Explore the creation of a comprehensive Pending Orders Management library for MetaTrader 5, designed specifically with algorithmic traders in mind. This article delves into structuring a functional EX5 library using standard MQL5 functions to open, modify, and manage pending orders efficiently. Discover how to streamline the development process by importing this library, which significantly reduces code redundancy and accelerates project timelines. Learn to implement practical error-handling strategies and ensure trading permissions are met. With a focus on enhancing trading efficiency, this library is an essential toolkit for both novice and experienced MQL5 developers aiming to optimize their algorithmic strategies.
#MQL5 #MT5 #MQL5 #Libraries

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In the recent update on developing a replay system, the focus shifted to enhancing the Chart Trade Project. The initial attempts to integrate a control indicator on the chart using a service proved challenging, emphasizing the need to convert MQL5 scripts into services effectively. A service can operate independently from a specific chart, which facilitates ongoing chart monitoring.

The article highlights differences between scripts and services, illustrating how a simple moving average script can be transformed into a service. This involves crucial property adjustments in the code to ensure functionality even without direct chart linkage. The enhanced service can automatically reintroduce indicators if removed, offering an innovative method for maintaining chart configurations.

Additionally, the discourse extends to the practical application, such as...
#MQL5 #MT5 #ReplaySystem #MQL5

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This indicator visually represents the high and low boundaries of the previous three days on a chart. It automatically updates the current day's levels throughout the trading session. The feature allows users to assess recent price action trends and potential support and resistance areas effectively. Its primary function is to aid in identifying key market levels quickly without cluttering the chart with too much information. This tool is particularly useful for those seeking to understand market behavior over several days, assisting in making informed trading decisions based on historical price levels. Designed for users aiming for efficient analysis, it integrates seamlessly into daily chart reviews.
#MQL5 #MT5 #Indicator #Trading

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Explore expert approaches to securing Admin Panels in MQL5 with password protection, enhancing authentication without compromising user experience. The integration of MQL5's robust security features, like encryption and account-based licensing, safeguards intellectual property while ensuring only authorized access. Learn about implementing a password-based authentication mechanism with a user-friendly interface for sensitive functionalities. Addressing potential vulnerabilities, this method employs concepts like secure password management and seamless user input handling. Dive into the process of fortifying applications against unauthorized access using advanced MQL5 protection techniques, fostering a secure environment for both developers and traders.
#MQL5 #MT5 #Security #AdminPanel

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Reinforcement Learning (RL) is transforming algorithmic trading with its adaptability to market fluctuations. It refines decision-making under uncertain conditions, enhancing strategies by optimizing trade execution through continuous feedback. Unlike traditional linear models, RL's nuanced approach balances exploration and exploitation. In implementing SARSA, an on-policy algorithm, developers can expect safer decision-making by considering real-time actions to update Q-values. This method, compared to Q-Learning, excels in unpredictable markets, making SARSA favorable in environments like JPY trading pairs. Practical applications span improved risk management to scalable multi-asset strategies, underscoring RL's growing significance in sophisticated trading systems.
#MQL5 #MT5 #RL #AITrading

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The Expert Advisor operates using the 'iVIDyA' indicator, which provides signals exclusively at the start of a new bar. Positions are opened with predefined Stop Loss and Take Profit settings, and trailing is not employed. At any given time, the system maintains no more than one active position. Upon receiving a new signal, any opposite position will be closed immediately. Optimization is possible by adjusting the 'Working timeframe' parameter for tailored performance. This EA does not layer multiple positions, ensuring a straightforward approach to trading within the market structure.
#MQL5 #MT5 #EA #Strategy

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Explore the next stage in enhancing library classes for MetaTrader 5, focusing on developing a refined SplitContainer control. This involves creating a dynamic separator object that adjusts panel sizes based on a mouse-driven, hatched area, offering a simplified yet efficient resizing process. The new structure enables direct interaction through panels, integrating updated event IDs and methods to handle user inputs accurately. This iteration emphasizes modifying core design features and improving user-interface interactions, paving the way for sophisticated trading tools and better control management across various trade scenarios. Ideal for developers seeking to integrate flexible interface components within their trading systems.
#MQL5 #MT5 #Algorithm #Programming

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Creating a logger for MQL5 inspired by Python's logging module can enhance project management significantly. The CDKLogger class is designed for simplicity, focusing on ease of use without complex features like hierarchies or rotators. To use it, copy CDKLogger.mqh into the designated MQL\Include\DKStdLib\Logger folder and import the class.

