This analytical indicator evaluates whether price time series follow a Gaussian "random walk," allowing for parametric transformation of price increments into stable time series, primarily focusing on volatility. It measures the expected distance of a "random walk" using standard deviation calculations, helping traders understand market movements. It averages price changes for predefined sub-ranges using an exponent factor F, ranging from 0.1 to 1, to find uniform distribution.

The indicator uses methods such as minimum variance, differences between the triple M's, and Gini coefficient to determine statistical "regularity." Applications include data normalization for machine learning, optimal bar sampling in volatility trading systems, and anomaly detection in symbols or timeframes. Parameters include Period, Factor, Method, and MaxBars, with the opt...

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Explore advanced algorithmic trading with an MQL5 trade layering strategy, combining MACD and RSI, elevated by statistical analysis. This sophisticated approach dynamically scales positions in trending markets, leveraging momentum for compounded potential gains. Emphasizing precision, the strategy utilizes MACD for trend confirmation and RSI for optimal entry points, with statistical methods enhancing signal fidelity. Developers can implement the architecture in MQL5, with detailed steps for coding and backtesting. This robust Expert Advisor provides a powerful tool for algorithmic traders, ensuring strategic layering of trades and maximizing market opportunities while maintaining controlled risks. Ideal for developers seeking to refine trading algorithms in MetaTrader 5.

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The article delves into optimizing replay simulations in MetaTrader 5, specifically addressing timing challenges when combining real and simulated tick data. It examines determining the minimum tick number required, focusing on key criteria like price dynamics that dictate simulation needs. A critical update involves allowing user-configurable tick limits in configuration files, enhancing flexibility and system performance. The article also details necessary code adjustments in key files such as C_Simulation.mqh and C_FileTicks.mqh to ensure accurate data representation and memory management. These improvements facilitate a seamless experience for traders and developers in algorithmic trading by addressing errors and enabling effective system testing and maintenance.

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The article discusses a method for optimizing trading strategies in MetaTrader 5 by selecting and grouping individual strategy instances for improved performance. Two approaches are considered: full optimization over a period and selecting strategies based on similar results in a shorter interval. The latter demonstrated better results, especially when automated through a genetic algorithm, despite initial database management issues. The article outlines implementing forward period testing to enhance strategy selection, detailing necessary database modifications and error fixes. This approach aims to optimize strategy grouping, ensuring robust strategies that maintain performance over different intervals.

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In recent developments around the replay/simulator application, a crucial fix was implemented regarding the unexpected automatic pause mode. The incident, initially perplexing, was traced to a custom event inadvertently modifying the OBJPROP_STATE property, misleading the service into pause mode. By leveraging the indicator buffer instead, performance impacts were minimized and the application's reliability improved while laying the groundwork for a future fast-forward feature.

Additionally, another critical issue involving memory dumps was addressed. Errors were traced back to unreleased objects of the C_DrawImage class, highlighting poor pointer management within the C_Controls class. By simply ensuring pointers are properly initialized and deallocated, stability was restored, emphasizing the importance of meticulous memory management in develo...

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The Expert Advisor (EA) utilizes the custom indicator RSI_MAonRSI_Filling where signals are defined by the intersection of the RSI and MAonRSI lines. Specifically, a crossing below the 50.0 line indicates a BUY signal, while a crossing above signals a SELL. The strategy emphasizes evaluating the distance from the current price to the nearest position via the 'Position Step' parameter, ensuring market entry is strategic.

Focus is placed on parameter optimization according to the selected 'Working timeframe' where indicators and new bar generation are defined. Single market entry per bar is enforced, disconnected from input parameters. Additionally, search modes define the bar context, with options ranging from 'every tick' to 'new bar'.

Trade direction is customizable with three modes: BUY only, SELL only, or both. Trading signals can be time-restricted usi...

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The "Text label" control is an essential graphical object for displaying text in program GUIs. It mirrors the functionality of MS Visual Studio's text label, with additional features for flexibility in positioning and resizing. Users have options to set font parameters, and enable the frame feature for visual distinction.

In efforts to enhance library classes, new text messages and indices have been introduced, alongside modifications to incorporate text opacity for visual effects. Adjustments to the class structures include updating properties to improve customization and sorting capabilities.

