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Articles by Void OnTick
Creating a mean-reversion strategy based on machine learning
Maxim Dmitrievsky #: Checked, everything works for me. Attached the files of trained models from the article and the updated bot above. It is desirable to retrain the models afterwards, because there are demo models attached to the article. When you understand the python script. Good day! Yes, in this release the bot itself compiles and works correctly. But the models need to be retrained. And in general, as I understand, it should be done regularly.
Integrate Your Own LLM into EA (Part 5): Develop and Test Trading Strategy with LLMs(IV) - Test Trading Strategy
MetaTrader 5 — Trading | 29 January 2025, 13:33 22 0 Table of contents Introduction Development Environment for the Example in This Article Methods for Loading LLMs in MQL5 Converting the GPT-2 Model to ONNX Model Formulating EA Strategy and Server Functionality Creating the Inference Service EA Client Backtesting Conclusion Introduction In previous articles, we introduced how to fine-tune pre-trained GPT-2 models using different methods to make GPT-2 perform tasks according to our wishes,...
Price Action Analysis Toolkit Development (Part 9): External Flow
Financial markets can be complex, often presenting challenges for traders and analysts in processing and interpreting data accurately. To overcome these challenges, various libraries has been developed to simplify market analysis, each designed to handle data in ways that align with specific goals.
Price Action Analysis Toolkit Development Part(4): Analytics Forecaster EA
MetaTrader 5 — Integration | 6 December 2024, 14:10 71 0 Introduction Previous Article Review Project Overview Building a Telegram Bot and Fetching Chart IDs Implementing Telegram Integration to the EA (Expert Advisor) Testing Conclusion Having transitioned from a script to an Expert Advisor (EA), the previous tool, Analytics Master EA, was designed to analyze key metrics and provide continuous updates directly on the chart.
Price Action Analysis Toolkit Development (Part 3): Analytics Master - EA
MetaTrader 5 — Examples | 29 November 2024, 14:02 33 0 Introduction Review of the Previous Tool Overview of the Analytic Master Exploring the Expert Advisor Code Code Breakdown Code Implementation and Testing Conclusion Having developed the analytic comment script in the previous episode, I have identified its limitations regarding script properties, which I will outline below.
Data Science and ML (Part 31): Using CatBoost AI Models for Trading
Iterations This is the number of decision trees iterations to build. More iterations lead to better performance but also carry a risk of overfitting. learning_rate This factor controls the distribution of each tree to the final prediction. A smaller learning rate requires more iterations for trees to converge but often results in better models. depth This is the maximum depth of the trees. Deeper trees can capture more complex patterns in the data but, may often lead to overfitting.
Gain An Edge Over Any Market (Part IV): CBOE Euro And Gold Volatility Indexes
MetaTrader 5 — Examples | 23 September 2024, 13:54 18 0 In the age of big data, there are hundreds of millions of datasets that each hold the potential to yield untapped levels of accuracy when forecasting financial markets. Unfortunately, it is unlikely that all existing datasets will live up to this potential.
Introduction to MQL5 (Part 9): Understanding and Using Objects in MQL5
MetaTrader 5 — Tester | 5 September 2024, 12:18 21 0 Welcome back to our MQL5 series! We'll discuss a fascinating subject in this chapter that I believe you'll find very useful and fascinating. We will begin a project where we will work with different chart objects in MQL5, which will be an essential foundation for our future projects. This starting point will be especially handy when we go into more complex projects, like using various harmonic patterns.
Building A Candlestick Trend Constraint Model (Part 8): Expert Advisor Development (II)
MetaTrader 5 — Tester | 30 August 2024, 13:34 20 0 Introduction Creating the Expert Advisor: (i) Launching the default EA (template) in MetaEditor. (ii) Customizing the Template. (iii) Writing Trend Constraint Expert logic into the prepared Template. Tester Conclusion In our previous article, we explored creating an expert advisor (EA) using the Trend Constraint V1.09 indicator, complemented by the manually executed Trend Constraint R-R script for placing risk and reward rectangles.
Example of Causality Network Analysis (CNA) and Vector Auto-Regression Model for Market Event Prediction
MetaTrader 5 — Trading systems | 29 August 2024, 17:11 21 0 Causality Network Analysis (CNA) is a method used to understand and model complex causal relationships between variables in a system. When applied to financial markets, it can help identify how different market events and factors influence each other, potentially leading to more accurate predictions. Causal Discovery: Causal discovery is the process of inferring causal relationships from observational data.
Implementing a Bollinger Bands Trading Strategy with MQL5: A Step-by-Step Guide
MetaTrader 5 — Trading | 7 August 2024, 11:38 78 0 In the dynamic world of financial trading using of technical indicators can be of big impact. Bollinger Bands are one such effective technique that traders can use to determine possible entry and exit points based on price volatility and trend strength. This article explores automating trading choices with a Bollinger Bands trading technique utilizing the MQL5 programming language in MetaTrader 5.
Twitter Sentiment Analysis with Sockets
MetaTrader 5 — Integration | 26 July 2024, 17:00 152 0 This article introduces a sophisticated trading bot that leverages real-time sentiment analysis from social media platforms to inform its trading decisions. By integrating MetaTrader 5 (MT5) with a Python-based sentiment analysis engine, this bot represents a cutting-edge fusion of quantitative finance and natural language processing.
Using JSON Data API in your MQL projects
Mixing external data could improve decision-making in algorithm trading. APIs enable data transfer between different systems and help traders access different data sources like real-time market data from other brokers and banks, access economic indicators not just economic calendars, access news feeds or social sentiment analysis, online artificial intelligence tools, online forecast system or anything you can imagine that are available in API services.
