Aipe Li / Profile

The graphical method proposed by Bill Wolfe allows to detect a pattern, based on which a moment and direction for entry can be found, and also it helps forecast the target which the price should reach, as well as the time of target reaching. The article describes how to create an indicator based on a ZigZag, that would search for Wolfe Waves, and a simple Expert Advisor trading based on this indicator.

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.

In this article we are going to show how to explore the Standard Library of Trading Strategy Classes and how to add Custom Strategies and Filters/Signals using the Patterns-and-Models logic of the MQL5 Wizard. In the end you will be able easily add your own strategies using MetaTrader 5 standard indicators, and MQL5 Wizard will create a clean and powerful code and fully functional Expert Advisor.

This article will teach you how to receive trade signals that are necessary for a trade system to work. The examples of forming 20 trade signals are given here as separate custom functions that can be used while developing Expert Advisors. For your convenience, all the functions used in the article are combined in a single mqh include file that can be easily connected to a future Expert Advisor.

The MetaTrader 5 platform allows developing and testing trading robots that simultaneously trade multiple financial instruments. The built-in Strategy Tester automatically downloads required tick history from the broker's server taking into account contract specifications, so the developer does not need to do anything manually. This makes it possible to easily and reliably reproduce trading environment conditions, including even millisecond intervals between the arrival of ticks on different symbols. In this article we will demonstrate the development and testing of a spread strategy on two Moscow Exchange futures.

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 details a method by which cross-platform expert advisors can be developed faster and easier. The proposed method consolidates the features shared by both versions into a single class, and splits the implementation on derived classes for incompatible features.

The article features formalized rules of two trading strategies 'Turtle Soup' and 'Turtle Soup Plus One' from Street Smarts: High Probability Short-Term Trading Strategies by Linda Bradford Raschke and Laurence A. Connors. The strategies described in the book are quite popular. But it is important to understand that the authors have developed them based on the 15...20 year old market behavior.

One of the most popular methods of market analysis is the Elliott Wave Principle. However, this process is quite complicated, which leads us to the use of additional tools. One of such instruments is the automatic marker. This article describes the creation of an automatic analyzer of Elliott Waves in MQL5 language.

The article describes a method of automated creation of neural network EAs using MQL5 Wizard and Hlaiman EA Generator. It shows you how you can easily start working with neural networks, without having to learn the entire body of theoretical information and writing your own code.

EA Tree is the first drag and drop MetaTrader MQL5 Expert Advisor builder. You can create complex MQL5 using a very easy to use graphical user interface. In EA Tree, Expert Advisors are created by connecting boxes together. Boxes may contain MQL5 functions, technical indicators, custom indicators, or values. Using the "tree of boxes", EA Tree generates the MQL5 code of the Expert Advisor.

In this article I presented different methods of interaction between MQL5 code and managed C# code. I also provided several examples on how to marshal MQL5 structures against C# and how to invoke exported DLL functions in MQL5 scripts. I believe that the provided examples may serve as a basis for future research in writing DLLs in managed code. This article also open doors for MetaTrader to use many libraries that are already implemented in C#.

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.

In addition to creation of neuronets, the NeuroSolutions software suite allows exporting them as DLLs. This article describes the process of creating a neuronet, generating a DLL and connecting it to an Expert Advisor for trading in MetaTrader 5.