A tool has been developed to calculate lot size based on risk percentage and stop-loss level. Users can set a virtual stop loss by clicking on the chart, which will calculate the lot size corresponding to the applied risk percentage. In the input section, users need to specify whether the calculation should be for a buy or sell position, determining if the risk is calculated from the ask or bid price. Longer stop-loss distances on higher timeframes carry more risk due to the larger scale of price points. This tool functions with all types of securities and directly calculates the lot size from the risk percentage and stop-loss distance. Note, it does not account for the maximum tradeable lots allowed by account size and leverage. For that, use the max trade volume script.
#MQL5 #MT5 #LotSize #RiskMgmt

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In a recent update on trading EA development, significant changes were made focusing on performance and reliability. The Chart Trade feature was removed from the EA, leaving a basic order system. Quick trading options are now available via MetaTrader 5, though they lack integration with the cross order system, underscoring the need for Chart Trade as an independent indicator rather than as part of the EA code.

To maintain system cohesion, Chart Trade is being developed as a separate indicator, enhancing order and position management without burdening the EA. This transition aims to streamline operations while retaining core functionalities. Modifications are underway to ensure compatibility, simplifying the system architecture while retaining essential capabilities.
#MQL5 #MT5 #EA #Indicator

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An indicator is available that computes and displays the exponential moving average (EMA) of the true range, along with an offset of the EMA of its deviation. The implementation utilizes conditional compilation, ensuring compatibility with both MQL4 and MQL5 environments. Additionally, all source codes from previous CodeBase publications are now accessible in the "Public Projects" section of MetaEditor, identified by the name "FMIC". This resource offers developers a streamlined way to access, examine, and integrate advanced coding solutions into their projects, reinforcing efficiency in trading strategies.
#MQL4 #MT4 #Indicator #EMA

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Explore the use of evolutionary optimization methods in MetaTrader 5 for trading model development. Unlike gradient-descent, these methods don't require differentiable model functions. They are inspired by Darwin's evolution theory, utilizing concepts like heredity and natural selection. The genetic optimization algorithm is particularly effective for non-differentiable functions or those with explosive gradients. Practically, the MQL5 implementation allows for parallel model operations, enhancing resource management and optimization speed. This approach optimizes trading strategies by selecting top models and introducing probabilistic mutations, ensuring adaptability and innovation in algorithmic trading environments. Embrace advanced strategies for efficient, adaptive trading systems.
#MQL5 #MT5 #algorithm #AI

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The Super Trend - Simple custom indicator has been enhanced to include multiple types of signal notifications. When the line color changes, users can now receive a sound alert, an email, or a push notification. This addition allows for timely updates and improved monitoring of market conditions. The ability to choose from various signal types offers flexibility in responding to market movements. This feature broadens the usability of the indicator by informing traders immediately of trend changes, thereby facilitating better decision-making and strategy adjustments. Adjust the notification settings according to personal preferences to optimize trading workflow.
#MQL5 #MT5 #Indicator #Alerts

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The article presents a streamlined method for traders to automate their trading journal using Google Sheets, reducing errors and saving time. It outlines the creation of a Google Apps Script to facilitate data entry via HTTP POST, allowing real-time updates without manual inputs. The system leverages Google Sheets' collaborative features, making it easily accessible for analysis and feedback among traders. Additionally, it covers reading data from Google Sheets using HTTP, with practical applications in the MetaTrader platform. This setup helps traders focus on improving strategies by automating data handling, providing a robust tool for performance evaluation and enhancement.
#MQL5 #MT5 #Algorithm #Trading

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An innovative approach involves displaying a candlestick chart without shadows in a subwindow. This unique representation provides a streamlined view, focusing solely on the body of the candles. Accompanying this, the 'Custom Moving Average' indicator is applied both to the main window and the subwindow, showcasing consistent analytical metrics across different chart views. This setup assists in simplifying analysis by emphasizing price movement within the candlestick bodies rather than fluctuations suggested by shadows. It can be useful for those looking to minimize noise and focus on primary price trends.
#MQL5 #MT5 #Indicator #Candlestick

