This article focuses on specifics of choice, preconditioning and evaluation of the input variables (predictors) for use in machine learning models. Manipulations. This book will be an invaluable resource for anyone who wants to use artificial intelligence in Oct 11, 2016 · These functions allow you to create and optimize neural networks containing from two to four layers (input layer, output layer, zero layer, as well as one or two hidden layers). Kohonen Maps or Self-Organizing maps(SOM) or Self-Organizing Feature Map(SOFM). mqproj). May 21, 2024 · Free Download MQL5 MACHINE LEARNING 02 – Deep Learning For Algo–TradingPublished 4/2024Created by Latvian Trading Solutions,Omega Joctan,Joy D MoyoMP4 | Video: h264, 1280x720 | Audio: AAC, 44. In this course, our primary objective is to introduce you to the realm of Machine learning with neural networks using the most powerful algorithmic trading language, MQL5. Apr 7, 2023 · Mql5 now supports matrix and vector operations which are used in various computational tasks, including machine learning. mql5. Applied Learning Project. The term "Nodiurnal" reflects its ability to adapt and operate not only during the typical diurnal (daytime) trading hours but also during non-standard Jun 2, 2023 · Machine learning is the process of iteratively improving a model, and properly tuned parameters are key to achieving better results. Build high-frequency expert advisors using algebraic equations and advanced MQl5 tools. Let's take a look at how to set up and prepare a development Dive into the world of ONNX, the powerful open-standard format for exchanging machine learning models. nhid1: hidden layer 1. Ahmad Hassam. 2: Figure 2. 05 lot or other that i can select on inputs but after that the grid has to start with 0. The presentation covers game logic development, integration, and hands-on testing Oct 6, 2022 · Polynomial Regression. ONNX models can be created using various machine learning tools. The current project involves fixing existing code that runs into debugging issues without errors and optimizing it for efficient performance in live trading Apr 25, 2024 · Hello , I want Machine Learning: Lorentzian Classification (TradingView) indicator to MQL5 indicator. You will find many tutorial videos on YouTube. Aug 10, 2022 · Data Science and Machine Learning(Part 21): Unlocking Neural Networks, Optimization algorithms demystified; Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5; Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost With "Neural Networks for Algorithmic Trading with MQL5", you will gain comprehensive knowledge and practical skills for creating your own trading robots capable of analyzing markets and making decisions using advanced machine learning technologies. Feb 7, 2023 · Introduction. Hlaiman EA Generator is integrated with the MQL5 Wizard using a signal library module - SignalHNN. Extract a diagonal or construct a diagonal matrix. If you want to learn about machine learning, try RapidMiner. Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on the use of computer algorithms to learn the happenings of Jan 17, 2024 · Machine Learning is a complex and rewarding field for anyone of any experience. Machine learning technology is based on neural networks. Which is machine learning indicator . And same inputs in it. Nov 16, 2021 · There is a Python package available for developing integrations with MQL, which enables a plethora of opportunities such as data exploration, creation and use of machine learning models. Dec 17, 2012 · The support vector machine observes the data in 2 dimensional space, and uses a regression algorithm to find a 1 dimensional hyperplane (aka line) that most accurately separate the data into its two categories. mqh. MetaTrader 5 Trading Platform; MetaTrader 5 Nov 7, 2022 · We continue to study machine learning methods. Computes the eigenvalues and right eigenvectors of a square matrix. MQL5 has been developed by MetaQuotes for their trading platform. In recent years, several new types of data have emerged, specifically designed for working with deep learning models. Same To Same. With this article, we begin another big topic, Reinforcement Learning. Jun 22, 2022 · A learner with some or no previous knowledge of Machine Learning will get to know main algorithms of Supervised and Unsupervised Learning, and Reinforcement Learning, and will be able to use ML open source Python packages to design, test, and implement ML algorithms in Finance. 