Candlestick patterns remain a critical component of technical analysis, offering insights into market dynamics. They document buyer-seller interactions and reflect market sentiment, often predicting future movements. The bullish engulfing pattern exemplifies this predictive ability by indicating potential buying strength. Developers utilizing the MQL5 environment can automate and enhance candlestick studies.

CandlePatternSearch.mq5 is an Expert Advisor designed for MetaTrader 5. It detects and highlights popular candlestick formations on charts, enhancing traders' abilities to analyze patterns across instruments and timeframes. Features include a comprehensive pattern library, interactive on-chart controls, real-time monitoring, and customizable parameters for alert configurations.

This EA consolidates technical analysis by transforming candle...

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #Candlestick

Discover cutting-edge enhancements in the MetaTrader 5 library designed for algorithmic trading. The refined structure splits a monolithic codebase into reusable components, optimizing execution through modularity. Key improvements involve efficient input handling; only active charts now process keystrokes, reducing resource demands. The new Crosshair tool simplifies interfacing with charts, while the Trendline tool adds flexibility with customizable extrema. The upgrade ensures improved responsiveness in environments with numerous open tabs. Developers benefit from a revamped data management approach, storing global variables locally within classes, enabling independent usage and runtime modification. Embrace these advancements for robust trading systems enhancement.

👉 Read | AlgoBook | @mql5dev

#MQL5 #MT5 #ExpertAdvisor

MetaTrader 5's Economic Calendar offers powerful tools for algorithmic traders and developers to enhance market analysis. With MQL5 functions like CalendarCountryById() and CalendarValueHistory(), developers can programmatically interact with economic data. MqlCalendarCountry, MqlCalendarEvent, and MqlCalendarValue structures provide detailed insights into countries, events, and their values, essential for fundamental analysis. The CiCalendarInfo class simplifies access to calendar properties, enabling developers to create detailed time series for specific events. Practical applications include reliable event forecasting and comprehensive historical data analysis, crucial for developing advanced trading strategies. This tool enhances decision-making, providing a competitive edge in algorithmic trading.

👉 Read | VPS | @mql5dev

#MQL5 #MT5 #Algorithm

This script offers a comprehensive approach to candlestick analysis for traders. It efficiently retrieves essential data points, including opening, closing, high, and low prices. The script categorizes the candlesticks into bullish, bearish, or neutral based on the relationship between open and close prices. It performs amplitude calculations to determine differences between high and low values, and computes average amplitudes for both bullish and bearish candlesticks. The script identifies the top five significant candlesticks with the highest amplitudes in bullish and bearish categories.

A report is generated detailing the count of each candlestick type and average amplitudes, highlighting the top significant candlesticks. This report is displayed as commentary on the trading chart, providing traders with an enhanced visual understanding of the cand...

👉 Read | NeuroBook | @mql5dev

#MQL5 #MT5 #script

The recently developed report streamlines testing of multiple EAs or strategies in a single account by consolidating data based on magic numbers and currency. It provides total profit and loss metrics, including profit, swap, and commission, alongside the win rate percentage to evaluate performance accurately. The net position size reflects historical trades, while current exposure details open position risks. Gross profit and loss are separated, and the profit factor is shown as a risk/reward analysis. Cumulative lot sizes are reported under total volume. The report includes all magic numbers, even zero, and aggregates symbols per magic number, displaying a combined symbol list for each. This data is then exported into a single TradingStats.csv file, which can be saved in the MQL5/Files/ folder. The process is simplified to a drag-and-drop action on any ...

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #EA

Discover the intricacies of Analytical Volume Profile Trading (AVPT), an advanced method revolutionizing market analysis by focusing on trading volume across price levels. AVPT goes beyond traditional indicators, using High-Volume Nodes and Low-Volume Nodes to map market memory and liquidity structures. This precision approach allows traders to decode institutional support and resistance, anticipate breakouts, and execute trades with precision. By integrating automation and real-time volume distribution, AVPT enables traders to navigate liquidity imbalances, turning market chaos into actionable insights. Ideal for MetaTrader 5 developers, AVPT offers a context-aware trading blueprint that enhances decision-making and risk management.

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #Trading

Dive deep into MQL5 with an extensive breakdown of APIs and URLs, crucial for seamless data flow in MetaTrader 5 algorithmic trading. Learn each URL component—protocol, domain, path, and query—and their roles in retrieving data via external APIs. Create an MQL5 script to fetch real-time pricing data, utilizing JSON parsing for actionable trading insights. Understand the WebRequest function setup, focusing on headers and response handling, to effectively communicate with servers like Binance. This guide ensures practical understanding, offering valuable strategies for optimizing MQL5 applications and enhancing trading systems through efficient API integration. Perfect for both seasoned developers and enthusiasts exploring trading automation.

