The African Buffalo Optimization (ABO) algorithm, introduced in 2015, is a metaheuristic strategy inspired by the social behaviors and adaptive capabilities of African buffaloes. The algorithm incorporates key buffalo behaviors such as group communication and learning, adapting these principles for optimization processes. It starts by initializing a population of buffaloes, with each buffalo acting as a potential solution. Solutions are evaluated using fitness functions, and positions are updated based on signals "maaa" for exploitation and "waaa" for exploration, guided by specific equations.

The core components of the ABO algorithm are the S_Buffalo structure and C_AO_ABO class. S_Buffalo represents each buffalo as an agent with a movement vector, and allows parameter adjustments through its constructor and SetParams method. The C_AO_ABO class m...

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The recent advancements in point cloud processing are exemplified by the development of the Mask-Attention-Free Transformer (MATF). The method reframes traditional Transformer-based approaches by eliminating the mask attention design. Instead, it incorporates an auxiliary center regression task to enhance the convergence speed and accuracy of object segmentation. This novel approach effectively uses positional queries and contextual relative position encoding in the cross-attention mechanism, addressing the challenges of slow convergence and poor initial mask quality. The MATF approach shows superior performance across various datasets and effectively reduces training complexity while maintaining flexibility and robustness in 3D instance segmentation.

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Discover comprehensive details about MetaTrader 4 build 2140 and MetaTrader 5 build 3802. Staying updated with the latest builds ensures access to new features and platform security enhancements. System stability has been prioritized with optimized performance metrics. Important attention to bug fixes and improved interface adaptability for a seamless user experience. Developers and traders should review changelogs for essential updates impacting algorithmic trading scripts and indicators integration. Recognizing the necessity of maintaining updated programming environments is crucial for enduring operational productivity and achieving effective trading results.

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This text lays out the framework for developing a custom logging system designed to enhance the debugging and profiling of trading algorithms in MQL5. Traditional methods like using Print() lack robustness, failing in larger projects due to their inability to manage log severity, context, outputs, and filters. This makes custom toolkits invaluable.

The proposed framework begins with building a logging system composed of LogLevels to classify severity, an ILogHandler interface to manage different outputs, and a singleton CLogger orchestrator. These components work together to improve message clarity, filtering, and contextual information.

Implementing specific log handlers, such as ConsoleLogHandler and FileLogHandler, allows for flexible logging solutions like writing logs to console or files. These handlers provide customization options for log severity lev...

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In the automation of the Grid-Mart Scalping Strategy using MetaQuotes Language 5 (MQL5), the development of an Expert Advisor focuses on executing grid-based Martingale trades. This task involves creating a dynamic dashboard for real-time monitoring. The strategy utilizes a grid-based Martingale approach to capture market fluctuations, requiring precise configuration and risk management. Implementation involves declaring global variables, managing trade execution using the CTrade object, and defining inputs for grid intervals and lot scaling. Risk controls include drawdown limits and grid size restrictions. The dashboard visualizes trading metrics with interactive elements, providing an intuitive user interface for monitoring and decision-making.

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The intersection of financial news and AI presents significant trading opportunities. Begin by gathering comprehensive news data, ensuring factors like timeframe, symbols, and handling NaN values are considered. Utilize MetaTrader 5 for collecting relevant data, including OHLC values around news events.

Prepare the dataset by cleaning and structuring it, focus on encoding categorical variables to support machine learning processes. Splitting data into training and testing sets is crucial. LightGBM emerges as an efficient choice for modeling due to its decision tree base, handling both categorical data and bias effectively.

The model shows strong predictive capabilities. Use tools like SHAP to analyze feature impacts. Export the model to ONNX format for practical deployment. Combining AI models with news can enhance algorithmic trading strategies but...

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Explore the intriguing Artificial Ecosystem-based Optimization (AEO) algorithm, inspired by natural ecosystems and their intricate interactions. AEO mimics ecosystems with a diverse population of solutions, each adapting to its niche, using energy transfer through simulated agents like "herbivores", "carnivores", and "omnivores". This method optimizes solution quality by updating decisions through competition and cooperation strategies. It balances exploration and exploitation by incorporating stochastic and deterministic elements, utilizing techniques such as Gaussian and Levy distributions. Perfect for algorithmic traders and developers, AEO provides novel techniques for solving complex optimization problems with practical applications in trading systems.

