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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Chaikin's Cash Flow (CMF) serves as a quantitative tool for evaluating cash flow volume over defined periods. Developed by Mark Chaikin, it measures buying and selling pressure of securities within a single timeframe and then aggregates it for a specified period—commonly 20 or 21 days. The CMF ranges between 1 and -1, offering insights into market dynamics.

Calculation involves determining a cash flow multiplier, computing cash flow volume, and then deriving the CMF. A period closing in the upper half of its range signals buying pressure, while a close in the lower half hints at selling pressure.

CMF assists in trend confirmation, with values above 0 supporting bullish trends and values below 0 indicating bearish trends. Crossings of the zero line suggest potential trend reversals. Accuracy can be improved by using lines such as 0.05 and -0.05 to filter ...

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The correlation coefficient (CC) is vital for measuring the relationship between two financial instruments. It ranges from 1 to -1, indicating the degree of positive or negative correlation. A CC near 1 means the instruments move together, while a CC near -1 indicates an opposite movement. A value of 0 suggests no correlation. These insights are beneficial for assessing investment risks.

In portfolio management, CC is critical for diversification. By evaluating the correlation between assets, one can avoid redundant risks. Traders can effectively use the CC to adapt to changing correlations over time. It is an important tool not just for short-term market analysis but for long-term investment strategies as well.

The indicator includes parameters such as Symbol, Source, and Length, which allow customization for more precise analysis. Adjustments in the...

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The Know Sure Thing (KST) indicator is an advanced momentum oscillator using Rate of Change (ROC) metrics. Developed by Martin Pring, the KST combines four different-period ROCs smoothed by simple moving averages. This results in a line that oscillates around a zero point, with movement indicating shifts in market momentum. The indicator calculates momentum for four distinct price cycles, and the signal line is a further SMA of the KST. The default periods for calculation include: 10, 15, 20, 30 for ROC and 10, 10, 10, 10, 10, 15, 9 for smoothing and the signal line.

KST's interpretation involves understanding bull and bear trends through positive and negative momentum shifts. Divergences between price and KST may signal potential reversals, whereas crossovers, while lagging in nature, can suggest momentum changes. KST doesn't have fixed overbought...

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The Net Volume indicator provides insights into market dynamics by illustrating where buyers and sellers are committing capital. A positive net volume suggests that buying pressure is overtaking selling pressure, often indicating potential market growth. Conversely, a negative net volume suggests selling pressure is prevailing. This analysis assists in measuring the pressure exerted by buyers or sellers on an asset over a specific timeframe. Users can adjust the indicator settings to utilize either tick or real volume for more precise calculations. This flexibility allows for a tailored approach to understanding market forces in real time.

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The SMI Ergodic Oscillator indicator is used to determine the difference between the True Strength Index (TSI) and its exponentially smoothed signal line. This technical tool features three adjustable parameters: Long Length for the primary smoothing period, Short Length for the secondary smoothing period, and Signal Line Length for the SMI's signal line smoothing.

The functionality of the ergodic oscillator is centered around its interaction with the zero level. A prolonged period below zero followed by an upward crossing indicates a potential long position opportunity. Conversely, a sustained duration above zero that culminates with a downward crossing suggests an ideal opening for a short position. Adjusting these parameters can fine-tune the indicator's responsiveness and enhance its precision in market analysis.

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The Volatility Stop is a crucial technical indicator for setting effective stop losses. It helps strike a balance between profit-making and risk management. The stop loss should be strategically positioned at a distance from the price to manage risks while allowing market fluctuations so as not to exit trades prematurely. The indicator features three adjustable parameters: Length, which determines the calculation period of the ATR for current volatility assessment; Source, which specifies the price type from where the StopLoss level is set; and Multiplier, which controls the StopLoss distance from the Source price through volatility scaling. Effective stop loss placement minimizes risk, and utilizing additional indicators alongside Volatility Stop enhances profit and risk management strategies.

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