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.

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.

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.

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.

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.

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 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.

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.

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.

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.

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.

The article familiarizes the reader with exponential smoothing models used for short-term forecasting of time series. In addition, it touches upon the issues related to optimization and estimation of the forecast results and provides a few examples of scripts and indicators. This article will be useful as a first acquaintance with principles of forecasting on the basis of exponential smoothing models.

The market price is formed out of a stable balance between demand and supply which, in turn, depend on a variety of economic, political and psychological factors. Differences in nature as well as causes of influence of these factors make it difficult to directly consider all the components. This article sets forth an attempt to predict the market price on the basis of an elaborated regression model.

This article introduces a class designed to give a quick preliminary estimate of characteristics of various time series. As this takes place, statistical parameters and autocorrelation function are estimated, a spectral estimation of time series is carried out and a histogram is built.

When developing a trading system, there usually arises a problem of selecting the best combination of indicators and their signals. Discriminant analysis is one of the methods to find such combinations. The article gives an example of developing an EA for market data collection and illustrates the use of the discriminant analysis for building prognostic models for the FOREX market in Statistica software.

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.

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.

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.

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.

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.

The major problem of applied statistics is the problem of accepting statistical hypotheses. It was long considered impossible to be solved. The situation has changed with the emergence of the eigen-coordinates method. It is a fine and powerful tool for a structural study of a signal allowing to see more than what is possible using methods of modern applied statistics. The article focuses on practical use of this method and sets forth programs in MQL5. It also deals with the problem of function identification using as an example the distribution introduced by Hilhorst and Schehr.

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.

This article serves to familiarize the reader with the empirical mode decomposition (EMD) method. It is the fundamental part of the Hilbert–Huang transform and is intended for analyzing data from nonstationary and nonlinear processes. This article also features a possible software implementation of this method along with a brief consideration of its peculiarities and gives some simple examples of its use.

Indicator emissions are a little-studied area of market research. Primarily, this is due to the difficulty of analysis that is caused by the processing of very large arrays of time-varying data. Existing graphical analysis is too resource intensive and has therefore triggered the development of a parsimonious algorithm that uses time series of emissions. This article demonstrates how visual (intuitive image) analysis can be replaced with the study of integral characteristics of emissions. It can be of interest to both traders and developers of automated trading systems.

One year has passed since the launch of sales in MQL5 Market. It was a year of hard work, which turned the new service into the largest store of trading robots and technical indicators for MetaTrader 5 platform.

A short life span of futures contracts complicates their technical analysis. It is difficult to technically analyze short charts. For example, number of bars on the day chart of the UX-9.13 Ukrainian Stock index future is more than 100. Therefore, trader creates synthetic long futures contracts. This article explains how to splice futures contracts with different dates in the MetaTrader 5 terminal.

This article is dedicated to a new and perspective direction in machine learning - deep learning or, to be precise, deep neural networks. This is a brief review of second generation neural networks, the architecture of their connections and main types, methods and rules of learning and their main disadvantages followed by the history of the third generation neural network development, their main types, peculiarities and training methods. Conducted are practical experiments on building and training a deep neural network initiated by the weights of a stacked autoencoder with real data. All the stages from selecting input data to metric derivation are discussed in detail. The last part of the article contains a software implementation of a deep neural network in an Expert Advisor with a built-in indicator based on MQL4/R.

This article considers the application of multiple regression analysis to macroeconomic statistics. It also gives an insight into the evaluation of the statistics impact on the currency exchange rate fluctuation based on the example of the currency pair EURUSD. Such evaluation allows automating the fundamental analysis which becomes available to even novice traders.