In recent updates on our replay/simulation application project, several refinements have been made to enhance system functionality. Although two primary bugs were resolved in the last session, a few minor issues still persist due to the transition from global terminal variables to new methodologies. This necessitates adapting and refining existing code rather than a complete overhaul. A key task addressed is reintroducing the fast-forward feature, which previously relied on now-obsolete global variables. By implementing a condition check within our control indicator functions, and adjusting select code snippets in our C_Replay.mqh file, the fast-forward mechanism now operates smoothly, addressing asynchronous issues between our service controls and user commands. Additionally, leveraging pre-built one-minute bars from the C_FileTicks class enables more e...

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Delve into the groundbreaking HyperDet3D algorithm, which revolutionizes 3D object detection by integrating scene-conditioned information into point cloud analysis. This approach rectifies ambiguities in object attributes using scene-level data, enhancing detection accuracy. The HyperDet3D model features a backbone encoder, object decoder, and detection head, which dynamically adjusts to varying input data. By leveraging scene-specific and scene-invariant knowledge, HyperDet3D ensures adaptive model performance. The innovative Multi-head Scene-Conditioned Attention module streamlines the fusion of prior knowledge with object features. Practical implementation in MQL5 facilitates the seamless application of these concepts for developers keen on advanced automated trading systems.

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CTsLogger provides a streamlined logging system tailored to MQL5 trading systems. It distinguishes itself by allowing selective debug mode activation, facilitating targeted diagnostics without overwhelming output. This feature enables detailed logging for specific components while keeping a leaner global log level, simplified further with the ability to toggle debugging with a single action.

The system emphasizes user convenience, offering straightforward initialization and intuitive logging function calls. Its modular design supports a hierarchical identification system, allowing logical organization of code sections, and boasts robust state management capabilities, such as pausing and resuming debug configurations without data loss. CTsLogger's resilience ensures operational continuity, even under file system disruptions, by falling back to terminal o...

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The outlined strategy involves taking short positions when the price reaches the high of n-lookback bars, aiming for a return to the mean of n-lookback. Conversely, it suggests going long when the price hits the low of n-lookback bars, with the target again being the mean. Utilizing this approach on one-minute OHLC data may lead to misleading simulations. The frequency of trades and the inherent noise in one-minute bars can distort outcomes. The strategy could be less reliable due to the high number of false signals typical in such short intervals. Thorough backtesting with robust data and risk management considerations is crucial before moving forward with such strategies.

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The current implementation of the Expert Advisor (EA) highlights some challenges and opportunities for improvement. Existing resources aid trading activities, yet issues with visualization and chart resizing persist, possibly causing screen clutter until refreshed. These drawbacks do not affect the trading functionality but could hinder user experience. Enhancements in volume analysis and order flow visualization are suggested, offering more precise tools for traders.

Accurate market behavior analysis often depends on evaluating price accumulation regions and tracking price movements with time-sensitive adjustments. Implementing a flexible tracking mechanism allows traders to better understand market tests versus trend reversals. By modifying the volume display functionality, capturing trades and price movements becomes clearer.

Chart resizing issues were ...

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The Currency Strength Meter for MetaTrader 5 provides users the ability to assess the relative strength of various currency pairs across different timeframes. This utility allows traders to make informed decisions based on the comparison of multiple currencies. Originally designed for MetaTrader 4, the tool known as "Currency Strength Giraia 28 pairs TRO MODIFIED" has been successfully adapted for MetaTrader 5. The configurable timeframe parameter adds flexibility, enabling users to adjust their analysis according to their specific trading strategies. This conversion enhances the usability of the renowned indicator, aligning it with the advanced features offered by MetaTrader 5 while maintaining its core functionality.

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Explore Kohonen Maps in MQL5 for innovative algorithmic trading. This article discusses using Kohonen Maps to translate complex multi-dimension price data into a simplified single-dimension format, facilitating more efficient trading decisions. Dive into technical details of creating classes and layers, including Feed, Functor, and Neuron classes, leveraging array lists and hash maps. The unique single-layer neuron structure differs from traditional networks, focusing on competitive learning for adjusting output. Practical insights on testing show how Kohonen Maps can refine quantization and topological errors, aiding traders in optimizing strategies through modeling and testing, providing promising results in dynamic market scenarios.