While effective, the class has room for improvement. A notable issue is the frequent parsing of strings by the StringFormat function, even when the log level doesn't necessitate message output. This can be inefficient when dealing with numerous debug messages, making it necessary to conditionally wrap log outputs.

Unfortunately, MQL5 lacks support for passing a dynamic number of parameters to various logging functions such as Debug, Info, and Error. Suggestions for optimizing this process are welcome and could help ref...
#MQL5 #MT5 #Logger #Coding

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Explore the K-Nearest Neighbors (KNN) algorithm, a straightforward yet powerful method for classification and regression. KNN relies on neighborhood proximity, assuming that similar data points cluster closely. Step-by-step, the algorithm selects the number of 'k' neighbors, calculates Euclidean distances, and votes on the classification. Key challenges include setting the optimal 'k' value and handling performance drawbacks, particularly with large datasets in trading applications. Despite these, KNN is effective for clearly labeled, smaller datasets, offering a robust approach to integrating machine learning with MetaTrader 5 for forex and stock predictions. Enhance your trades with data-driven insights using KNN.
#MQL5 #MT5 #KNN #AlgoTrading

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The "EuroSurge" Expert Advisor for MT4 presents a structured approach for managing trades on EURUSD 5-minute charts, incorporating multiple technical indicators for signal generation. Configurable trade size calculations are offered with options for fixed lot size, balance percentage, and equity percentage. Key input parameters include FixedLotSize, TradeSizePercent, and MagicNumber.

Indicator settings encompass Moving Averages, RSI, MACD, Bollinger Bands, and the Stochastic Oscillator. Each indicator can be enabled or disabled individually. Signal detection functions evaluate buy and sell criteria with conditions for each indicator, allowing for relaxed threshold levels compared to standard.

Trade execution includes placing orders with calculated stop loss and take profit using multipliers. Lot sizes are managed through a specialized function that adapt...
#MQL4 #MT4 #EA #AlgoTrading

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Streamline your trading strategy with a data-driven approach using enhanced visualization techniques. By transforming raw market data into intuitive, interactive charts like dynamic candlestick overlays and heat maps, traders gain deeper market insights, facilitating informed decision-making. Connect MetaTrader 5 with Python to automate data collection—efficiently using pandas for analysis—and visualize trends using advanced plotting techniques. Implement reinforcement learning models, like Deep Q-Networks, to predict trading moves by evaluating historical XAU/USD data. Establish socket communication between MQL5 and Python for seamless trade execution. This sophisticated integration reduces human error and enhances trading precision, optimizing entry and exit points for maximized performance.
#MQL5 #MT5 #DataViz #AITrading

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Creating an Expert Advisor (EA) for the Daily Range Breakout strategy in MetaQuotes Language 5 (MQL5) enables traders to automate trading based on breaking key price levels formed from the previous day's range. This strategy relies on capitalizing on significant price movements beyond identified support and resistance levels, typically observed on 1-hour or 4-hour charts, reducing noise and capturing major trends.

The fundamental steps involve setting the daily high and low price as potential breakout points. A long position is triggered when price moves above the previous day's resistance, while a short position follows a breach below support. Incorporating a stop-loss to manage risk, it's critical to optimize and backtest the EA to ensure it aligns with trading objectives and adapts to various market conditions.

Implementation in MQL5 requires defining an...
#MQL5 #MT5 #EA #Strategy

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Starting December 1, 2024, the minimum supported versions of the trading platforms will be:

• MetaTrader 4 build 1420 released on May 24
• MetaTrader 5 build 4410 released on June 21

After this date, older versions of desktop terminals will not be able to connect to broker servers.

In the past six months, we have released four MetaTrader 5 updates:

✓ Build 4410: Fixed crashes in the desktop platform, browser compatibility checks, and demo account opening in the web version.
✓ Build 4570: Crosshair mode, line chart and Market Watch setting in the web version, OpenBLAS library for matrix computations and improved ONNX support in MQL5.
✓ Build 4585: Fixed crashes during debugging and testing of MQL5 programs, as well as memory leaks during compilation.
✓ Build 4620: Extended OpenBLAS support, fixed tick history queries.

Each MetaTrader 4 version comes with performance improvements and bug fixes.

