Normalized values are crucial in various technical fields such as computer graphics, machine learning, and technical analysis. The Smooth Step function is a viable approach for value normalization, fitting within the sigmoidal function family. Unlike typical interpolation uses, this method operates as a clamping function. It generates results in the 0 to 1 range, filtering certain outputs produced by stochastic models while maintaining a similar operational scope.

The Smooth Step indicator can process all standard price data inputs rather than being limited to common configurations like close/close or low/high/close. It is recommended to employ this indicator in ways similar to the built-in stochastic indicator for efficient analysis. This approach ensures reliable and streamlined value normalization across multiple domains.
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Dive into algorithmic trading with the Metrics Board EA for MetaTrader 5, a cutting-edge tool that transforms complex market analysis into simple, actionable insights. This distinct EA offers a seamless application integrating essential analyses such as High/Low, Volume, and Trend evaluation with a user-friendly interface. Developed using MQL5, it effectively utilizes button clicks for real-time data processing and presentation. The EA’s advanced algorithm ensures high-speed, accurate computations, providing immediate value to traders. It supports everything from optimally identifying key levels to enhancing strategies with important market metrics, marking a step forward in trading tool efficiency and accessibility.
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Dive into streamlined MQL5 development with our comprehensive EX5 trading libraries. By simplifying trade operations and historical data management, these libraries drastically reduce development time. Our final module tackles a key MQL5 limitation, providing seamless access to canceled pending order data. The innovative GetLastCanceledPendingOrderData() function efficiently retrieves critical information such as symbol, price, and duration. This tool is essential for developers building applications reliant on accurate trading history, allowing a focus on broader analytical insights. Through well-structured and intuitive functions, our libraries enhance precision and efficiency in trading history processing, benefiting both novice and experienced MetaTrader 5 developers.
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A continuation for beginners on creating complex data types: structures, unions, and classes. Understanding these concepts helps in organizing data effectively and ensuring modular, maintainable code.

Structures group different types of data under one name, facilitating easier access and modification. They can even contain other structures for more intricate data management. Common predefined structures in MQL5 include MqlDateTime and MqlTradeRequest.

Unions allow storing variables of different types in the same memory location. Ideal for converting types, but restricted from containing strings or dynamic arrays.

Object-oriented programming, through classes, encapsulates data and functionalities, promoting reusability and reduced error occurrences. Classes restrict direct data access by making internal variables private, accessible only via pub...
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For efficient management of trading data, several components are integral in developing an application using the MQL5 language. The application is structured with a Service app for generating reports and sending notifications; a collection of accounts to access historical positions; and separate classes for deals and positions.

The Deal class facilitates storing and accessing individual trade properties, enabling comparison functionalities that aid in creating filtered lists based on selected criteria. The Historical Position class, on the other hand, manages composite data from trades, offering a streamlined method to reconstruct closed market positions for analysis.

These elements combined enable seamless tracking and reporting, crucial for evaluating past trades, optimizing strategies, and maintaining trading efficiency while abiding by notification co...
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A generalized version of the smooth step indicator is now available, building upon Kenneth H. Perlin's concepts. When applying order 0, it behaves similarly to the built-in stochastic divided by 100, with the stochastic slowing set to 1. Order 1 replicates the standard smooth step indicator. Higher orders provide enhanced signal filtering while retaining values within expected ranges. This indicator can be used in scenarios requiring normalization, offering an alternative to stochastic for normalized input in your code. It effectively maintains data integrity across different applications, ensuring consistent and reliable results within technical analysis and systems requiring normalized data inputs.
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Understanding the fundamentals of programming requires a focus on variables, as they serve as the foundation of any computer program. Variables can change their values or remain constant; when they do not change, they are referred to as constants. In programming, precision in variable declaration and initialization is crucial to prevent unpredictable outcomes. Using MQL5, programmers can better grasp how variables work, understanding compiler warnings, variable scope, and the implications of uninitialized variables. Properly declared variables can improve code reliability by minimizing errors and establishing clarity in the code's purpose and functionality. As we progress, we'll discuss deeper concepts, such as visibility and lifetime, to build a comprehensive understanding of variable management and optimization in programming.
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Financial markets require sophisticated analysis for accurate decision-making. Integrating libraries such as MQL5 and Python provides enhanced analytical capabilities. MQL5 serves as the core, with Expert Advisors (EAs) acting as a bridge to external resources like Python’s Pandas library. This setup allows in-depth data processing and signal generation, enhancing trading strategies without replacing MQL5's fundamental role.