Developing Zone Recovery Martingale strategy in MQL5
MetaTrader 5 — Trading | 28 June 2024, 15:53 68 0 In this article we will create the zone recovery martingale forex trading strategy expert advisor (EA) in MetaQuotes Language 5 (MQL5) for MetaTrader 5 (MT5) step by step. The zone recovery martingale strategy is a common strategy that is oriented to counter loosing positions by opening opposite positions with a slightly greater trading volume that cancels the losing positions.
Data Science and ML (Part 23): Why LightGBM and XGBoost outperform a lot of AI models?
Gradient Boosted Decision Trees (GBDT) are a powerful machine learning technique used primarily for regression and classification tasks. They combine the predictions of multiple weak learners, usually decision trees, to create a strong predictive model. The core idea is to build models sequentially, each new model attempting to correct the errors made by the previous ones.
Neural networks made easy (Part 66): Exploration problems in offline learning
Dmitriy Gizlyk #: I don't know how MetaTrader Tester selects inputs for each core. Main idea in online study use pretrained model from one pass to another. But if Tester run Optimithation 1..4 to Agent 1 at one pass the they all use random (not pretrained) model. Understood! Thank you Very Much! I also added some indicators and Parameters, total 27 BarDescr....
Use of custom tick modeling to prevent illusory grail-like backtests of Renko-driven trading robots
Many traders like renko and other "timeless" charts for their clarity and price noise reduction. The charts are used not only for technical analysis but for building trading strategies on top of them. And they require a proper backtesting. However, not many traders realize that Renko backtesting may be (and usually is) highly deceptive due to specificities of the chart and platforms that provide it.
Data Science and Machine Learning (Part 19): Supercharge Your AI models with AdaBoost
Adaboost, short for adaptive boosting is an ensemble machine learning model that attempts to build a strong classifier out of weak classifiers. The algorithm assigns weights to instances based on their correct or incorrect classification. It combines weak learners using a weighted sum. The final strong learner is a linear combination of weak learners with weights determined during the training process.
Introduction to MQL5 (Part 3): Mastering the Core Elements of MQL5
Do you like the article? Share it with others — post a link to it! Find us on Facebook! Join our fan page MetaTrader 5 — Expert Advisors | 26 January 2024, 10:11 68 0 Welcome back, fellow traders and aspiring algorithmic enthusiasts! As we step into the third chapter of our MQL5 journey, we stand at the crossroads of theory and practice, poised to unravel the secrets behind arrays, custom functions, preprocessors, and event handling.
Data label for time series mining (Part 6)：Apply and Test in EA Using ONNX
Do you like the article? Share it with others — post a link to it! Find us on Facebook! Join our fan page MetaTrader 5 — Examples | 18 January 2024, 13:22 84 0 We discussed in the previous article how to use socket (websocket) to communicate between EA and python server to solve the backtesting problem, and also discussed why we adopted this technique.
Neural networks made easy (Part 40): Using Go-Explore on large amounts of data
Do you like the article? Share it with others — post a link to it! MetaTrader 5 — Expert Advisors | 23 October 2023, 14:18 182 0 In the previous article "Neural networks made easy (Part 39): Go-Explore, a different approach to exploration", we familiarized ourselves with the Go-Explore algorithm and its ability to explore the environment.
Learn how to deal with date and time in MQL5
Do you like the article? Share it with others — post a link to it! MetaTrader 5 — Trading | 18 October 2023, 10:21 125 0 It is not hidden by anyone in the financial market field, the importance of time, and how it can affect trading decisions and results.
The RSI Deep Three Move Trading Technique
Do you like the article? Share it with others — post a link to it! Similar articles MetaTrader 5 — Trading systems | 8 August 2023, 14:23 576 0 1. Introduction This article is based on a new series of studies that showcase a few trading techniques based on the RSI. A trading technique is a way to use an indicator. The study is based on mql5 coding language. 2.
Can Heiken-Ashi Combined With Moving Averages Provide Good Signals Together?
Do you like the article? Share it with others — post a link to it! Similar articles MetaTrader 5 — Trading systems | 6 July 2023, 13:59 228 0 Introduction Combinations of strategies may offer better opportunities. We can combine indicators together or patterns, or even better, indicators with patterns, so that we get an extra confirmation factor. In this article, we will see how to use Heiken-Ashi charting alongside moving averages as a trend confirmation technique.
How to use MQL5 to detect candlesticks patterns
Do you like the article? Share it with others — post a link to it! Similar articles MetaTrader 5 — Trading | 3 April 2023, 13:59 303 0 Introduction Candlesticks are a very helpful technical tool if we use them correctly, as we can find a potential movement based on their patterns. Candlesticks can form specific patterns on the chart and these patterns can be divided into two types single-candle patterns and blended candle patterns (more than one candle).
Learn how to design a trading system by Fibonacci
Do you like the article? Share it with others — post a link to it! Similar articles MetaTrader 5 — Trading | 20 March 2023, 16:04 295 0 Introduction In this new article from our series about learning how to design a trading system based on the most popular technical analysis tools and indicators, we will learn how to create a trading system based on the Fibonacci Retracement technical tool which is one of the most popular and widely used in trading.
Data Science and Machine Learning (Part 12): Can Self-Training Neural Networks Help You Outsmart the Stock Market?
Introduction If you have been an algorithmic-trader for a while, chances are high you've heard about Neural Networks. It always seems like they are a way forward to make holy grails trading robots, about this I'm not that sure because it takes more than just adding neural networks to a trading bot to end up with a profitable system.
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