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #MQL5

Explore a trend-following strategy using the innovative Flower Volatility Index (FVI), derived from the classical Rose Curve. The FVI adapts the geometric properties of the Rose Curve to market conditions, utilizing price deviations and volatility for precise signal generation. Key technical features include bounded oscillation, frequency control, and predictable periodicity. By substituting market-derived angles, the FVI translates complex price data into accessible oscillatory signals, offering traders new insights into market trends while maintaining stable, normalized indicators. Applicable to various trading environments, the FVI is a versatile tool for both trend mapping and volatility assessment.

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Indicator

The discussed tool offers a comprehensive statistical overview for traders, highlighting both daily and all-time metrics. It provides key features such as viewing statistics over the past 7 days with customizable settings and a cumulative summary of trading histories. Real-time updates automatically refresh data during trading activities, ensuring up-to-date information. The tool employs a color-coded system for quick identification of profit or loss days, enhancing readability with a modern flat UI that supports color customization. Numerical data is displayed in a professional format, with commas aiding clarity.

The tool tracks various metrics, including total lots traded, order count, and net profit or loss, comprehensively covering swaps and commissions. Each trading day is logged in the YYYY.MM.DD format, alongside pertinent details such as t...

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Indicator

Refinement and Testing in Table Models:

Development of table models advances with refining methods to manage columns more efficiently. New initialization methods include creating models from arrays, matrices, and linked lists, enhancing adaptability for various data scenarios. Transferring classes to separate include files allows for better organization and modularity. Enhancements to CListObj facilitate new object types, providing robust functionality across different data forms. The CMqlParamObj class aids in versatile data handling, accommodating multiple data types and properties seamlessly. These improvements underpin a universal model architecture, paving the way for adaptable, task-specific data representation.

Table Header and Class Structure:

The table header class facilitates dynamic column management, linking headers with column numbe...

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #TableModel

Enhancing black-box models for trading strategy selection presents complex challenges. Traditional metrics like RMSE often mislead due to sensitivity to scale and lack of comparability across regression targets. Mutual Information (MI) offers a more robust alternative. Its nonparametric nature and unitless measurement provide a consistent comparison across targets, helping identify the most informative strategies.

Empirical results demonstrate MI's superiority. Models predicting changes in the Stochastic oscillator show marked improvements, reflecting market width better than others. Visual analysis through scatterplots and bar plots further validate these findings, reinforcing MI's reliability.

In application, a neural network model, backed by ONNX, enables real-time strategy execution in MQL5, leveraging newfound insights for improved decision-ma...

👉 Read | AlgoBook | @mql5dev

#MQL5 #MT5 #Strategy

Delve into the world of Kagi charts, an insightful Japanese innovation, now being translated into a cutting-edge algorithmic trading system using MQL5. Unlike traditional charts, Kagi charts highlight real market trends by altering direction based on price movement, rather than time, minimizing noise for clearer trend analysis. This two-part series provides a comprehensive guide: Part One introduces crafting a live, responsive Kagi chart utilizing MQL5's graphical capabilities for precise market insights, while Part Two expands to automated trading. Harness this method for superior market trend visualization and robust trading strategies, benefiting both developers and traders in enhancing their algorithmic trading frameworks.

👉 Read | VPS | @mql5dev

#MQL5 #MT5 #KagiCharts

Explore the integration of Python-like time modules in MQL5 to enhance algorithmic trading capabilities. Addressing the limitations of native MQL5, this implementation introduces Python-inspired classes such as CTime, CDate, and CDatetime for efficient time manipulation, timezone handling, and accurate timestamp conversions. These additions facilitate sophisticated backtesting and time-sensitive systems in MetaTrader 5. The complete implementation is available for community collaboration on GitHub. Each module provides essential methods similar to Python's datetime, improving accessibility and precision in trading applications. Access the repository to explore these innovative tools for trading and development.

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #python

Multi-timeframe analysis is essential for understanding market direction in trading. A lower timeframe signal can conflict with higher timeframe trends, leading to unreliable results. The Timeframe Visual Analyzer enhances this by overlaying two higher-timeframe candles on the current chart, maintaining market focus. This allows traders to confirm directional bias across timeframes and receive alerts when alignments are detected, offering settings for sound, push notifications, and emails. The tool ensures seamless chart integration with customizable visual styling and performance optimization, supporting traders' workflows without chart switching, aiding quick decision-making in dynamic market conditions.

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #EA

The Hidformer framework leverages a unique dual-tower encoder structure to effectively analyze and forecast complex multivariate time series, particularly beneficial for handling dynamic and volatile data. This framework excels in drawing out both explicit and hidden dependencies in the data through advanced attention mechanisms, enhancing the analysis of both temporal structures and frequency domains.

A significant feature of Hidformer is its recursive attention mechanism, which aids in capturing intricate temporal dependencies in financial data. The linear attention mechanism complements this by optimizing computations while maintaining training stability. Together, these components enable reliable forecasts, vital in high-volatility markets.

The model's multilayer perceptron-based decoder offers efficient sequence prediction, improving long-t...

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #TimeSeries