0. Lumina Vision. May 13, 2022 · Data Science and Machine Learning(Part 21): Unlocking Neural Networks, Optimization algorithms demystified; Data Science and Machine Learning (Part 20): Algorithmic Trading Insights, A Faceoff Between LDA and PCA in MQL5; Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost Feb 29, 2024 · The book "Neural networks for algorithmic trading with MQL5" is your go-to guide for learning how to use machine learning and neural networks in trading. Apr 11, 2023 · In this book Raphael makes everything simple and comprehensive, he starts with the rudiments and the start-up blocks of the mql5 language to the building of high-frequency algorithms using machine learning. Alexander Hahn 2016. One of the leading programming languages for data processing is Python. Ridge regression is the method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. This is a native functionality of the language, not a library. This article discusses the implementation of automatic moves in the tic-tac-toe game in Python, integrated with MQL5 functions and unit tests. Description. Neural networks are--- MQL5. This course covers data science, artificial intelligence, machine learning, coding, training and prediction with neural networks. 2. from 2010 to 2022. Polynomial regression is one of the machine learning algorithms used for making predictions, I heard that it was widely used to predict the spread rate of COVID-19 and other infectious diseases, Let's see what this algorithm is made up of. Our aim is to give you a solid foundation to principles and concepts you will need in developing self optimizing softwares that learn from Mar 19, 2019 · In this post, we present a technique employing ZeroMQ (an Open Source, Asynchronous Messaging Library and Concurrency Framework) for building a basic – but easily extensible – high performance bridge between external (non-MQL) programming languages and MetaTrader 4. Discover the essentials of MQL5, the language powering MetaTrader 5, as we demystify the world of automated trading. Det. vect_true [in] Vector of true values. Then press Ctrl+N or click on the New button on the Menu bar. Eig. bmtrading. This article describes the machine learning technique applied to grid and martingale trading. Soon we will release native support for complex numbers (ready), speed vectors and matrices. In the MQL5 Wizard window, select Expert Advisor and click the "Next" as shown on Fig. Training independently (Python etc). Computes the eigenvalues of a general matrix Mar 3, 2023 · Naïve Bayes classifier is a probabilistic algorithm used in machine learning for classification tasks. MQL5 is part of the trading platform MetaTrader 5 (MT5) for Forex, CFD and Futures. We will code an expert advisor from scratch that can trade in different financial markets, such as forex, cryptocurrencies, indices, commodities, and stocks. Passing indicators and prices to a perceptron for market analysis Indicators are mathematical equations used to analyze the market and help identify trends, entry and exit points, as well as support and resistance Apr 5, 2023 · 2. Jan 23, 2023 · Introduction. Python is rapidly becoming the language of choice for machine learning. com/TraderZetaCoding a neural network in MQL5Disclaimer: Use at your own risk, I make no gu MQL5 now supports matrix and vector operations which are used in various computational tasks, including machine learning. Once generated automatically, the Expert Advisor can then be taught to trade on any number of instruments and time frames. 1 MQL5 Wizard. Writing an Expert Advisor. Linear regression is one of the core algorithms that is used by many algorithms such as: Logistic regression which is a linear regression-based model. Mar 19, 2019 · In this post, we present a technique employing ZeroMQ (an Open Source, Asynchronous Messaging Library and Concurrency Framework) for building a basic – but easily extensible – high performance bridge between external (non-MQL) programming languages and MetaTrader 4. You'll learn to code your own DNNs using MQL5, a programming language for MetaTrader platforms. Apr 8, 2022 · Data Science and Machine Learning (Part 02): Logistic Regression. I want it As soon As possible! - en Machine learning. nout: output layer. Convolutional Neural Networks are another machine learning algorithm that tend to specialize in decomposing multi-dimensioned data sets into key constituent parts. MetaQuotes Language 5 (MQL5) is a high-level language designed for developing technical indicators, trading robots and utility applications, which automate financial trading. Here we will focus only on the implementation of the deep Q-learning method. We look at how this is typically achieved and explore a possible application for traders in another MQL5 wizard signal class. Once in the ONNX format, the model can be loaded into MQL5 scripts or Expert Advisors, enabling the utilization of advanced machine learning capabilities for algorithmic trading strategies Sep 5, 2016 · A topic for traders. The neural network activation function determines the output value of a neuron depending on the weighted sum of inputs. While traditional methods have served us well, their Nov 8, 2022 · To implement the deep Q-learning algorithm using MQL5, we will use the "Q-learning. But it can be difficult to assemble these models into one ONNX model. Is a Predictive model that is used to find the linear relationship between a dependent variable and one or more independent variables. May 7, 2024 · In the fast-paced world of financial markets, separating meaningful signals from the noise is crucial for successful trading. 