The interaction process begins with the MQL5 EA collecting market data, which is formatted and sent to a Python server for analysis. Pandas processes this data, returning insights such as trading signals to the EA, which updates the market charts accordingly.

This framework relies on Python's simplicity and Pandas’ analytical power, supporting the generation of trading signals based on historical data. The integration provides flexibility...
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MQL5 has evolved beyond a basic programming language for simple trading robots. It now supports the creation of complex trading programs that can be robustly deployed and tested. Manual traders often utilize the native or custom indicators for market analysis in MetaTrader5, which offers a user-friendly interface for indicator attachment to charts. However, in algorithmic trading, indicator calculations hold more significance than visual chart representations.

Algorithmic trading requires meticulous calculation of indicators like the Simple Moving Average (SMA). Traditional approaches using predefined price constants and smoothing methods in MQL5 may limit flexibility. Rethinking the input structure for indicators can expand exploration possibilities. Inspired by TA-Lib's flexible approach, implementing indicators with customizable input fosters ne...
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This article explores the balance between human intuition and algorithmic precision in trading software, presenting a refined implementation of the Bollinger Bands strategy using MetaTrader 5. By introducing a logistic regression model to assess trade confidence, the improved strategy increased profitability while preserving simplicity. The refined algorithm placed 495 trades with a 63% success rate, resulting in a $2,427 profit with a 0.74 Sharpe ratio, compared to losses with the original model. This approach balances classical trading strategies and modern computational tools, demonstrating effective yet straightforward techniques to enhance algorithmic trading without unnecessary complexity.
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The "Symbol Swap Panel" is an efficient utility for traders aiming to optimize their chart symbols and Market Watch management. It provides a feature to switch chart symbols with a single click, facilitating quick adjustments to trading strategies without navigating multiple settings. New symbols are automatically added to Market Watch, providing instant access to real-time data.

Designed to enhance trading workflow, this tool reduces the time needed for symbol monitoring and analysis. It's equipped to handle historical data, aiding in past market condition analysis for informed decisions. The tool ensures accurate data loading, though switching back and forth when changing timeframes is recommended for optimal performance.

For traders managing multiple symbols, the Symbol Swap Panel streamlines processes, maintaining focus and efficiency. Active trader...
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Symbol Swap Panel" is a utility for traders to efficiently manage chart symbols and Market Watch. It enables instant symbol switching on charts with a single click, automatically updating Market Watch for real-time data access. Designed to enhance trading workflows, it streamlines the process of monitoring and analyzing multiple symbols, reducing manual navigation and effort.

The panel supports historical data analysis, aiding informed decision-making by allowing swaps based on past market conditions. It ensures accurate data loading, though switching timeframes might require toggling to guarantee data consistency.

Ideal for active traders, this tool facilitates quick symbol management and Market Watch updates without disrupting market analysis. It offers a practical solution for maintaining focus in fast-paced trading environments.

Additional custo...
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The wave probabilistic model's fundamentals and price random walks are linked through complex analytics. This model allows price predictions by understanding the wave field's behavior, critical for trading strategies. The wave probabilistic field follows equations similar to the Schrödinger equation. The wave field function can predict future price movements by analyzing its current state unless disturbed by strong market changes.

The interaction of price movements with potential fields can define discrete price levels and explain observed spikes and jumps on charts. Identifying patterns within the price probability field helps anticipate price spikes influenced by internal market dynamics, offering insights into future market behavior.

Understanding the appearance of prices on a chart involves recognizing various technical and philosophical layers. ...
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The Market Watch Panel Utility is a robust tool for real-time financial symbol monitoring in MetaTrader 4. It provides a user-friendly interface showcasing key data such as close prices. This utility enables efficient trading by allowing quick symbol switching, symbol stacking, and list filtering for targeted market analysis. Its customizable features include saving and resetting symbol lists and personalizing the panel's appearance through color adjustments. Users can store symbols in a text file to ensure consistency in monitoring across sessions.

For enhanced customization, users can add personal button images. This requires placing a 24-bit BMP image in the MQL5/Images folder and updating the code's resource path. Properly formatted images and accurate paths are crucial for successful customization. Despite the absence of a default button image, func...
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The Relative Vigor Index (RVI) is a momentum oscillator used widely in technical analysis. It gauges trend strength by comparing closing and opening prices. Unlike the Stochastic Oscillator, which uses price ranges, RVI focuses on price levels. RVI is beneficial in trending markets, calculated with simple moving averages.