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Explore the cutting-edge methodologies in algorithmic trading using Python and MetaTrader 5 tools. This article delves into constructing a machine learning model crafted to refine price forecasting and trading efficiency. The cornerstone lies in feature engineering, from clustering via Gaussian Mixture Models to leveraging XGBoost classifiers for superior accuracy. GridSearchCV optimizes hyperparameters, while model ensembling amplifies classification precision to 73%. A custom Python tester evaluates profitability, accounting for spreads and commissions, ensuring expected market outcomes. This technical exposition provides traders and developers with actionable insights on creating robust, profitable trading models using advanced machine learning techniques.
#MQL5 #MT5 #AITrading #Python

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Discover how to leverage Markov Chains to optimize RSI-based trading strategies in MetaTrader 5. This article explores transforming state definitions from moving averages to Relative Strength Indicator (RSI) values, showing how to build custom Markov Chains for adaptive trading rules. Learn how this statistical approach dynamically adjusts based on your market data, offering tailored insights for different assets. By employing a transition matrix, gain a sophisticated understanding of market trends, enhancing decision-making accuracy. Follow along to see the practical development of an MQL5 Expert Advisor and the testing of this probabilistic model against deep learning methods. Ideal for traders and developers seeking advanced algorithmic solutions.
#MQL5 #MT5 #MarkovChain #Algorithm

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Auto Profit Closer is an Expert Advisor that automates the process of closing open trades upon reaching a set profit target. It features the parameter "TargetProfit," enabling users to specify the desired profit level. This tool is well-suited for traders aiming to lock in profits without the need for continuous market supervision. It provides greater control over one's trading strategy by ensuring gains are secured effectively. The application is structured to enhance trading efficiency, helping to reduce the emotional stress often associated with manual trading. It streamlines decision-making, offering traders a practical solution for managing trading objectives more effectively.
#MQL4 #MT4 #EA #Trading

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The recent discussion illustrates modifications to MQL5 library classes for theme management, enhancing GUI components like CDialog, CEdit, and CButton. Modifying built-in libraries can both improve and negatively impact platform features, so proceed with caution. The integration revolves around theme-switching methods to adjust text, button skin, and background colors.

Incorporating methods into CDialog, CEdit, and CButton facilitates theme adaptability through color definitions and dynamic updates, promoting visually appealing design. The Admin Panel's algorithm was adjusted for seamless theme switching, maintaining efficient functionality.

This exploration serves educational purposes, emphasizing careful execution and testing of modifications to prevent potential issues in trading applications.
#MQL5 #MT5 #ThemeMgmt #MQL5

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Exploring optimal time frames for EURUSD prediction, the study assesses model error across 11 frames, revealing minimal error on monthly and hourly frames. An intriguing find is Granger causality between hourly and monthly returns, harnessing a VAR model for prediction. Using MetaTrader 5, the data is fetched and analyzed, focusing on the correlation and error distribution. Advanced techniques like Time Series Warping align time series data, and parameter tuning enhances model accuracy. Implementation in MQL5 allows flexible trading strategies through ONNX-exported AI models, adapting to technical analysis indicators for trade execution on the MetaTrader 5 platform.
#MQL5 #MT5 #AITrading #TimeFrames

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The Perfect Seconds chart indicator offers a practical solution for transforming live minute candle data into second-based charts. It permits the selection of various seconds durations to close bars precisely, providing live OHLC data that operates seamlessly without the necessity of tick availability. The code is fast and optimized, requiring no external DLLs, making it suitable for VPS environments.