Download the latest version to take advantage of new features

CandlesticksData script, developed for MetaTrader 5, facilitates the transfer of detailed candlestick data into a CSV file. Its primary function is to structure this data across various timeframes, aiding in quantitative analysis, strategy backtesting, and educational exploration. Traders can leverage this for informed decision-making by recognizing trends, patterns, and market behaviors. The script allows integration with external software for advanced analyses, including statistical or machine learning applications.

Upon initialization, it defines properties and sets variables, supporting timeframe selection from minutes to months. Data collection is executed within the OnStart function, gathering key metrics: Open, High, Low, Close prices, tick volume, total volume, spread, and candlestick characteristics such as size and type. Captured data is fo...
#MQL5 #MT5 #Script #DataAnalysis

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Delve into Smart Money Concepts (SMC) and Order Blocks—key chart areas where institutional traders execute large trades, sparking significant price movements. This gives retail traders a strategic edge by aligning with institutional flows. By harnessing tools like Fibonacci retracement, traders can refine entry points, enhance trade accuracy, and monitor price action. Detect Bullish/Bearish Order Blocks using simple candles logic. Leveraging the 61.8% Fibonacci level ensures alignment with institutional activity. The integrated Expert Advisor automates these strategies, continuously scanning the market for market structure, helping traders achieve systematic, high-probability trades mirroring institutional strategies.
#MQL5 #MT5 #SMC #AlgoTrading

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Enhancing our MQL5 dashboard panel with interactive components is the next critical phase. Following an initial static setup, focus shifts towards automating button functionalities to ensure an intuitive user interface. The goal is to create a dynamic trading tool by setting up events that trigger actions upon user interaction.

We will automate various buttons for trading operations such as "Open Buy", "Sell", and others needed for market engagement. Additionally, automation extends to closure and information buttons providing account details. The "OnTick" event handler will update account information in real-time.

"OnChartEvent" will handle user interactions, including mouse movements and button clicks. Implementing this structure will streamline the trading process within the MetaTrader 5 environment, enhancing user experience.
#MQL5 #MT5 #automation #AlgoTrading

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The Saucer signal from the iAO (Awesome Oscillator) is an analytical tool that detects potential market momentum shifts. This indicator focuses on three consecutive bars: a down bar followed by two upward bars, to spot changes in the trend. An added layer of analysis is provided with the integration of iMA (Moving Average), which serves as a filter to refine the signal's accuracy. The MA component helps verify that the identified trend shift aligns with broader market movements. The visualization involves the MA AO Arrow image, illustrating points where the conditions for the Saucer signal align with the Moving Average filter. This combination of indicators seeks to enhance decision-making by providing clearer insights into market trends.
#MQL5 #MT5 #Indicator #Trading

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The article explores FEDformer, a cutting-edge model designed to enhance long-term time series forecasting. By integrating seasonal trend decomposition and Fourier analysis into the traditional Transformer architecture, FEDformer aims to improve prediction accuracy while reducing computational complexity from quadratic to linear. The model effectively captures global properties of time series by selectively using both low and high-frequency components, validated by extensive experiments showing performance improvements by 14.8% for multivariate and 22.6% for univariate forecasting. This innovative approach provides practical benefits for MetaTrader 5 developers, offering more efficient and accurate trading algorithms.
#MQL5 #MT5 #Algorithm #TimeSeries

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Implementing efficiency improvements and integration strategies in technical design can streamline processes and enhance system performance. Recent updates to the MetaTrader 5 replay/simulator system involve restructuring code to eliminate redundant components and enhance stability. The control indicator has been integrated directly into the simulator service, removing its visibility from user-accessible indicator lists. This change offers improved control over system resources and operational environments.

Compilation challenges often arise during such substantial code revisions. The MQL5 platform may not fully support MAKE compilation systems, necessitating careful attention to dependency management and incremental code changes. Addressing compilation errors requires an iterative approach, focusing on primary errors and gradually resolving subseque...
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Financial time series prediction often utilizes dimensionality reduction techniques due to high feature correlations. While PCA is commonly employed, it can dilute individual variable impact, complicating tasks like feature selection. To tackle this, Forward Selection Component Analysis (FSCA) offers a more refined method by selecting variables based on their unique variance contribution. FSCA's backward refinement step further optimizes variable choice by replacing less important ones, enhancing model accuracy without sacrificing step order. These techniques empower traders and developers to build more transparent and effective algorithmic trading models, highlighting how FSCA addresses PCA's limitations in highly correlated datasets.
#MQL5 #MT5 #Algorithm #FeatureSelection

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