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Candle signature with example is a beneficial tool for traders in the research and development of identifying single candlestick patterns. It enables users to store these patterns and make inquiries to identify potential matches in the future. Utilizing datasets like open, high, low, close, and comment, traders can input custom values to search for similar candlestick patterns. The script employs a fuzzy matching algorithm to maximize the potential for pattern recognition. Users have the option to add a tolerance level, considering that exact pattern repetitions are uncommon. This feature enhances the script's utility for those looking to refine their trading strategies based on candlestick analysis.

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Unsupervised learning is gaining traction in AI, offering models the ability to train with only raw data, thus reducing the labor in preparing reference values. Compared to supervised learning, which depends on labeled data, unsupervised learning thrives on detecting patterns independently, useful in scenarios like anomaly detection or data dimensionality reduction. K-means clustering is a prime example, efficient for clustering tasks. It initializes random cluster centers and iteratively assigns data points based on proximity. The algorithm adjusts cluster centers until stability is achieved, and cluster evaluation can be done by analyzing the average deviation of points from their centers.

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A modified MQL4 indicator now includes an automatic Fibonacci feature. It streamlines technical analysis by automatically plotting Fibonacci retracement and projection levels using selected swing highs and lows. Users can select which swing index, such as the 1st, 2nd, or 3rd swing, to use as the Fibonacci anchor point. This enhancement removes the need for manual drawing while maintaining the accuracy of analysis. There is no claim on the rights of the original indicator; the modification solely aims to improve user experience by enhancing usability. This update facilitates more efficient and effective technical analysis.

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The Kuskus Starlight is a technical indicator designed for oscillator functions, leveraging a Fisher price transformation to aid traders in trend identification and market reversals. It normalizes over various periods and includes adjustable smoothing for custom responsiveness. This tool serves as a confirmation component within trading systems, enhancing trade signal validation. Initially discovered through platforms like Stonehill Forex and NNFX, it is acknowledged for confirming indicators within trading strategies, with origins linked to Stonehill Forex in 2007 and NNFX in 2017.

MT5 users now have access to the Kuskus Starlight indicator thanks to a newly coded version that adapts the original MT4 design, preserving its core algorithm. The MT5 adaptation remains aligned with the primary functionality intended by its MT4 predecessor. Indicator s...

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The tool serves as a monitoring system for Expert Advisors (EAs), allowing traders to efficiently track historical and current drawdown levels. By inputting expected historical maximum drawdown figures derived from backtesting or past trade data, traders have a clear visual benchmark for assessing EA performance. Real-time monitoring ensures that any breach of critical drawdown levels can be swiftly addressed.

The tool offers smart notifications, sending alerts via the MetaTrader app when new drawdown records are achieved, or at regular intervals set by the user. This facilitates informed decision-making without unnecessary message fatigue. Traders can also log drawdown data to external CSV or TXT files for post-trade analysis.

Geared toward users of automated or semi-automated trading systems, the tool is ideal for those needing to reconcile strateg...

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The Volume Oscillator measures market trends using two volume-based moving averages. It calculates the strength or weakness of a trend by analyzing price movements with volume changes. When the Volume Oscillator is above the zero line, it suggests that the current trend direction is supported by adequate volume, signaling a strong market movement either in an uptrend or downtrend.

Conversely, if the Volume Oscillator falls below the zero line, it indicates a weak market trend due to insufficient volume support. This could signal stagnation or a potential trend reversal. Negative divergences can often hint at an impending reversal. The indicator's oscillation between positive and negative values provides insights into the market's support for price movements. Understanding these signals helps in assessing the anticipated strength or weakness of ongoing tr...

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Discover a software solution tailored for MetaTrader 5 users. This tool facilitates market analysis by employing clusters for price action insight. The code repository offers a comprehensive example of integrating cluster-based analytical tools into trading platforms. It supports traders in observing the market environment, enhancing decision-making capabilities through more nuanced data interpretation.

Built with adaptability in mind, it is designed to adjust to varied trading strategies and preferences. Users can refine their understanding of financial markets and apply advanced analytics for trading advantage. It is a valuable resource for developers seeking to incorporate sophisticated analytical capabilities into their trading systems, enhancing overall system efficiency and data processing methodologies.