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XAUUSD is a key trading instrument in the forex market, known for its volatility and potential returns. However, the impact of economic news events like Non-Farm Payrolls or Fed interest rate decisions can lead to abrupt price fluctuations, affecting automated trading strategies. This prompts the need for a News Filter in an Expert Advisor to pause trading during high-impact news.

News events related to USD, GBP, or EUR often result in significant XAUUSD price movements. An effective News Filter can temporarily halt trading, thus reducing risk and improving trading consistency. It acts by holding trades before and after major news to mitigate exposure to market swings.

The filter's functionality involves a simple MQL5 code snippet incorporating variables like MinutesBeforeNews and MinutesAfterNews to specify when trading should pause around predefined news tim...

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This indicator calculates a multi-day Volume Weighted Average Price (VWAP), which starts from the daily timeframe by default but is fully customizable. VWAP is beneficial for pinpointing support and resistance levels, confirming trends, and identifying mean reversion signals. Unlike simple averages, VWAP indicates the average price weighted by volume over a set period, essential for institutional insights. It dynamically updates the VWAP level and includes market close prices plotted with the Heiken Ashi trend for visual trend analysis.

In a downtrend, when the price is below VWAP, it acts as resistance, indicating seller control. In an uptrend, when the price is above VWAP, it acts as support, indicating buyer dominance. Momentum is suggested when the price moves strongly away from VWAP, signaling potential trade opportunities. Breakout signals occur whe...

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The new installment in the MQL5 Economic Calendar series introduces enhancements to optimize news-driven trading systems. The focus is on implementing a visual chronograph for efficient event processing and logging. This setup integrates smart event filtering and targeted logging to streamline backtesting, achieving faster and clearer results akin to live trading conditions.

In MQL5, the trading library inclusion facilitates seamless trade execution. The event filtering mechanism pre-selects crucial news events within defined date ranges, significantly reducing computational load. The introduction of a unified dashboard for both live and offline testing enhances the strategy development process by providing unobstructed visualization.

Enhanced backtesting is enabled by loading historical news events as resources, ensuring robust event datasets. Efficie...

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The previous exploration revealed the intricacies of managing time tracking in low-liquidity scenarios within MetaTrader 5. A highlighted issue was the dependence on the OnCalculate event, which limits updating the mouse indicator when liquidity is low or during auctions.

The primary challenge is ensuring accurate timing updates regardless of trading activity. Proposed solutions include modifying service code to accommodate low-liquidity environments, deploying test services to assess feasibility, and utilizing 32-bit spread values to transmit time information effectively even during periods of sparse trading.

Strategically, integrating bit-level control in the spread values offers a sophisticated, resource-efficient approach to monitor and relay time accurately, crucial for maintaining synchronization in the replay/simulation application. Adjustm...

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Educational content helps programmers comprehend fundamental concepts. The prior article, "From Basic to Intermediate: Arrays and Strings (II)," demonstrated practical applications for array and string manipulation, accessible even for beginners. Despite its simplicity, the article’s applications reveal a common beginner's pitfall: understanding why simple text manipulations work.

Understanding data translation is central in programming, where computers interpret binary data into human-readable formats. Early processors dealt with BCD systems, but transitioning to binary operations proved more efficient. Thus, programmers often handle numeric translations, using ASCII tables and similar encodings for data manipulation.

MQL5 showcases translation functions, yet developing comprehension of data manipulation basics enhances programming acumen. Understan...

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A refined version of the GARCH volatility indicator is now available. It incorporates various enhancements designed to improve the accuracy and reliability of volatility estimations. These updates optimize the algorithm's ability to model financial markets' volatility changes, providing users with a more precise analytical tool. The improvements address previous limitations, offering a more stable and responsive performance. This version aims to facilitate better risk management and decision-making processes for analysts and traders. Users can now experience increased confidence in volatility forecasts, critical for strategic market assessments.

