Chao Jie Shen / Profile

We all are aware of that "No profit obtained in the past will guarantee any success in future". However, it is still very actual to be able to estimate trading systems. This article deals with some simple and convenient methods that will help to estimate trade results.

I am not a professional programmer. And thus, the principle of "going from the simple to the complex" is of primary importance to me when I am working on trading system development. What exactly is simple for me? First of all, it is the visualization of the process of creating the system, and the logic of its work. Also, it is a minimum of handwritten code. In this article, I will attempt to create and test the trading system, based on a Matlab package, and then write an Expert Advisor for MetaTrader 5. The historical data from MetaTrader 5 will be used for the testing process.

This article is a continuation of previous articles on deep neural network and predictor selection. Here we will cover features of a neural network initiated by Stacked RBM, and its implementation in the "darch" package.

The optimization process can require significant resources of your computer or even of the MQL5 Cloud Network test agents. This article comprises some simple ideas that I use for work facilitation and improvement of the MetaTrader 5 Strategy Tester. I got these ideas from the documentation, forum and articles.

Hello dear reader! In this article, I will try to explain and show you how you can easily and quickly get the hang of the principles of creating Expert Advisors, working with indicators, etc. It is beginner-oriented and will not feature any difficult or abstruse examples.

This article summarizes and systematizes the principles of creating algorithms and elements of trading systems. The article considers designing of expert algorithm. As an example the CExpertAdvisor class is considered, which can be used for quick and easy development of trading systems.

This article aims to present ready-made solutions for publishing forecasts using MetaTrader 5. It covers a range of ideas: from using dedicated websites for publishing MetaTrader statements, through setting up one's own website with virtually no web programming experience needed and finally integration with a social network microblogging service that allows many readers to join and follow the forecasts. All solutions presented here are 100% free and possible to setup by anyone with a basic knowledge of e-mail and ftp services. There are no obstacles to use the same techniques for professional hosting and commercial trading forecast services.

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.

This article focuses on specifics of choice, preconditioning and evaluation of the input variables (predictors) for use in machine learning models. New approaches and opportunities of deep predictor analysis and their influence on possible overfitting of models will be considered. The overall result of using models largely depends on the result of this stage. We will analyze two packages offering new and original approaches to the selection of predictors.

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 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.

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.

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.

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.

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.

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.

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.