
Studying candlestick analysis techniques (part IV): Updates and additions to Pattern Analyzer
The article presents a new version of the Pattern Analyzer application. This version provides bug fixes and new features, as well as the revised user interface. Comments and suggestions from previous article were taken into account when developing the new version. The resulting application is described in this article.

Library for easy and quick development of MetaTrader programs (part XXIII): Base trading class - verification of valid parameters
In the article, we continue the development of the trading class by implementing the control over incorrect trading order parameter values and voicing trading events.

Library for easy and quick development of MetaTrader programs (part XXV): Handling errors returned by the trade server
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.

Applying OLAP in trading (part 1): Online analysis of multidimensional data
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.

Creating a new trading strategy using a technology of resolving entries into indicators
The article suggests a technology helping everyone to create custom trading strategies by assembling an individual indicator set, as well as to develop custom market entry signals.
Practical application of neural networks in trading. It's time to practice
The article provides a description and instructions for the practical use of neural network modules on the Matlab platform. It also covers the main aspects of creation of a trading system using the neural network module. In order to be able to introduce the complex within one article, I had to modify it so as to combine several neural network module functions in one program.

Timeseries in DoEasy library (part 40): Library-based indicators - updating data in real time
The article considers the development of a simple multi-period indicator based on the DoEasy library. Let's improve the timeseries classes to receive data from any timeframes to display it on the current chart period.

The Simple Example of Creating an Indicator Using Fuzzy Logic
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.

Library for easy and quick development of MetaTrader programs (part IV): Trading events
In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We already have collections of historical orders and deals, market orders and positions, as well as the class for convenient selection and sorting of orders. In this part, we will continue the development of the base object and teach the Engine Library to track trading events on the account.

Genetic Algorithms: Mathematics
Genetic (evolutionary) algorithms are used for optimization purposes. An example of such purpose can be neuronet learning, i.e., selection of such weight values that allow reaching the minimum error. At this, the genetic algorithm is based on the random search method.

Analyzing trading results using HTML reports
The MetaTrader 5 platform features functionality for saving trading reports, as well as Expert Advisor testing and optimization reports. Trading and testing reports can be saved in two formats: XLSX and HTML, while the optimization report can be saved in XML. In this article we consider the HTML testing report, the XML optimization report and the HTML trading history report.

Visualizing optimization results using a selected criterion
In the article, we continue to develop the MQL application for working with optimization results. This time, we will show how to form the table of the best results after optimizing the parameters by specifying another criterion via the graphical interface.

How to Evaluate the Expert Testing Results
The article gives formulas and the calculation order for data shown in the Tester report.

Time Series Forecasting Using Exponential Smoothing (continued)
This article seeks to upgrade the indicator created earlier on and briefly deals with a method for estimating forecast confidence intervals using bootstrapping and quantiles. As a result, we will get the forecast indicator and scripts to be used for estimation of the forecast accuracy.

Timeseries in DoEasy library (part 41): Sample multi-symbol multi-period indicator
In the article, we will consider a sample multi-symbol multi-period indicator using the timeseries classes of the DoEasy library displaying the chart of a selected currency pair on a selected timeframe as candles in a subwindow. I am going to modify the library classes a bit and create a separate file for storing enumerations for program inputs and selecting a compilation language.

Applying the probability theory to trading gaps
In this article, we will apply the probability theory and mathematical statistics methods to creating and testing trading strategies. We will also look for optimal trading risk using the differences between the price and the random walk. It is proved that if prices behave like a zero-drift random walk (with no directional trend), then profitable trading is impossible.

Library for easy and quick development of MetaTrader programs (part XIX): Class of library messages
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.

Processing optimization results using the graphical interface
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.

Self-adapting algorithm (Part III): Abandoning optimization
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.

Using MATLAB 2018 computational capabilities in MetaTrader 5
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».

OpenAI's ChatGPT features within the framework of MQL4 and MQL5 development
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.

Grokking market "memory" through differentiation and entropy analysis
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.

Testing (Optimization) Technique and Some Criteria for Selection of the Expert Advisor Parameters
There is no trouble finding the Holy Grail of testing, it is however much more difficult to get rid of it. This article addresses the selection of the Expert Advisor operating parameters with automated group processing of optimisation and testing results upon maximum utilisation of the Terminal performance capabilities and minimum end user load.

On Methods of Technical Analysis and Market Forecasting
The article demonstrates the capabilities and potential of a well-known mathematical method coupled with visual thinking and an "out of the box" market outlook. On the one hand, it serves to attract the attention of a wide audience as it can get the creative minds to reconsider the trading paradigm as such. And on the other, it can give rise to alternative developments and program code implementations regarding a wide range of tools for analysis and forecasting.

Library for easy and quick development of MetaTrader programs (part XXXIII): Pending trading requests - closing positions under certain conditions
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.

Kernel Density Estimation of the Unknown Probability Density Function
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 Box-Cox Transformation
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.

Analyzing the Indicators Statistical Parameters
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.

Resolving entries into indicators
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.

Library for easy and quick development of MetaTrader programs (part XXVII): Working with trading requests - placing pending orders
In this article, we will continue the development of trading requests, implement placing pending orders and eliminate detected shortcomings of the trading class operation.

Neural networks made easy (Part 7): Adaptive optimization methods
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.

Timeseries in DoEasy library (part 37): Timeseries collection - database of timeseries by symbols and periods
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.

Evaluating the ability of Fractal index and Hurst exponent to predict financial time series
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.

Library for easy and quick development of MetaTrader programs (part XVII): Interactivity of library objects
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.

Manual charting and trading toolkit (Part II). Chart graphics drawing tools
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.

Neural networks made easy (Part 4): Recurrent networks
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.

Library for easy and quick development of MetaTrader programs (part XXIV): Base trading class - auto correction of invalid parameters
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.

MQL5 Cookbook: Saving Optimization Results of an Expert Advisor Based on Specified Criteria
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.

Market math: profit, loss and costs
In this article, I will show you how to calculate the total profit or loss of any trade, including commission and swap. I will provide the most accurate mathematical model and use it to write the code and compare it with the standard. Besides, I will also try to get on the inside of the main MQL5 function to calculate profit and get to the bottom of all the necessary values from the specification.

Neural networks made easy (Part 2): Network training and testing
In this second article, we will continue to study neural networks and will consider an example of using our created CNet class in Expert Advisors. We will work with two neural network models, which show similar results both in terms of training time and prediction accuracy.