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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The Price Action Analysis Toolkit has developed a tool that enhances chart analysis by scanning and identifying candlestick patterns. Initially intended to locate patterns, its application has expanded to reveal recurring price levels, acting as support or resistance. Recognizing these levels allows traders to anticipate market behavior, better timing for entries and exits, and strategic stop placements.

The Pattern Density Heatmap further advances this by detecting historical candlestick patterns to create zones that illustrate past market reactions. This approach offers a strategic advantage by informing traders of potential market moves as price approaches these zones.

Implementation in MQL5 involves coding a system that scans historical data for patterns, aggregates detections into price zones, and visualizes them with a heatmap. These zones are no...

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Average Daily Range (ADR) and Average True Range (ATR) are essential indicators used in trading for volatility analysis. ADR measures the average difference between the maximum and minimum prices over a specific period, such as 14 days. This provides traders with insights into expected price fluctuations within a day, aiding in strategy development.

In contrast, ATR calculates the average of the true range values. The true range considers the differences between today's high and low, today's high and the previous close, and today's low and the previous close. By accounting for these gaps, ATR offers a more comprehensive view of volatility and is valued for adaptability to market changes.

While ADR focuses on daily volatility, ATR’s flexibility makes it suitable for broader applications, including risk management and establishing stop-loss levels. Understanding ...

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Explore an advanced approach to creating Expert Advisors (EAs) in MetaTrader 5 using a systematic constructor methodology. This framework facilitates a modular design with customizable trading strategies through a simple 'copy-paste' logic, ensuring the inclusion of essential functions like Stop Loss, Take Profit, and Trailing Stops. By leveraging the structured `SearchTradingSignals` and `STRUCT_POSITION` methods, the article outlines robust techniques for managing trades, including executing and confirming trading orders. Additionally, it delves into integrating standard and custom indicators, showcasing effective algorithmic solutions for developers and traders interested in reliable, versatile EA development.

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The multi-timeframe confluence oscillator integrates Stochastic, RSI, and MACD across three timeframes to support trend entry identification. It assigns scores for alignment, with values above 50 indicating bullish sentiment and below -50 suggesting bearish sentiment. This tool is designed for trend-continuation confirmations, reactions to support and resistance levels, and identifying exhaustion conditions. Unlike traditional methods that normalize values, this oscillator relies on a scoring system to provide its insights. It has shown effectiveness, especially in detecting divergences, making it a useful component of a technical analysis toolkit when used alongside other strategies.

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The two moving averages crossover strategy remains a staple in trading. It leverages two moving averages, typically with different timeframes like 50-day and 200-day. Traders monitor the point of intersection. A short-term moving average crossing above a long-term one indicates a potential buy situation, suggesting a trend reversal upwards. Conversely, a downward crossover may signal a sell opportunity.

Selecting appropriate periods is crucial for accurate signals. Incorporating risk management through stop loss orders enhances strategy robustness. Setting stop losses at strategic levels can mitigate potential downturn impacts. Ensure continuous testing and evaluation to refine strategy effectiveness in varying market conditions. Stay informed and adapt to market changes.

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Explore how dynamic, multidimensional arrays enhance MetaTrader 5 development. The article introduces an innovative approach for managing complex object properties using dynamic arrays, allowing flexibility beyond traditional static arrays. Developers can now store various data types—integer, real, or string—using a custom class that dynamically adjusts to changing data dimensions. This progression facilitates streamlined storage of multi-property objects like graphical elements on a trading chart, solving the challenges of static array limitations. The approach ensures scalability and adaptability in storing dynamically changing object data, vastly improving algorithmic trading strategies with intricate, updatable data structures.

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