The development continues with revisions to base and derived classes to support new features. Testing has confirmed the effective integration of these enhancements, ensuring accurate text display.

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Introducing the Simple Slope Oscillator Normalized with symbol overlay for MT4. This technical indicator offers clear visualization of price movements. The Simple Slope Oscillator calculates the slope of an asset's price, providing traders with potential entry and exit signals by reflecting price momentum. Normalization helps in comparing slopes across different assets, making it a versatile tool.

The symbol overlay feature enhances analysis by providing visual context directly on the chart, reducing the need for multiple charts. This integration facilitates efficient monitoring of multiple currency pairs or assets simultaneously. Understanding the flow and impact of price momentum is crucial for effective decision-making. Enhance your MT4 toolkit with this oscillator to streamline trading analysis.

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Portfolio consistency and robust risk management are crucial in professional trading. Over-reliance on singular assets or strategies increases exposure during market shifts. Over-leveraging correlated instruments also heightens risk. A diversified, optimized portfolio mitigates emotional decision-making and volatile profitability. Implementing a systematic framework with multi-asset diversification and breakout trading strategies, confirmed by oscillators, ensures resilience. A breakout strategy across currency pairs capitalizes on momentum while diversifying risk. Validating entry signals with oscillators reduces false trades. This approach ensures portfolio stability and alignment with macroeconomic conditions. Employ rigorous execution, monitoring multiple symbols, and adjusting trade parameters for consistent performance.

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Object detection in point clouds is critical for applications like autonomous driving and robotics. Point clouds provide detailed geometric data but pose challenges due to their irregularity. The Pointformer model addresses these issues by combining Transformer-based architectures, which are effective in learning context-dependent representations, with a U-Net structure for efficient feature learning. The Pointformer architecture comprises Local, Local-Global, and Global Transformer modules that model dependencies on various scales. This approach harnesses both local and global information, improving feature extraction in complex scenes. Implementation in MQL5 involves creating new classes and methods to integrate Pointformer functionalities, leveraging existing structures like PointNet++.

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RadixSort algorithm efficiently organizes numeric data by sorting from the least significant to the most significant digit. This approach works well for both integer and float data types. The time complexity of RadixSort is O(n * k), where 'n' is the number of elements and 'k' represents the maximum number of bytes in the elements. The method iterates over each byte position to sort the data accordingly.

In conjunction with MQL, a highly-optimized LSD RadixSort implementation is available, leveraging radix 256 (8-bits). This version is capable of handling large arrays with millions of numbers efficiently. Stemming from Pierre Terdiman's work, it incorporates various optimizations for enhanced performance, attaining speeds of 3-10 times faster than MQL's native ArraySort() function.

This implementation accepts arrays of different types but sorts them b...

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Explore the realm of digital trade optimization with MQL5's advanced logging library! Discover how to enhance your Expert Advisors (EAs) with a dynamic logging solution that surmounts MetaTrader 5's default capabilities. Embrace the power of databases, moving beyond text files for efficient log storage and retrieval. This solution employs SQLite for streamlined, fast access to critical data, facilitating better performance analysis and refining trading strategies. Learn about essential database operations like creating tables, inserting, and retrieving data. Equip yourself with tools to transform data insights into actionable improvements, elevating your algorithmic trading experience. Unlock the future of EA optimization today!

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Discover a seamless way to backtest trading strategies in MetaTrader 5 by combining manual control with the precision of automation. This article breaks down a custom MQL5 Expert Advisor that transforms backtesting into an intuitive process. Key features include on-chart buttons for buying, selling, and adjusting trade parameters, providing traders with direct control over strategy testing at accelerated speeds. The toolkit leverages the "CTrade" class for efficient trade execution and integrates adjustable Stop Loss and Take Profit controls. Ideal for developers and traders, this solution enhances the efficiency and accuracy of strategy refinement within the Strategy Tester.

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Discover how MetaTrader 5 traders can leverage the Uniform Manifold Approximation and Projection (UMAP) for improved candlestick pattern detection. By employing UMAP, traders can unearth new, non-linear relationships in market data often obscured by high-dimensionality. The process reduces the complexity of market data descriptions, enabling clearer pattern recognition. Practical testing on EURGBP exchange rates shows error reduction using UMAP-transformed data. This approach offers a significant edge over traditional Principal Component Analysis, maintaining data integrity while uncovering latent patterns. For developers, seamless integration with Python and Numba facilitates efficient and robust computations on extensive datasets.