1,1. The full Expert Advisor code can be found in the attachment. 15. We'll start with a basic DNN built in Excel, providing a foundation for the more complex coding in MQL5. Online trading / WebTerminal; Free technical indicators and robots; Articles about programming and trading; Order trading robots on the Freelance; Market of Expert Advisors and applications Follow forex signals; Low latency forex VPS; Traders forum; Trading blogs; Charts; MetaTrader 5. This separating line is then used by the support vector machine to classify new data points into either category 1 or category 2. All other data is used for testing on new data, i. The Matrix. It is based on Bayes' theorem, which calculates the probability of a hypothesis given the available evidence. Sep 29, 2020 · Can a profitable system be created using machine learning? What can a neural network give us? The rationale for training neural networks for decision making. In this article, we explore how autoencoders are revolutionizing trading practices, offering Jul 27, 2022 · Introduction. MALE5 is a machine-learning repository for creating trading systems in the c++ like, MQL5 programming language. According to Wikipedia gradient descent (also often called steepest descent) is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. Values other than CLASSIFICATION_TOP_K_ACCURACY, CLASSIFICATION_AVERAGE_PRECISION and CLASSIFICATION_ROC_AUC (used in the ClassificationScore method) are applied. Jan 18, 2023 · scikit-learn is a widely used machine learning library for Python that includes a variety of tools for training and evaluating models, including neural networks. May 16, 2023 · Build expert advisors using dynamic signals and machine learning technics. Python has many good modules for deep learning as well. com/en/market Machine learning methods. MetaTrader 5 Trading Platform; MetaTrader 5 Parameters. The method provides improved efficiency in parameters estimation problems in exchange for a tolerable amount of bias meanwhile Lasso (Least absolute shrinkage and selection Apr 19, 2023 · Job Title: MQL5 Trading Bot Code Debugging and Optimization** **Description:** We are seeking an experienced MQL5 developer proficient in debugging and optimizing trading bot codes. Optimus PrimeX. By employing sophisticated neural network architectures, autoencoders excel at uncovering hidden patterns within market data, transforming noisy input into actionable insights. Feb 3, 2024 · Machine learning integration is a key feature of MQL5 (MetaQuotes Language 5) that empowers traders to leverage the power of machine learning algorithms within their trading systems. The course is organized into 2 blocks and 12 sections. Specialized programming languages are used for processing and analyzing data, statistics and machine learning. de/broker/*Free Trading Journal: https:// Mar 15, 2022 · Linear Regression. Is an unsupervised machine learning technique used to produce a low-dimensional(typically two-dimensional) representation of a higher dimensional data set while preserving the topological structure of the data. mqh: A class containing functions for preprocessing data to make it suitable for machine learning: tree. Descriptions of all supported functions are available in the MQL5 Documentation. e. They are currently supported in Caffe2, Microsoft Cognitive Toolkit, MXNet, PyTorch and OpenCV. Transformations. Dedicated Forex cloud solutions with stable and fast May 7, 2024 · In the fast-paced world of financial markets, separating meaningful signals from the noise is crucial for successful trading. Terminal: Added export of trading reports to HTML and PDF files. This book is intended for algorithmic traders who want to learn how to create trading strategies using advanced artificial intelligence techniques. MetaTrader 5 Client Terminal. The idea is to take repeated steps in the opposite direction of the gradient (or approximate gradient) of the function at the current point ClassificationScore. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel Dec 15, 2023 · December 14, 2023. Nov 10, 2015 · Using Assertions in MQL5 Programs. Sep 9, 2022 · Do you have any experience in neural networking or machine learning trading. This hands-on exercise will focus on a real-world forex trading problem, showcasing the practical applications of DNNs. com/TraderZetaCoding a neural network in MQL5Disclaimer: Use at your own risk, I make no gu Jul 24, 2022 · github: PhiAlphaInvestments/WillsNeuralNetworkhttps://www. 2,1. However, it is possible to combine several trained ONNX models in one MQL5 program. Jan 18, 2024 · Finance Magnates. MQL5 provides automatic data type conversion for model inputs and outputs if the passed parameter type does not match the model. Mar 28, 2023 · Introduction. I have dedicated significant effort to back testing, forward testing and tuning of my algorithm to make it performs optimally. Machine learning (ML) is a branch of artificial intelligence (AI) that focuses on the use of computer algorithms to learn the happenings of Trading Robot on Metatrader 5Based on Neural Network (Machine Learning)MT4 : https://www. Unlike Linear Regression that we discussed in part 01, Logistic Regression is a classification method based on linear regression. Apr 23, 2020 · Creating Neural Network EAs Using MQL5 Wizard and Hlaiman EA Generator - MT5; Neural network: Self-optimizing Expert Advisor - MT5; Neural Networks: From Theory to Practice - MT5; Using MetaTrader 5 Indicators with ENCOG Machine Learning Framework for Timeseries Prediction - MT5; Using Self-Organizing Feature Maps (Kohonen Maps) in MetaTrader 5 Dive into the world of ONNX, the powerful open-standard format for exchanging machine learning models. Feb 22, 2023 · 30 USD. de/broker/*Free Trading Journal: https:// Data formats used to represent machine learning models play a crucial role in their effectiveness. Products. 01 lots i need also a step grid option so i can select the Aug 20, 2020 · 1. Machine learning - Matrix and Vector Methods - MQL5 Reference - Reference on algorithmic/automated trading language for MetaTrader 5. Surprisingly, this approach has little to no coverage in the global network. Among the built-in methods of matrices and vectors, there are several that are in demand in machine learning tasks, in particular, in the implementation of neural networks. Dot. This format is supported by many platforms, including Chainer, Caffee2 and PyTorch. The names of the main inputs are quite self-explanatory: nin: number of input layer neurons. In this article we dive deep into the inner mechanisms powering the models you build, we explore the intricate world of features,predictions and impactful decisions unravelling the complexities and gaining a firm grasp of model interpretation. The idea is to take repeated steps in the opposite direction of the gradient (or approximate gradient) of the function at the current point Jan 26, 2024 · A library containing code for measuring performance of machine learning models: preprocessing. The built in Python integration in MQL5 enables the creation of various solutions, from simple linear regression to deep learning models. A complete guide to coding deep learning algorithms using the MQL5 Algorithmic trading language. In this article, we will focus on two new data formats that have become widely adopted in modern models. Jan 18, 2024 · In the context of MQL5 (MetaQuotes Language 5), the integration of ONNX models involves converting a trained machine learning model to the ONNX format. Prediction. Starting a new MQL5 document. One popular technique is a wrapper method. As the name implies, a neural network is a collection of many neurons which are primitive computing cells. Create an ONNX model using specialized tools, integrate it into your MQL5 application and use it to make trading decisions. Learn the art of navigating tradeoffs , enhancing predictions, ranking Aug 3, 2021 · We have already said that we are moving towards implementing machine learning in MQL5. These methods are used in machine learning. Neural Network: is it difficult or simple? How to integrate a neural network into a trading terminal? How to test a neural network? Testing stages. 55 USD. The goal is to improve the interactivity of the game and ensure the reliability of the system through testing in MQL5. It was developed to help build machine learning-based trading robots, effortlessly in the MetaTrader5 platform ONNX is an open-source format for machine learning models. Apr 12, 2023 · The same refers to machine learning models: it is easier to create several simpler models that one complex one. Learn how to develop algorithms for trends, trends pull backs ad trend reversal; Learn how to use moving averages to mark the beginning and end of trend regimes. Indicator for Spindles Charting. Learn how to use neural networks in MQL5, the most powerful algorithmic trading language, to identify market patterns and classify bullish and bearish conditions. Oct 8, 2015 · However, this is a problem that machine learning experts and data scientists have been grappling with for a long time and have come up with a wide range of tools and techniques to help you out. *Complete MT5 Programming Course: https://en. Oct 12, 2023 · AI Nodiurnal EA is an advanced Forex robot that leverages cutting-edge machine learning technology to optimize trading strategies and enhance performance in the dynamic foreign exchange market. Figure 1. In addition, it provides improvements to the code profiler and strategy tester. Calling this Library is so simple and takes few lines of code - English. Jun 9, 2010 · 2. Sampling of trades with a random duration is selected in the range of 15-35. Experiments with neural networks (part 1): revisiting geometry - mt5. 