The discussed tool offers a comprehensive statistical overview for traders, highlighting both daily and all-time metrics. It provides key features such as viewing statistics over the past 7 days with customizable settings and a cumulative summary of trading histories. Real-time updates automatically refresh data during trading activities, ensuring up-to-date information. The tool employs a color-coded system for quick identification of profit or loss days, enhancing readability with a modern flat UI that supports color customization. Numerical data is displayed in a professional format, with commas aiding clarity.

The tool tracks various metrics, including total lots traded, order count, and net profit or loss, comprehensively covering swaps and commissions. Each trading day is logged in the YYYY.MM.DD format, alongside pertinent details such as t...

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Refinement and Testing in Table Models:

Development of table models advances with refining methods to manage columns more efficiently. New initialization methods include creating models from arrays, matrices, and linked lists, enhancing adaptability for various data scenarios. Transferring classes to separate include files allows for better organization and modularity. Enhancements to CListObj facilitate new object types, providing robust functionality across different data forms. The CMqlParamObj class aids in versatile data handling, accommodating multiple data types and properties seamlessly. These improvements underpin a universal model architecture, paving the way for adaptable, task-specific data representation.

Table Header and Class Structure:

The table header class facilitates dynamic column management, linking headers with column numbe...

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Enhancing black-box models for trading strategy selection presents complex challenges. Traditional metrics like RMSE often mislead due to sensitivity to scale and lack of comparability across regression targets. Mutual Information (MI) offers a more robust alternative. Its nonparametric nature and unitless measurement provide a consistent comparison across targets, helping identify the most informative strategies.

Empirical results demonstrate MI's superiority. Models predicting changes in the Stochastic oscillator show marked improvements, reflecting market width better than others. Visual analysis through scatterplots and bar plots further validate these findings, reinforcing MI's reliability.

In application, a neural network model, backed by ONNX, enables real-time strategy execution in MQL5, leveraging newfound insights for improved decision-ma...

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Delve into the world of Kagi charts, an insightful Japanese innovation, now being translated into a cutting-edge algorithmic trading system using MQL5. Unlike traditional charts, Kagi charts highlight real market trends by altering direction based on price movement, rather than time, minimizing noise for clearer trend analysis. This two-part series provides a comprehensive guide: Part One introduces crafting a live, responsive Kagi chart utilizing MQL5's graphical capabilities for precise market insights, while Part Two expands to automated trading. Harness this method for superior market trend visualization and robust trading strategies, benefiting both developers and traders in enhancing their algorithmic trading frameworks.

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Explore the integration of Python-like time modules in MQL5 to enhance algorithmic trading capabilities. Addressing the limitations of native MQL5, this implementation introduces Python-inspired classes such as CTime, CDate, and CDatetime for efficient time manipulation, timezone handling, and accurate timestamp conversions. These additions facilitate sophisticated backtesting and time-sensitive systems in MetaTrader 5. The complete implementation is available for community collaboration on GitHub. Each module provides essential methods similar to Python's datetime, improving accessibility and precision in trading applications. Access the repository to explore these innovative tools for trading and development.

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Multi-timeframe analysis is essential for understanding market direction in trading. A lower timeframe signal can conflict with higher timeframe trends, leading to unreliable results. The Timeframe Visual Analyzer enhances this by overlaying two higher-timeframe candles on the current chart, maintaining market focus. This allows traders to confirm directional bias across timeframes and receive alerts when alignments are detected, offering settings for sound, push notifications, and emails. The tool ensures seamless chart integration with customizable visual styling and performance optimization, supporting traders' workflows without chart switching, aiding quick decision-making in dynamic market conditions.

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The Hidformer framework leverages a unique dual-tower encoder structure to effectively analyze and forecast complex multivariate time series, particularly beneficial for handling dynamic and volatile data. This framework excels in drawing out both explicit and hidden dependencies in the data through advanced attention mechanisms, enhancing the analysis of both temporal structures and frequency domains.

A significant feature of Hidformer is its recursive attention mechanism, which aids in capturing intricate temporal dependencies in financial data. The linear attention mechanism complements this by optimizing computations while maintaining training stability. Together, these components enable reliable forecasts, vital in high-volatility markets.

The model's multilayer perceptron-based decoder offers efficient sequence prediction, improving long-t...

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An Expert Advisor is available that systematically executes orders based on grid settings. It can place additional orders either with a constant or increasing lot size, depending on user-defined settings. The grid placement can also be tailored using RSI and CCI indicators, adding an element of signal-based decision-making to the strategy.

Positions can be closed upon reaching a specified profit level, or when a profit combined with an MA reversal is detected. The tool allows for the independent closure of Buy or Sell orders, or all open positions simultaneously. It also has the capability to autonomously trade based on signal detection.

Feedback regarding code errors or optimization suggestions is welcome for further refinement and enhancement of functionality.

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Explore advanced strategies in MetaTrader 5 with a focus on bidirectional communication using sockets. Transition from simple data transfers to controlling MetaTrader with external data inputs. Unlike RTD or DDE, sockets offer reliable, sequence-guaranteed data flows with TCP or rapid message dispatch with UDP, depending on your needs. Develop robust applications by building a Client-Server model that integrates real-time data exchange. Practical socket application enhances chart signals and trading decisions without native server support in MQL5. Elevate your algorithmic trading capabilities by mastering these communication methods and expand your market analysis toolkit.

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The introduction of an optimization project creation script has shifted project development towards efficiency. Rather than manually setting tasks, a template-driven script offers a streamlined method for creating optimization projects tailored to diverse trading strategies. The main achievement is an operational solution allowing new strategy groups to be exported directly to a separate EA database, distinguishing it from the previous optimization database.

The transition to a new project file structure has further simplified processes. By consolidating common code into a library separate from project-specific files, maintenance and scalability are enhanced. Each project retains its unique files while relying on a shared library for common functionality.

Auto update functionality in the final EA is a key enhancement. It enables dynamic loading of updated ...

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Unlock the potential of MetaTrader 5 beyond traditional forex trading by exploring diverse assets like ETFs, equities, and commodities. The article reveals how traders can identify the best indicators for algorithmic trading by using data-driven approaches. Experiment with high-momentum ETFs, such as VGT, using MetaTrader 5 to assess and identify effective indicator pairings. Utilize statistical methods like Kendall’s Tau and Distance Correlation to evaluate the independence of indicators and avoid redundancy. This approach enables developers to craft more robust trading strategies, maximizing efficiency while minimizing resource waste. Explore innovative trading insights and refine your edge with precise technical methodologies.

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Accelerate your financial ML pipeline by tackling computational bottlenecks with intelligent caching solutions for MetaTrader 5. By persisting intermediate results and introducing custom key generation, AFML reduces strategy optimization time from hours to minutes. Dive into advanced caching patterns to enhance cross-validation efficiency and prevent test set contamination. Effortlessly integrate with existing projects via decorator patterns without complicated configurations. Transition smoothly from research to production with rapid feature engineering, robust cross-validation, and efficient backtesting while maintaining data integrity. Unlock reduced computation latency to iterate and deploy sophisticated ML strategies in live trading environments effectively.

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In Part 42, a customizable Session-Based Opening Range Breakout (ORB) system is developed in MQL5. The system captures true high and low during defined session times and identifies breakouts with multi-bar confirmation to minimize false signals. Trades are executed in the breakout direction with configurable stop-loss and take-profit options. The system incorporates dynamic or static risk-reward management and can utilize trailing stops upon reaching a profit threshold. Visualizations include range markers and entry signals for clarity. Implementation involves defining session times, range calculation, breakout identification, and position management, ensuring adaptability for various market sessions.

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