Vladimir Skorina / Profile
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9+ years
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109
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Большой интерес к работе с тиками и нейронными сетями(в часности третьего поколения).


This article briefly describes the author's opinion on redrawing indicators, multi-timeframe indicators and displaying of quotes with Japanese candlesticks. The article contain no programming specifics and is of a general character.


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.


Nowadays, every trader must have heard of neural networks and knows how cool it is to use them. The majority believes that those who can deal with neural networks are some kind of superhuman. In this article, I will try to explain to you the neural network architecture, describe its applications and show examples of practical use.


Arrays are an integral part of almost any programming language along with variables and functions. The article should be of interest primarily to novice MQL5 programmers, while experienced programmers will have a good opportunity to summarize and systematize their knowledge.


The article describes one of the approaches to determining a useful signal (trend) in stream data. Small filtering (smoothing) tests applied to market quotes demonstrate the potential for creating non-lagging digital filters (indicators) that are not redrawn on the last bars.


The article examines the possibility of creating an advanced ZigZag indicator. The idea of identifying nodes is based on the use of the Envelopes indicator. We assume that we can find a certain combination of input parameters for a series of Envelopes, whereby all ZigZag nodes lie within the confines of the Envelopes bands. Consequently, we can try to predict the coordinates of the new node.


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.


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.


We all know the saying "Better to see once than hear a hundred times". You can read various books about Paris or Venice, but based on the mental images you wouldn't have the same feelings as on the evening walk in these fabulous cities. The advantage of visualization can easily be projected on any aspect of our lives, including work in the market, for example, the analysis of price on charts using indicators, and of course, the visualization of strategy testing. This article contains descriptions of all the visualization features of the MetaTrader 5 Strategy Tester.


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 centers around strategies that actively use pending orders, a metalanguage that can be created to formally describe such strategies and the use of a multi-purpose Expert Advisor whose operation is based on those descriptions


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 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.


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.


If we thoroughly examine any complex trading system, we will see that it is based on a set of simple trading signals. Therefore, there is no need for novice developers to start writing complex algorithms immediately. This article provides an example of a trading system that uses semaphore indicators to perform deals.


This article describes how object-oriented programming can be used for creating multi-timeframe and multi-currency panels for MetaTrader 5. The main goal is to build a universal panel, which can be used for displaying many different kinds of data, such as prices, price changes, indicator values or custom buy/sell conditions without the need to modify the code of the panel itself.


This article presents connecting MetaTrader 5 to ENCOG - Advanced Neural Network and Machine Learning Framework. It contains description and implementation of a simple neural network indicator based on a standard technical indicators and an Expert Advisor based on a neural indicator. All source code, compiled binaries, DLLs and an exemplary trained network are attached to the article.


The article provides a review of AutoElliottWaveMaker - the first development for Elliott Wave analysis in MetaTrader 5 that represents a combination of manual and automatic wave labeling. The wave analysis tool is written exclusively in MQL5 and does not include external dll libraries. This is another proof that sophisticated and interesting programs can (and should) be developed in MQL5.


This article takes us to a whole new direction in developing EAs, indicators and scripts in MQL4 and MQL5. In the future, this programming paradigm will gradually become the base standard for all traders in implementation of EAs. Using the automata-based programming paradigm, the MQL5 and MetaTrader 5 developers will be anywhere near being able to create a new language - MQL6 - and a new platform - MetaTrader 6.


If MQL5 language functional is not enough for fulfilling tasks, an MQL5 programmer has to use additional tools. He\she has to pass to another programming language and create an intermediate DLL. MQL5 has the possibility to present various data types and transfer them to API but, unfortunately, MQL5 cannot solve the issue concerning data extraction from the accepted pointer. In this article we will dot all the "i"s and show simple mechanisms of exchanging and working with complex data types.