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Explore the power of execution algorithms in MQL5 for seamless trading! Discover how TWAP, VWAP, and Iceberg Orders can transform your strategy by mitigating slippage, enhancing execution precision, and ensuring minimal market impact. Each algorithm serves a specific trading environment: TWAP for stable markets, VWAP for volume-predictive trades, and Iceberg for minimizing visibility in illiquid settings. Our implementation and detailed performance analytics allow seamless integration within your automated scripts, offering optimized order execution and strategic flexibility. Elevate your trading efficiency by implementing these sophisticated algorithms, once exclusive to institutional investors, using advanced yet accessible MQL5 code.

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3D Referring Expression Segmentation (3D-RES) is advancing with a method called 3D-GRES, tackling challenges of interpreting instructions involving multiple targets in real-world scenarios. Traditional 3D-RES models fall short in addressing cases with no matching target or multiple objects, limiting their practical use. 3D-GRES aims for a comprehensive approach, utilizing a Multi-Query Decoupled Interaction Network (MDIN) to enhance interaction between queries and superpoints, thus managing multiple targets effectively. Additionally, the Text-Guided Sparse Query (TSQ) and Multi-Object Decoupling Optimization (MDO) strategies ensure distinctiveness and semantic consistency across queries. This approach fosters accurate multi-object identification within complex scenes.

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Discover how Fibonacci retracement levels can transform trading strategies using MetaTrader 5 with a focus on machine learning. Gain insights into generating target variables with Fibonacci sequences for both classifier and regressor models. Learn to train and utilize Random Forest models to predict market trends. See how these models fare when applied in a strategy tester to assess their effectiveness in real trading environments. The results highlight the potential of integrating Fibonacci-based insights with algorithmic trading to optimize strategies, offering a practical approach for traders and developers seeking to enhance their understanding and performance in the market.

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To define a range based on specific parameters, focus on the time frames and size conditions. The Range Start Time and Range End Time establish the initial boundaries for range creation within a specified period. The Trade End Time extends the high/low lines of the range zone to a predetermined point, providing a clear visual guide for traders. Size constraints are crucial; ranges must fall between the Minimum Size and Maximum Size. Should the range size be within these limits, the indicator will display the first designated color (blue), allowing for quick identification of suitable trading zones. This approach aids in maintaining consistency when establishing trading ranges.

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The BBMA trading strategy, created by Malaysian trader Oma Ally, integrates Bollinger Bands with Moving Averages to pinpoint trading opportunities. It is distinguished by its precise entry points and capacity for managing multiple entries, making it adaptable for markets such as Forex, stocks, and cryptocurrency. This approach leverages the analytical power of both tools to enhance decision-making in various trading environments. The strategy’s focus on precision and versatility increases its applicability across different financial markets, providing traders with a structured method to navigate complex market conditions effectively.

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The range creation process requires precise inputs for accurate results. Start by setting the Range Start Time to define when data collection for the range begins. Next, determine the Range End Time to conclude this period. The Trade End Time indicates the duration until which the range boundaries (high/low) will remain visible on the chart.

A crucial parameter is the range size, expressed in points. Define both Minimum Size and Maximum Size to establish acceptable boundaries. When the calculated range size falls within these specified limits, the system will visually represent this range using the first color, blue. Proper configuration of these parameters is essential for enhanced trading analysis and effective decision-making.

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BBMA is a trading strategy gaining attention in the financial markets, notably developed by Malaysian trader, Oma Ally. This strategy effectively utilizes Bollinger Bands in conjunction with Moving Averages to pinpoint trading opportunities with precision. Renowned for its capability to manage multiple entry points, the BBMA strategy is adaptable to various financial markets, including Forex, stocks, and cryptocurrencies. Its application promises enhanced precision in entry, making it a favorable choice among traders seeking reliable methods to navigate volatile market conditions. Its multifaceted approach caters to traders aiming for versatility across asset classes.

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Understanding currency strength is crucial for forex trading. This EA analyzes individual currency movements across multiple pairs and timeframes (M15, H1, H4) using parameters like Lookback_M15, Lookback_H1, Lookback_H4, and Update_Seconds. It calculates a single strength value for each currency by averaging percentage changes. The dashboard updates frequently, providing current strengths and visual curves for account equity and drawdown.

Our development uses MQL5 to assess currency strength reliably. We track major currencies across pairs, compute percentage changes, normalize signs, and average results to generate strength scores. This methodology identifies strong and weak currencies, aiding confident trading decisions based on real-time market data.

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