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The Inverse Fair Value Gap Trading Strategy
The Inverse Fair Value Gap Trading Strategy
An inverse fair value gap(IFVG) occurs when price returns to a previously identified fair value gap and, instead of showing the expected supportive or resistive reaction, fails to respect it. This failure can signal a potential shift in market direction and offer a contrarian trading edge. In this article, I'm going to introduce my self-developed approach to quantifying and utilizing inverse fair value gap as a strategy for MetaTrader 5 expert advisors.
Gating mechanisms in ensemble learning
Gating mechanisms in ensemble learning
In this article, we continue our exploration of ensemble models by discussing the concept of gates, specifically how they may be useful in combining model outputs to enhance either prediction accuracy or model generalization.
From Basic to Intermediate: Variables (I)
From Basic to Intermediate: Variables (I)
Many beginning programmers have a hard time understanding why their code doesn't work as they expect. There are many things that make code truly functional. It's not just a bunch of different functions and operations that make the code work. Today I invite you to learn how to properly create real code, rather than copy and paste fragments of it. The materials presented here are for didactic purposes only. Under no circumstances should the application be viewed for any purpose other than to learn and master the concepts presented.
Feature Engineering With Python And MQL5 (Part I): Forecasting Moving Averages For Long-Range AI Models
Feature Engineering With Python And MQL5 (Part I): Forecasting Moving Averages For Long-Range AI Models
The moving averages are by far the best indicators for our AI models to predict. However, we can improve our accuracy even further by carefully transforming our data. This article will demonstrate, how you can build AI Models capable of forecasting further into the future than you may currently be practicing without significant drops to your accuracy levels. It is truly remarkable, how useful the moving averages are.
Price Action Analysis Toolkit Development (Part 9): External Flow
Price Action Analysis Toolkit Development (Part 9): External Flow
This article explores a new dimension of analysis using external libraries specifically designed for advanced analytics. These libraries, like pandas, provide powerful tools for processing and interpreting complex data, enabling traders to gain more profound insights into market dynamics. By integrating such technologies, we can bridge the gap between raw data and actionable strategies. Join us as we lay the foundation for this innovative approach and unlock the potential of combining technology with trading expertise.
Price Action Analysis Toolkit Development (Part 8): Metrics Board
Price Action Analysis Toolkit Development (Part 8): Metrics Board
As one of the most powerful Price Action analysis toolkits, the Metrics Board is designed to streamline market analysis by instantly providing essential market metrics with just a click of a button. Each button serves a specific function, whether it’s analyzing high/low trends, volume, or other key indicators. This tool delivers accurate, real-time data when you need it most. Let’s dive deeper into its features in this article.
Developing a Calendar-Based News Event Breakout Expert Advisor in MQL5
Developing a Calendar-Based News Event Breakout Expert Advisor in MQL5
Volatility tends to peak around high-impact news events, creating significant breakout opportunities. In this article, we will outline the implementation process of a calendar-based breakout strategy. We'll cover everything from creating a class to interpret and store calendar data, developing realistic backtests using this data, and finally, implementing execution code for live trading.
Introduction to MQL5 (Part 8): Beginner's Guide to Building Expert Advisors (II)
Introduction to MQL5 (Part 8): Beginner's Guide to Building Expert Advisors (II)
This article addresses common beginner questions from MQL5 forums and demonstrates practical solutions. Learn to perform essential tasks like buying and selling, obtaining candlestick prices, and managing automated trading aspects such as trade limits, trading periods, and profit/loss thresholds. Get step-by-step guidance to enhance your understanding and implementation of these concepts in MQL5.
The Liquidity Grab Trading Strategy
The Liquidity Grab Trading Strategy
The liquidity grab trading strategy is a key component of Smart Money Concepts (SMC), which seeks to identify and exploit the actions of institutional players in the market. It involves targeting areas of high liquidity, such as support or resistance zones, where large orders can trigger price movements before the market resumes its trend. This article explains the concept of liquidity grab in detail and outlines the development process of the liquidity grab trading strategy Expert Advisor in MQL5.
Creating a Daily Drawdown Limiter EA in MQL5
Creating a Daily Drawdown Limiter EA in MQL5
The article discusses, from a detailed perspective, how to implement the creation of an Expert Advisor (EA) based on the trading algorithm. This helps to automate the system in the MQL5 and take control of the Daily Drawdown.
Hidden Markov Models for Trend-Following Volatility Prediction
Hidden Markov Models for Trend-Following Volatility Prediction
Hidden Markov Models (HMMs) are powerful statistical tools that identify underlying market states by analyzing observable price movements. In trading, HMMs enhance volatility prediction and inform trend-following strategies by modeling and anticipating shifts in market regimes. In this article, we will present the complete procedure for developing a trend-following strategy that utilizes HMMs to predict volatility as a filter.
Developing a Replay System (Part 56): Adapting the Modules
Developing a Replay System (Part 56): Adapting the Modules
Although the modules already interact with each other properly, an error occurs when trying to use the mouse pointer in the replay service. We need to fix this before moving on to the next step. Additionally, we will fix an issue in the mouse indicator code. So this version will be finally stable and properly polished.