775. com/en/market/product/65084MT5 : https://www. By the end of the specialization, you will be able to create and enhance quantitative trading strategies with machine learning that you can train, test, and implement in capital markets. Machine learning relies on training data to learn the general behaviour of the market to ultimately make fairly accurate predictions. Features. 3 and etc. We can expect that this property of reinforcement learning will open up new horizons for building trading strategies. 1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 32 Lectures ( 6h 1m ) | Size: 2. We have created this thread to select and share some materials that may be useful to you. MetaTrader 5 (MT5) introduces build 4150, featuring a range of improvements in reporting functionality and the integration of new machine learning methods in MQL5. Interfaces for other popular frameworks and libraries Dec 1, 2023 · Dive into the fascinating realm of algorithmic trading with our beginner-friendly guide to MQL5 programming. Sep 19, 2013 · A multilayer perceptron (MLP) is used as the main neural network component. 1. A wrapper method uses a machine-learning algorithm to evaluate each subset of indicators. Neural Networks Libraries: This is standard library built for flexible neural Networks with performance in mind. MQL5 provides a seamless integration of machine learning techniques, allowing traders to develop advanced and adaptive trading strategies. Mar 4, 2024 · Dive into the world of ONNX, the powerful open-standard format for exchanging machine learning models. New approaches and opportunities of deep predictor analysis and their influence on possible overfitting of models will be considered. There are two ways to create a model: You can use OnnxCreate to create a model from an onnx file or OnnxCreateFromBuffer to create it from a data array. In this article, we explore how autoencoders are revolutionizing trading practices, offering Jan 17, 2024 · Machine Learning is a complex and rewarding field for anyone of any experience. Traders and investors will benefit from enhanced reporting capabilities and advanced tools for data analysis. mqh: Decision tree library can be found on this file: AdaBoost Test. Equip yourself with the essential Feb 14, 2016 · hello coders i need someone to create an ea with this condition: the ea has to start with open buy and sell order and after that use a grid with lot exponent 1,1. It's an easy to use Drag and Drop Environment with hundreds of algorithms for various kinds of tasks. From understanding the basics to taking your first steps in coding, this article is your key to unlocking the potential of algorithmic trading even without a programming With "Neural Networks for Algorithmic Trading with MQL5", you will gain comprehensive knowledge and practical skills for creating your own trading robots capable of analyzing markets and making decisions using advanced machine learning technologies. With this option, you can easily share your trading Nov 14, 2023 · Discover the indispensable role of Support Vector Machines (SVM) in shaping the future of trading. Price. Connecting neurosolutions neuronets - mt5 using neural networks in metatrader - mt4 price forecasting using neural networks - mt4 recipes for neuronets - mt4 third generation neural networks: deep networks - mt5 neural networks cheap and cheerful Dec 20, 2023 · This build introduces new MQL5 functions for matrix and vector operations, which are used in machine learning. 09. In this article, we will consider one of the ensembles called the voting classifier. If an ONNX model is used as a resources in an EA, you will need to recompile the EA every time you change the model. the ea has to start for example with sell and buy order with 0. MQL5. Universities, governments, start-ups and major technology companies are pouring their resources into ai because they believe it is the future experiments with AlgLib in machine learning; using Apache Spark with Amazon Web Services (EC2 and EMR), when the capabilities of AlgLib ceased to be enough; using TensorFlow or PyTorch via PythonDLL. The method produces an ensemble of weak models (for example, decision trees), in which (in contrast to bagging) models are built sequentially, rather than independently (in parallel). py script included in the project. Compute the classification metric to evaluate the quality of the predicted data compared to the true data. The reason why many fail to successfully apply these sophiscated tools is because Next, update the project from MQL5 Storage. Diag. mq5" EA file. The three courses will show you how to create various quantitative and algorithmic trading