For coding and implementation, MQL5 in MetaTrader 5 is recommended. It’s crucial to rigorously test any strategies built upon RVI in demo environments to ensure their applicability and profitability. The example strategies discussed include various crossover techniques and their corresponding blueprint to facilitate system creation. Remember these strategies serve educational purposes and might require further optimization.
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The transition to daylight saving time introduces challenges in maintaining consistent trading hours for FOREX sessions due to discrepancies in time changes across regions. Trading hours are supposed to last 120 hours: from Sunday 5:00 p.m. EST to Friday 5:00 p.m. EST. However, the U.S. shifts its time on the second Sunday in March and the first Sunday in November, while the E.U. changes on the last Sunday in both March and October. This results in temporary inconsistencies in time differences between markets, affecting the start and end of FOREX sessions.

A particular issue arises with brokers that fail to adjust server times accordingly, leading to an incorrect start and endpoint of the session—specifically omitting the first hour after the weekend. This impacts strategies relying on weekend events, as the expected adjustment doesn't occur. A script can v...
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An advanced adaptation of the Zigzag algorithm offers notable enhancements. It includes two modes: "Oscillator" and "HighLow." The oscillator mode visually represents zigzag swings, treating extreme lows and highs distinctively by designating the extreme low as the symbol point value. The HighLow mode remains faithful to the traditional Zigzag approach, respecting the highs and lows while introducing dynamically scaled Fibonacci retracement levels for better visual continuity.

In both modes, the Zigzag plots the current leg even unconfirmed, allowing real-time price analysis. Users can select various price tracking options, such as open or close. Color coding in the current leg indicates bullish or bearish divergence, with volume checks influencing color depiction to reflect trend strength accurately. Updates in version 1.01 addressed bugs, while ...
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Significant improvements are underway in WinForms objects for enhanced library cohesion. Adjustments to method names and property structures are aligning with a unified method, streamlining graphical object developers' workflows. Each WinForms object now uniformly manages integer, real, and string properties, with flags indicating unsupported features.

Interactive capacity sees advancement with elements like buttons and radio buttons being created. Mouse interactions are enhanced by recognizing cursor positions and responding with events.

Library classes are refined, with default control values updated. Integration of new graphical properties and sorting criteria expands capabilities. Methods for property saving and restoration are in development stages, ensuring robust object management across application sessions.

Methodological consistency is ac...
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The Expert Advisor (EA) showcases how to use the MQL5 Calendar for creating an automated trading system responsive to high-impact forex news. Primarily educational, it teaches traders and developers how to work with the MQL5 Calendar to pinpoint and trade critical economic news, such as inflation figures or interest rate announcements. This EA employs MQL5 Calendar functions to spot pertinent upcoming news events for the trading symbol.

Upon detection of a high-impact event for the base or quote currency, the EA executes a breakout trading strategy by placing Buy Stop and Sell Stop orders around the current price. This tactic seeks to harness price shifts resulting from news-driven volatility.

Multiple adjustable inputs tailor the EA's functionality: Type, Magic, TPPoints, SLPoints, and Volume. These determine event-triggered operations, order identifica...
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An inverse fair value gap (IFVG) represents when price returns to a fair value gap but fails to respect it, signaling a potential market shift. The IFVG strategy, applicable in MetaTrader 5, offers a contrarian edge by anticipating market reversals.

Understanding the standard fair value gap (FVG) involves a three-candle pattern where gaps denote market inefficiencies. Unlike traditional FVG strategies focusing on market rebalancing, the IFVG approach identifies failed gap fills to capitalize on market reversals. This is backed by large market participants whose lack of orders at these zones may signal shifting market intent.

Key rules include aligning with macro trends, using low timeframes, and validating gap size. The strategy components are coded into MetaTrader 5, leveraging global variables and specific function setups. Strategies are rigorous...
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Gating methods offer a dynamic approach to model selection in complex environments, crucial for financial forecasting where economic trends affect prediction accuracy. These techniques utilize gate variables to adaptively weight model outputs based on context, outperforming traditional ensemble methods. There are two main strategies: selecting a single model through predefined rules or using context-dependent weights to combine multiple models, the latter being more robust. Key innovations include learned specialization, where gating parameters are derived directly from data, enhancing model performance despite computational demands. Practical applications demonstrated by testing scenarios highlight the potential of such methods in adaptive algorithmic trading systems.
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