MQL5 Trading Toolkit (Part 6): Expanding the History Management EX5 Library with the Last Filled Pending Order Functions
MQL5 Trading Toolkit (Part 6): Expanding the History Management EX5 Library with the Last Filled Pending Order Functions
Learn how to create an EX5 module of exportable functions that seamlessly query and save data for the most recently filled pending order. In this comprehensive step-by-step guide, we will enhance the History Management EX5 library by developing dedicated and compartmentalized functions to retrieve essential properties of the last filled pending order. These properties include the order type, setup time, execution time, filling type, and other critical details necessary for effective pending orders trade history management and analysis.
Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method
Adaptive Social Behavior Optimization (ASBO): Schwefel, Box-Muller Method
This article provides a fascinating insight into the world of social behavior in living organisms and its influence on the creation of a new mathematical model - ASBO (Adaptive Social Behavior Optimization). We will examine how the principles of leadership, neighborhood, and cooperation observed in living societies inspire the development of innovative optimization algorithms.
Creating an MQL5 Expert Advisor Based on the Daily Range Breakout Strategy
Creating an MQL5 Expert Advisor Based on the Daily Range Breakout Strategy
In this article, we create an MQL5 Expert Advisor based on the Daily Range Breakout strategy. We cover the strategy’s key concepts, design the EA blueprint, and implement the breakout logic in MQL5. In the end, we explore techniques for backtesting and optimizing the EA to maximize its effectiveness.
Developing a Replay System (Part 55): Control Module
Developing a Replay System (Part 55): Control Module
In this article, we will implement a control indicator so that it can be integrated into the message system we are developing. Although it is not very difficult, there are some details that need to be understood about the initialization of this module. The material presented here is for educational purposes only. In no way should it be considered as an application for any purpose other than learning and mastering the concepts shown.
Developing A Swing Entries Monitoring (EA)
Developing A Swing Entries Monitoring (EA)
As the year approaches its end, long-term traders often reflect on market history to analyze its behavior and trends, aiming to project potential future movements. In this article, we will explore the development of a long-term entry monitoring Expert Advisor (EA) using MQL5. The objective is to address the challenge of missed long-term trading opportunities caused by manual trading and the absence of automated monitoring systems. We'll use one of the most prominently traded pairs as an example to strategize and develop our solution effectively.
Artificial Electric Field Algorithm (AEFA)
Artificial Electric Field Algorithm (AEFA)
The article presents an artificial electric field algorithm (AEFA) inspired by Coulomb's law of electrostatic force. The algorithm simulates electrical phenomena to solve complex optimization problems using charged particles and their interactions. AEFA exhibits unique properties in the context of other algorithms related to laws of nature.
Econometric tools for forecasting volatility: GARCH model
Econometric tools for forecasting volatility: GARCH model
The article describes the properties of the non-linear model of conditional heteroscedasticity (GARCH). The iGARCH indicator has been built on its basis for predicting volatility one step ahead. The ALGLIB numerical analysis library is used to estimate the model parameters.
Reimagining Classic Strategies in Python: MA Crossovers
Reimagining Classic Strategies in Python: MA Crossovers
In this article, we revisit the classic moving average crossover strategy to assess its current effectiveness. Given the amount of time since its inception, we explore the potential enhancements that AI can bring to this traditional trading strategy. By incorporating AI techniques, we aim to leverage advanced predictive capabilities to potentially optimize trade entry and exit points, adapt to varying market conditions, and enhance overall performance compared to conventional approaches.
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
MQL5 Trading Toolkit (Part 5): Expanding the History Management EX5 Library with Position Functions
Discover how to create exportable EX5 functions to efficiently query and save historical position data. In this step-by-step guide, we will expand the History Management EX5 library by developing modules that retrieve key properties of the most recently closed position. These include net profit, trade duration, pip-based stop loss, take profit, profit values, and various other important details.
Integrating Discord with MetaTrader 5: Building a Trading Bot with Real-Time Notifications
Integrating Discord with MetaTrader 5: Building a Trading Bot with Real-Time Notifications
In this article, we will see how to integrate MetaTrader 5 and a discord server in order to receive trading notifications in real time from any location. We will see how to configure the platform and Discord to enable the delivery of alerts to Discord. We will also cover security issues which arise in connection with the use of WebRequests and webhooks for such alerting solutions.
Across Neighbourhood Search (ANS)
Across Neighbourhood Search (ANS)
The article reveals the potential of the ANS algorithm as an important step in the development of flexible and intelligent optimization methods that can take into account the specifics of the problem and the dynamics of the environment in the search space.
Build Self Optimizing Expert Advisors in MQL5 (Part 2): USDJPY Scalping Strategy
Build Self Optimizing Expert Advisors in MQL5 (Part 2): USDJPY Scalping Strategy
Join us today as we challenge ourselves to build a trading strategy around the USDJPY pair. We will trade candlestick patterns that are formed on the daily time frame because they potentially have more strength behind them. Our initial strategy was profitable, which encouraged us to continue refining the strategy and adding extra layers of safety, to protect the capital gained.
Price Action Analysis Toolkit Development (Part 5): Volatility Navigator EA
Price Action Analysis Toolkit Development (Part 5): Volatility Navigator EA
Determining market direction can be straightforward, but knowing when to enter can be challenging. As part of the series titled "Price Action Analysis Toolkit Development", I am excited to introduce another tool that provides entry points, take profit levels, and stop loss placements. To achieve this, we have utilized the MQL5 programming language. Let’s delve into each step in this article.