strategies using Python. Looking at a simple linear regression model. If you are a trader, you can use machine learning to predict market direction. Aug 17, 2022 · STOP_DATE = datetime ( 2022, 1, 1 ) The base model is trained from 2021 to early 2022, while the metamodel is trained from 2018 to 2022. This approach allows the models to set up certain strategies for solving the problems. Jul 24, 2022 · github: PhiAlphaInvestments/WillsNeuralNetworkhttps://www. Learn the art of navigating tradeoffs , enhancing predictions, ranking Jul 27, 2022 · Introduction. Reasons for writing this post: Lack of comprehensive, publicly available Mar 28, 2019 · Comprehensive data processing requires extensive tools and is often beyond the sandbox of one single application. Dive into the world of SVM with real-world applications, step-by-step tutorials, and expert insights. About training samples. You can create the ONNX model yourself using the PricePredictionTraining. Save model as REST endpoint (in my case i was saving it as a pickle file) 2. The article provides a description of how to connect MetaTrader 5 and Python using sockets, as well Apr 26, 2023 · *Complete MT5 Programming Course: https://en. community. In this course, you will learn how to fully automate your trading using MetaTrader 5 trading robots (expert advisors). 75 USD. The project contains an ONNX model, two python scripts, an MQL5 script for project operation, and an MQL5 project file (ONNX. Good to know before you get started. Dot product of two vectors. Machine learning in trading: CatFx50. Unlike other methods in the Machine Learning section, this one applies to the vector of true values rather than the vector of predicted values. mq5(EA) The main test Expert Advisor, all the code explained here, is executed ClassificationScore. 4 181. Reasons for writing this post: Lack of comprehensive, publicly available Feb 3, 2023 · Using machine learning and OpenAI's technology allows the EA to analyze vast amounts of data and make predictions with high accuracy, providing traders with a powerful tool that can help them achieve their financial goals. The language syntax is very close to C++ enabling programmers to develop applications in the object Apr 12, 2021 · According to the graph, the found pattern works from the end of 2016 to the present day, in the rest interval it fails. The chosen learning algorithm has to wade through a carefully selected sample to extract meaningful information . EigVals. Trading logic in MQL5 and prediction via internet (in my case i was loading the pickle file) I assume that any machine learning bot needs a training part (runs periodically) and a trading logic (runs continuously during market Jan 16, 2017 · 16 January 2017, 08:34. The forex market, a dynamic beast fueled by a complex web of data, demands a keen eye for intricate patterns and the agility to adapt. This means that the next tree learns from the mistakes of the previous one, then this process is These theories represented a significant step in understanding the interaction of neurons and later formed the basis for the principles of constructing neuron interactions in artificial neural networks. . Machine learning is a new game that is becoming very popular. 1. This comprehensive guide explores how SVM can elevate your trading strategies, enhance decision-making, and unlock new opportunities in the financial markets. It provides a consistent interface for a wide range of machine learning algorithms, including neural networks, making it a popular choice for data scientists and researchers. 05 15:08 #3. Compute the determinant of a square invertible matrix. metric [in] Metric type from the ENUM_CLASSIFICATION_METRIC enumeration. Before proceeding with the implementation, let us decide what the initial data and the reward system will be. MetaTrader 5 Trading Platform; MetaTrader 5 Apr 4, 2024 · MQL5 MACHINE LEARNING 02: Deep Learning For Algo-Trading. 06. This probabilistic classifier is a simple yet effective algorithm in various situations. de/mt5-masterclass/*Recommended Broker: https://en. Next, we will include a large set of ML mechanics and give functionality similar to TensorFlow. Product Details. Donald Hebb's book The organization of behavior: A neuropsychological theoryreleased in 1949 laid the foundation for neural learning. patreon. Discover how leveraging ONNX can revolutionize algorithmic trading in MQL5, allowing traders to seamlessly integrate cutting-edge AI models and elevate their strategies to new heights. Theory: Suppose that we draw a graph of the probability of someone being obese versus their weight. Sep 26, 2023 · OVERVIEW A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. 9 GBA complete guide to coding deep learning algorithms using the Nov 17, 2020 · Gradient boosting is a powerful machine learning algorithm. Begin by launching the MetaQuotes Language Editor 5. eisqkkcqkdzxalphekor