Articles on data analysis and statistics in MQL5

This article is a logical continuation of my article Statistical Probability Distributions in MQL5 which set forth the classes for working with some theoretical statistical distributions. Now that we have a theoretical base, I suggest that we should directly proceed to real data sets and try to make some informational use of this base.

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.

The article addresses probability distributions (normal, log-normal, binomial, logistic, exponential, Cauchy distribution, Student's t-distribution, Laplace distribution, Poisson distribution, Hyperbolic Secant distribution, Beta and Gamma distribution) of random variables used in Applied Statistics. It also features classes for handling these distributions.

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.

The MetaTrader 5 Client Terminal offers a wide range of opportunities for optimization of Expert Advisor parameters. In addition to the optimization criteria included in the strategy tester, developers are given the opportunity of creating their own criteria. This leads to an almost limitless number of possibilities of testing and optimizing of Expert Advisors. The article describes practical ways of creating such criteria - both complex and simple ones.

We now know that probability density function (PDF) of a market cycle does not remind a Gaussian but rather a PDF of a sine wave and most of the indicators assume that the market cycle PDF is Gaussian we need a way to "correct" that. The solution is to use Fisher Transform. The Fisher transform changes PDF of any waveform to approximately Gaussian. This article describes the mathematics behind the Fisher Transform and the Inverse Fisher Transform and their application to trading. A proprietary trading signal module based on the Inverse Fisher Transform is presented and evaluated.

One of the most interesting aspects of Self-Organizing Feature Maps (Kohonen maps) is that they learn to classify data without supervision. In its basic form it produces a similarity map of input data (clustering). The SOM maps can be used for classification and visualizing of high-dimensional data. In this article we will consider several simple applications of Kohonen maps.

Estimation of statistical parameters of a sequence is very important, since most of mathematical models and methods are based on different assumptions. For example, normality of distribution law or dispersion value, or other parameters. Thus, when analyzing and forecasting of time series we need a simple and convenient tool that allows quickly and clearly estimating the main statistical parameters. The article shortly describes the simplest statistical parameters of a random sequence and several methods of its visual analysis. It offers the implementation of these methods in MQL5 and the methods of visualization of the result of calculations using the Gnuplot application.

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.

This article describes the econometric methods of analysis, the autocorrelation analysis and the analysis of conditional variance in particular. What is the benefit of the approach described here? Use of the non-linear GARCH models allows representing the analyzed series formally from the mathematical point of view and creating a forecast for a specified number of steps.

Is there any correlation between the past price behavior and its future trends? Why does the price repeat today the character of its previous day movement? Can the statistics be used to forecast the price dynamics? There is an answer, and it is positive. If you have any doubt, then this article is for you. I'll tell how to create a working filter for a trading system in MQL5, revealing an interesting pattern in price changes.

This article is intended to get its readers acquainted with a possible variant of using graphical objects of the MQL5 language. It analyses an indicator, which implements a panel of managing a simple spectrum analyzer using the graphical objects. The article is meant for readers acquianted with basics of MQL5.

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.

The article shows an example of how to develop an MQL5-program implementing the adaptive algorithm of clustering called Growing neural gas (GNG). The article is intended for the users who have studied the language documentation and have certain programming skills and basic knowledge in the area of neuroinformatics.

There are a lot of measures that allow determining the effectiveness and profitability of a trade system. However, traders are always ready to put any system to a new crash test. The article tells how the statistics based on measures of effectiveness can be used for the MetaTrader 5 platform. It includes the class for transformation of the interpretation of statistics by deals to the one that doesn't contradict the description given in the "Statistika dlya traderov" ("Statistics for Traders") book by S.V. Bulashev. It also includes an example of custom function for optimization.

Construction of Japanese candlestick chart and analysis of candlestick patterns constitute an amazing area of technical analysis. The advantage of candlesticks is that they represent data in such a manner that you can track the dynamics inside the data. In this article we analyze candlestick types, classification of candlestick patterns and present an indicator that can determine candlestick patterns.

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.

In this article the author talks about evolutionary calculations with the use of a personally developed genetic algorithm. He demonstrates the functioning of the algorithm, using examples, and provides practical recommendations for its usage.

Is it possible to predict the behavior of the market for a short upcoming interval of time, based on the recurring tendencies of candle directions, at specific times throughout the day? That is, If such an occurrence is found in the first place. This question has probably arisen in the mind of every trader. The purpose of this article is to attempt to predict the behavior of the market, based on the statistical recurrences of candle directions during specific intervals of time.

In this article, we will develop a tool for CFTC report analysis. We will solve the following problem: to develop an indicator, that allows using the CFTC report data directly from the data files provided by Commission without an intermediate processing and conversion. Further, it can be used for the different purposes: to plot the data as an indicator, to proceed with the data in the other indicators, in the scripts for the automated analysis, in the Expert Advisors for the use in the trading strategies.

The idea of digital signal filtering has been widely discussed on forum topics about building trading systems. And it would be imprudent not to create a standard code of digital filters in MQL5. In this article the author describes the transformation of simple SMA indicator's code from his article "Custom Indicators in MQL5 for Newbies" into code of more complicated and universal digital filter. This article is a logical sequel to the previous article. It also tells how to replace text in code and how to correct programming errors.

In this article we will check the well-known statement that "The whole day trading depends on how the Asian session is traded".

The Market Profile was developed by trully brilliant thinker Peter Steidlmayer. He suggested to use the alternative representation of information about "horizontal" and "vertical" market movements that leads to completely different set of models. He assumed that there is an underlying pulse of the market or a fundamental pattern called the cycle of equilibrium and disequilibrium. In this article I will consider Price Histogram — a simplified model of Market Profile, and will describe its implementation in MQL5.

This article shows you how to easily use Neural Networks in your MQL4 code taking advantage of best freely available artificial neural network library (FANN) employing multiple neural networks in your code.

The article compares the time and results of Expert Advisors' optimization using genetic algorithms and those obtained by simple search.

Trading is, first of all, a calculus of probabilities. The proverb about idleness being an engine for progress reveals us the reason why all those indicators and trading systems have been developed. It comes that the major of newcomers in trading study "ready-made" trading theories. But, as luck would have it, there are some more undiscovered market secrets, and tools used in analyzing of price movements exist, basically, as those unrealized technical indicators or math and stat packages. Thanks awfully to Bill Williams for his contribution to the market movements theory. Though, perhaps, it's too early to rest on oars.

The article is concerned with the problem of re-counting of the indicator value in the MetaTrader 4 Client Terminal when the null bar changes. It outlines general idea of how to add to the indicator code some extra program items that allow to restore program code saved before multiple re-counting.

25 to 30% of all crashlogs received from users appear due to errors occurring when functions imported from custom dlls are executed.

The article deals with convenient and efficient methods of information storage and viewing. Alternatives to the terminal standard log file and the Comment() function are considered here.

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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.

The article gives formulas and the calculation order for data shown in the Tester report.

Article explains how to read testing reports and to interpret the obtained results properly.

Many programs of technical analysis allow to test trading strategies on history data. In the most cases, the testing is conducted on already completed data without any attempts to model the trends within a price bar. It was made quickly, but not precisely