Class For Working With Databases In A Simplified Manner – library MetaTrader 5

Class For Working With Databases In A Simplified Manner - library for MetaTrader 5
Having desired to work with SQLite database for the purpose of storing my statistical generated from simulations, i noticed very early that it seems very challenging and time consuming to work with database built in functions. I then decided to create a simplified class and functions to make my work easy. To use the class

Class CalcFrac – Number of bars before and after the current High / Low (calculated fractal) – library MetaTrader 5

Class CalcFrac - Number of bars before and after the current High / Low (calculated fractal) - library for MetaTrader 5
Calculates fractals and lets you specify the number of bars separately before and after the current High / Low (fractal).Functions: //+——————————————————————+ //| calculate lower fractals                                         | //+——————————————————————+ bool CalcFrac :: is_lower_fr(int number_of_bars) //+——————————————————————+ //| calculate upper fractals                                         | //+——————————————————————+ bool CalcFrac :: is_upper_fr(int number_of_bars) Sample: Indicator : FractalsPeriod Class CalcFrac – Number of bars before and after

MQL5 Wizard – Candlestick Patterns Class – library MetaTrader 5

MQL5 Wizard - Candlestick Patterns Class - library for MetaTrader 5
The MQL5 Wizard allows creating ready-made Expert Advisors based on the Standard library classes delivered together with the client terminal. It allows to check your trade ideas quickly, all you need is to create your own trading signals class. The structure of this class and example can be found in the article MQL5 Wizard: How

CDownLoadHistory class – library MetaTrader 5

CDownLoadHistory class
The CDownLoadHistory class provides the methods of historical data downloading in two modes: “visual” and “silent”. 1. Visual mode The example of use of this mode is downloadhistoryvisualmode.mq5. The “history download mode” input parameter can be one of two modes: “current symbol” or “all symbols from Market Watch window”: For the “All symbols from Market

The class of a module of trade signals, on “inner bar breakthrough” in trend direction – library MetaTrader 5

Description of signals
The MQL5 Wizard provides an opportunity to create a strategy using different modules. For example, the main module can be written by developer, the other modules (money management, trailing stop) can be developed by other programmers. The strategy, implemented in this module is following: when outside bar appears, it checks the fact of the inner

MLP Neural Network Class – library MetaTrader 5

MLP Neural Network Class - library for MetaTrader 5
CNetMLP provides multilayer perceptron (MLP). The feature of the class is that input vector and network structure notions are separated, i.e. input vector and network structure descriptions are not connected to each other. The size of the input vector can have any value within reasonable limits. Input data should be normalized, i.e. the data should be

CFastFile – class for working with uchar array as a virtual file – library MetaTrader 5

CFastFile - class for working with uchar array as a virtual file - library for MetaTrader 5
The CFastFile eliminates the need for an intermediate writing of data to the physical file on disk. It provides the significant acceleration when working with data. It has functions, similar to standard FileWriteXXX/FileReadXXX functions. It means that you can easily migrate from the use of the physical files to the fast work with the “virtual”

RBF Neural Network Class – library MetaTrader 5

RBF Neural Network Class - library for MetaTrader 5
Class implements neural network of radial basis functions (Radial Basis Function Network – RBFN). Here is represented the classic realization of RBFN consisted of two layers of neurons: hidden layer neurons with radially symmetric activation function and exit layer of linear and sigmoid activation function. Activation function of the output layer is automatically selected for