real time, this article is just for you.

Recently MetaTrader 4 and MetaTrader 5 user received an opportunity to become a Signals Provider and earn additional profit. Now, you can display your trading success on your web site, blog or social network page using the new widgets. The benefits of using widgets are obvious: they increase the Signals Providers' popularity, establish their reputation as successful traders, as well as attract new Subscribers. All traders placing widgets on other web sites can enjoy these benefits.

We continue the series of articles on MQL5 programming. This time we will see how to get results of each optimization pass right during the Expert Advisor parameter optimization. The implementation will be done so as to ensure that if the conditions specified in the external parameters are met, the corresponding pass values will be written to a file. In addition to test values, we will also save the parameters that brought about such results.

The article provides the description of the technology aimed at increasing the effectiveness of any automated trading system. It provides a brief explanation of the idea, as well as its underlying basics, possibilities and disadvantages.

Every trader works using certain statistical calculations, even if being a supporter of fundamental analysis. This article walks you through the fundamentals of statistics, its basic elements and shows the importance of statistics in decision making.

This step-by-step guide is dedicated to the Signals service, examination of trading signals, a system approach to the search of a required signal which would satisfy criteria of profitability, risk, trading ambitions, working on various types of accounts and financial instruments.

If specific neural network programs for trading seem expensive and complex or, on the contrary, too simple, try NeuroPro. It is free and contains the optimal set of functionalities for amateurs. This article will tell you how to use it in conjunction with MetaTrader 5.

The Graphic.mqh library has been designed to work with graphics in MQL5. The article provides an example of its practical application and explains the idea of sorting. The general concept of sorting is described here since each type of sorting already has at least one separate article, while some of sorting types are objects of detailed studies.

Experienced traders are well aware of the fact that most time-consuming things in trading are not opening and tracking positions but selecting symbols and looking for entry points. In this article, we will develop an EA simplifying the search for entry points on trading instruments provided by your broker.

In this article, we continue expanding the features of the utility for collecting and navigating through symbols. This time, we will create new tabs displaying only the symbols that satisfy some of the necessary parameters and find out how to easily add custom tabs with the necessary sorting rules.