This indicator supports cryptocurrency pairs like Binance and Kucoin, as well as futures and traditional financial instruments including gold and forex pairs. It includes functionalities to manage symbols and rates efficiently. Removal of a specific line of code from OnInit and OnCalculate may be necessary to address operational issues.
#MQL5 #MT5 #Indicator #AlgoTrading

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Explore the world of HTTP headers and their crucial role in client-server communication. This article focuses on understanding and implementing headers in HTTP requests and responses. Learn the essential functions of headers like Authentication, Cache Control, and Content-Type specification for secure and efficient data exchange. Discover how MetaTrader 5 automatically manages certain headers and how to customize them. This deep dive includes practical coding examples in MetaTrader 5 for adjusting headers and introduces the development of a class for managing HTTP headers. Enhance your understanding of protocol nuances to optimize algorithmic trading operations.
#MQL5 #MT5 #HTTP #Coding

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Developing a risk manager class involves setting parameters to control trading losses on a daily and total basis. The implementation starts with defining balance-related metrics such as base balance, daily base balance, and daily level. Trading should be suspended when exceeding predefined loss limits, with parameters set as fixed values or percentages. The CVirtualRiskManager class manages this process, handling maximum daily and total loss calculations, and providing methods to update profits and positions safely.

The class ensures that the risk manager's state adjusts to trading conditions and supports programmatic implementation for both manual and algorithmic trading. Additional modifications to existing systems integrate these risk management functions, enhancing overall trading strategy resilience. Testing with model strategy parame...
#MQL5 #MT5 #RiskManagement #TradingStrategy

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The article provides a step-by-step guide to creating an Expert Advisor (EA) in MetaTrader 5 using MQL5, based on the PIRANHA strategy, which leverages Bollinger Bands for market volatility analysis. The PIRANHA strategy is dynamic, designed to exploit market fluctuations by identifying potential entry and exit points. Key to its approach is the use of a 12-period Bollinger Band with a 2-standard deviation setting for efficient price movement tracking. The article details the coding process, focusing on creating indicator handles, initializing data arrays, and incorporating risk management through systematic stop-loss and take-profit settings. This comprehensive guide assists developers and traders in efficient EA development.
#MQL5 #MT5 #EA #BollingerBands

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We've released MetaTrader 5 platform build 4620, which introduces new MQL5 methods and addresses a number of subtle issues:

- In the terminal, we've fixed errors with tick history requests, where incomplete historical data could be returned in certain cases.
- The search autocomplete function now works correctly and is case-insensitive in all languages.
- Descriptions of new OpenBLAS methods for high-performance computing are now available in the MQL5 documentation.

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This tool enhances multi-timeframe chart analysis by allowing you to locate specific candles efficiently. It includes an option to convert server time to local time, displayed as a tooltip. For better navigation, press [Ctrl] or [Shift] while moving the mouse on the chart to reposition the custom crosshair cursor. Key parameters include showing local time, setting the cursor color, and using a unified cursor name synchronized through terminal global variables. This utility is designed to streamline your chart examination process without unnecessary complexities.
#MQL5 #MT5 #Indicator #Cursor

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When dealing with categorical data in machine learning, nominal variables present challenges due to their lack of inherent numerical ranking. Unlike algorithms that natively handle these types, others, especially linear models, require numerical inputs, making conversion to ordinal variables a necessary step. This process assigns a meaningful order and enhances model interpretability and effectiveness.

Nominal variables, such as price bar types or days of the week, typically lack an inherent order, which can mislead algorithms if not correctly handled. On the other hand, ordinal variables possess a natural order, aiding in capturing underlying relationships. Converting nominal variables to ordinal formats helps in imposing a structured form which improves the model's ability to discern patterns.

Various techniques assist in this conversion to preserve data...
#MQL5 #MT5 #ML #AITrading

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The ADX indicator is key for assessing trend strength, using DI+ and DI- to gauge directional momentum. DI+ above DI- suggests possible uptrends, while the opposite indicates downtrends. Parabolic SAR identifies potential reversals, with volume divergence refining signals. A SAR flip with reduced volatility often hints at continuation, while increased volatility confirms trend changes. Using SAR on weekly charts provides broader trend insights, aiding in aligning strategies across timeframes. For precise trade entries, consider both higher and lower timeframe SAR signals. Combining SAR with RSI can filter false signals, enhancing accuracy. Implementing these strategies requires careful coding and testing.
#MQL5 #MT5 #Trading #Indicator

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