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.

👉 Read | VPS | @mql5dev

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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.

👉 Read | AppStore | @mql5dev

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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.

👉 Read | Docs | @mql5dev

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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...

👉 Read | Signals | @mql5dev

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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.

👉 Read | CodeBase | @mql5dev

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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.

👉 Read | NeuroBook | @mql5dev

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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.

👉 Read | Signals | @mql5dev

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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.

👉 Read | Docs | @mql5dev

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In the previous discussion, the focus was on templates and their efficiency in solution implementation. Moving from templates, we now turn our attention to structures within MQL5 programming. Structures serve as a critical building block, surpassing basic variables and approaching a more organized form of code.

Understanding the distinction between a structure and a union is crucial. A union shares memory among its elements, whereas a structure assigns unique memory spaces. This makes structures essential for complex variable management, allowing multiple elements within a single unit.

A common misconception among beginners is neglecting the design purpose of structures. They are more than convenience; they fulfill specific roles that necessitate understanding of their utility. Certain features seen in languages like C++ are missing in MQL5, often due ...

👉 Read | Freelance | @mql5dev

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Explore the transformative journey of developing custom trading signals for MetaTrader 5 using the MQL5 Wizard. This tool enables rapid prototyping of Expert Advisors, even for those with limited coding skills. By embracing its modular design, robust risk management, and pre-optimized components, developers can efficiently create and integrate personalized candlestick pattern signals into trading strategies. Key challenges such as class visibility within the Wizard are tackled by ensuring proper metadata configuration and adherence to structural standards. Discover how this innovative approach not only simplifies algorithmic trading development but also enhances precision and adaptability in creating effective trading systems.

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In our continued examination of MQL5, an advanced script is set for implementation. Focusing on candlestick data retrieval from platforms via MQL5's API, we aim to obtain detailed data beyond just current prices. This includes time, open, high, low, and close prices across multiple candles. Upon retrieval, each data type will be stored in separate arrays to enhance data management capabilities.

Utilizing WebRequest, our project initiates data extraction by querying comprehensive candlestick information. This involves configuring the method to GET, building the correct URL structure, and parsing returned JSON data into separate arrays. This facilitates precise data analysis.

Key to success is understanding the structure of returned data, storing them systematically, and ensuring your WebRequest setup accurately reflects server requirements. Methodical p...

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