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In this article, we explore an innovative approach to revamping a MetaTrader 5 Admin Panel. Our focus is on transforming a complex, monolithic interface into a modern, resource-based system leveraging MQL5. By utilizing BMP image files as resources, we create a visually appealing, floating button interface, enhancing usability and interactivity without cluttering the trading chart. The panel's design integrates intuitive icons for expanded functionalities, streamlining user interactions. Key methodologies include embedding resources, implementing bitmap labels, and managing button visibility through toggle logic. This development not only showcases MQL5's graphical capabilities but also ensures a scalable and efficient user experience.

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Delving into the fusion of machine learning techniques and trading algorithms, this article explores the integration of supervised, reinforcement, and inference learning within the MetaTrader 5 environment. It emphasizes the importance of utilizing Variational Auto-Encoders (VAE) for efficient inference, leveraging encoders to compress and map features, states, actions, and rewards (FSAR) to latent spaces. Practical applications include adapting models to shifting market dynamics, optimizing historical data, and improving prediction accuracy through techniques like Wasserstein distance and Maximum-Mean-Discrepancy (MMD). Developers gain insights into robust model training, adaptive prediction methods, and enhancing algorithmic trading effectiveness without exorbitant storage costs.

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Trend Rider combines indicators such as Super Trend, RSI, and MACD. Its purpose is to assist in spotting and riding trends by displaying direction through color-coded candles and trailing stop levels. It can be employed independently or alongside other filters for enhanced decision-making.

The integration of these indicators aims to provide a clearer picture of market trends and facilitate better trading strategies. Super Trend helps identify the prevailing trend, RSI measures the market condition, and MACD highlights momentum shifts. Together, they offer a comprehensive toolset for traders seeking to optimize their trading outcomes. This approach enables users to systematically evaluate market volatility and trend sustainability, potentially improving transaction timing and performance.

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Technical advancements often aim to optimize user interaction and efficiency, especially when dealing with trading indicators. In modern trading platforms, professionals have noted the need for seamless interaction with indicators to better accommodate volatile market conditions.

A primary concern is the cumbersome process of adjusting indicator periods manually. This interaction often involves repetitive steps, which can be time-consuming and detract from the core activity of trading. For example, adjusting Moving Average line periods requires frequent manual intervention to align with market trends, which can lead to missed opportunities.

To address this, integrating dynamic period adjustments through intuitive interfaces is crucial. One method involves using on-chart buttons to enable period scrolling with a mouse wheel. This mitigates manual sett...

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An Expert Advisor for MT4, based on the crossing of two customizable moving averages, is now available for traders who seek granular control over their trading parameters. This tool allows specification of fast and slow moving average periods, enabling tailored strategies. Traders can select the desired price type for calculation, such as Close, Open, High, or Low.

The EA presents risk management features such as Stop Loss and Take Profit in points, both adjustable or optional. A trailing stop can be activated once the trade is in profit. Entry direction is customizable, supporting Long-only, Short-only, or Both. Fixed lot sizes can be defined, and a maximum slippage setting ensures execution precision. Adding trade comments assists in order management and historical review.

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Machine learning models often struggle with imbalanced datasets, leading to biased predictions favoring the majority class. This is a challenge in algorithmic trading, where imbalanced data can skew a model towards predicting bullish trends in a predominantly bullish market. Addressing this requires precise evaluation metrics like the F1-score over simple accuracy. Techniques such as oversampling, undersampling, and hybrid methods have shown efficacy. Random oversampling enriches the minority class while hybrid methods like SMOTE combined with Tomek Links can refine decision boundaries, effectively balancing predictive accuracy and market sensitivity for improved trading strategies in MetaTrader 5.

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SEFormer brings a transformative approach to 3D object detection in the world of algorithmic trading. By enhancing traditional convolution with transformer-like attention, it adeptly deals with the challenges posed by irregular point clouds. SEFormer intelligently incorporates local structure details by considering direction and distance, allowing for more accurate recognition of object directionality and thereby improving trading pattern detection. This novel technique constructs a multi-scale network where local spatial structure is preserved, ensuring robust performance in feature extraction. While some conventional methods might overlook data irregularities, SEFormer prioritizes them, enabling more refined object-level embeddings, ultimately leading to precise trade decisions.

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