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An effective tool is available to assist traders in risk management and enhance EA capabilities for automated symbol selection. This indicator calculates the Average True Range (ATR) to determine average price movement per candle, presenting it as a percentage of the current price. By doing so, it simplifies the process of comparing different symbols, providing a clearer understanding of expected price fluctuations per candle. For example, the BCHUSD instrument typically shows a daily price movement ranging from 4.6% to 9.2%. This information facilitates informed decision-making and strategic adjustments in trading strategies.

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Opening Range Breakout (ORB) strategies exploit initial trading ranges. These reflect core price levels where traders agree on value. Detection of breakouts beyond these ranges often signals momentum shifts. The piece discusses three ORB strategies from Concretum Group papers.

The text details strategies, signal rules, and statistical analysis. There's focus on research rather than coding, ideal for those seeking trading insights. Strategies analyzed: Opening Candle Direction, VWAP Trend Following, and Concretum Bands Breakout. Each provides unique perspectives and trading edges, focusing on varying market conditions and research methodologies.

Evaluation spans 2020-2025, emphasizing approach consistency and adaptability across regimes and market conditions.

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Understanding currency correlations is crucial for optimizing forex trading strategies. This article delves into using correlation analysis to manage risk effectively. By focusing on the interdependencies between currency pairs like EUR/USD and GBP/USD, traders can diversify portfolios and apply hedging techniques. The described system employs an MQL5 Expert Advisor for retrieving historical data and a Python server for comprehensive analysis. Correlation metrics are calculated using Pandas, with insights visualized via Matplotlib. This approach helps identify market trends, providing clear signals for potential reversals. Such methodologies offer traders practical strategies to enhance market analysis and risk management.

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Enhancing MQL5 trading strategies with AI brings innovation and adaptability to a new level. By transitioning MQL5 logic to Python, traders can seamlessly integrate AI models like LSTM, allowing systems to analyze historical and real-time data for smarter trading actions. This blend of technical analysis with machine learning empowers strategies to dynamically adjust to market changes, improving accuracy and reducing false signals. By deploying a Python-based microservice, predictions align with trade executions on MQL5, enhancing decision-making with real-time data-driven insights. This hybrid approach optimizes trade execution, entry/exit, and risk management, benefiting both developers and traders.

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The SWITCH statement in MQL5 offers an efficient alternative to multiple IF statements when checking for exact matches. Unlike IF, which evaluates conditions as true or false, SWITCH evaluates numerically, comparing the expression to defined CASE values. The statement’s differentiating feature is how it manages execution flow; using BREAK ensures the block exits correctly. It’s integral to insert BREAK before each new CASE to maintain code clarity and flow efficiency. Understanding the switch from numeric to logical evaluation within the CASE block is crucial. This foundational grasp will aid in managing the SWITCH statement’s complex behavior and prevent misinterpretation.

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The new indicator enables the visualization of an arbitrary seconds timeframe on the chart. Users can adjust settings such as the number of days to display; however, excessive days may lead to prolonged calculation times. It offers a choice between viewing bars or candlesticks. Upon comparison with a reference utility, the candlesticks appear to be accurately drawn. It's crucial to understand that this is an indicator, not a comprehensive seconds chart. Integrating other indicators onto this chart isn't possible, as they will reflect the values of the primary chart timeframe, not those of the seconds representation. This should be taken into account when using the indicator for analysis.

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The multi-symbol indicator offers a streamlined method to assess price changes across various symbols listed in the Market Watch. Users define the timeframe with vertical lines, allowing for a clear comparison of market movements within specified dates. This feature is valuable for quickly understanding market dynamics and identifying trends.

The interface facilitates management, with date adjustments made using the mouse, while keyboard shortcuts enable swift symbol navigation. Such intuitive controls enhance user efficiency. Additionally, the indicator is designed to restart automatically upon launch or symbol change, ensuring uninterrupted functionality and up-to-date insights. This tool provides a practical solution for comprehensive market evaluation.

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