A customizable Moving Average feature with toggle functionality has been developed, similar to the one on Trading View. The feature allows users to show or hide the Moving Average on demand. This was achieved by modifying the example Moving Average code from the MQL5 Metaeditor Help. The enhancement includes adding a button and the necessary logic to make the button toggleable, enabling easy display control of the Moving Average. This functionality can be beneficial in optimizing workspace and simplifying analysis. Users can incorporate or adjust this code to fit their individual requirements, allowing for personalized application. Access the button to control the visibility of the Moving Average easily and maintain workflow fluidity.

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The volumes indicator is an essential tool in analyzing Forex and stock markets, providing insights into market liquidity and confirming trends. This post outlines strategies using the volumes indicator to enhance trading systems in MetaTrader 5.

Volumes Indicator Overview: It represents the number of price changes over time. In stock markets, it is calculated as the trading volume multiplied by price, useful in assessing supply and demand.

Strategies Explained:
1. Vol - Movement Strategy: Compares current to previous volume to determine increases or decreases, aiding signal generation.

2. Vol - Strength Strategy: Utilizes a five-period average for evaluating volume's strength, indicating potential market vigor.

3. Price & Volume Strategies (Uptrend/Downtrend): Integrates price highs/lows with volume levels to signal trading opportunities.

4...

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The revised indicator furthers the functionality of a traditional Donchian channel by incorporating a zigzag pivot structure. Pivots arise when the channel's direction plateaus, serving as connectors for new zigzag legs. This pivot formulation relies on a depth parameter to ensure only robust pivots are marked, acknowledging some lag due to the inherent need for confirmation. In live trading, a dynamic trendline from the last confirmed pivot enhances real-time analysis, persistent until a new pivot is acknowledged. The intention is to assess price respect or disregard towards the trendline, thereby obtaining qualitative insights. A recent update, version 1.02, introduces options for leg correction and trendline enablement, offering enhanced customization for technical analysis pursuits.

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This indicator focuses on pinpointing bullish and bearish engulfing candlestick patterns directly on your chart and offers the option for volume confirmation for greater reliability. The core function relies on candle patterns, where an upward arrow below a candle highlights a bullish pattern, and a downward arrow above a candle marks a bearish pattern. Users can exercise flexibility by enabling or disabling the volume confirmation, which considers the pattern stronger when the current candle's volume surpasses the previous one. External inputs allow customization of arrow colors for easy identification: BullishArrowColor for bullish patterns and BearishArrowColor for bearish patterns. This tool aids in visualizing critical market movements and adapting to trading strategies with or without volume confirmation.

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Explore how deep learning is revolutionizing trend forecasting in financial markets by using Molformer, a novel algorithm inspired by chemical element analysis. It utilizes motifs—recurring substructures within molecular graphs—to enhance data representation, akin to natural language processing techniques. Molformer introduces key innovations, such as heterogeneous self-attention (HSA) and attentive farthest point sampling (AFPS), to precisely capture interactions within complex data. For MetaTrader 5 developers, this can mean more accurate trend predictions and improved algorithmic trading strategies. Discover how these cutting-edge techniques can be implemented in MQL5 to harness their full potential for financial market analysis.

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In Part 18, the focus shifts to automating the Envelopes Trend Bounce Scalping Strategy utilizing MQL5. This stage establishes the development of an Expert Advisor's core infrastructure, including signal generation logic essential for scalping small profits from identified price reversals.

Key aspects involve implementing the strategy with the Envelopes indicator, which determines buy and sell signals through interaction with defined bands and confirmations from trend filters such as the EMA and RSI.

Critical steps include setting global variables, initial input configurations, libraries for trading operations, and constructing modular functions to ensure precise trade signaling. Structured risk management techniques will minimize exposure to false signals within ranging markets.

The development and integration of classes and utility functions to manage p...

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Explore the power of the ALGLIB library within the MetaTrader 5 terminal for robust trading system development. ALGLIB offers advanced numerical analysis methods, crucial for optimizing trading algorithms. Key techniques include BLEIC for constrained optimization and L-BFGS for handling large-scale variable problems efficiently. BLEIC addresses optimization challenges by respecting boundaries and constraints, ideal for trading systems with specific restrictions. Conversely, L-BFGS efficiently approximates Hessian matrices for rapid problem-solving in scenarios with numerous variables. MetaTrader 5 developers can leverage these methods to enhance trading strategies, while finding optimal solutions becomes intuitive with clear steps in algorithm setup and execution.

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Technical analysis of arrays in functions and procedures requires understanding MQL5's particularities. Arrays in MQL5 are simplified compared to languages like C/C++. Notably, passing arrays as function arguments in MQL5 always occurs by reference, eliminating certain complexities found in other languages.

MQL5 developers benefit from stricter array handling, leading to safer code. The flexibility to modify arrays within functions demands careful attention, especially when dealing with dynamic structures. Dynamic arrays add complexity due to memory management and initialization nuances.

Remote initialization and manipulation of the array are feasible, allowing advanced data structures to be designed within MQL5's framework. Coders must grasp referenced-based data flow to employ these techniques effectively in practical applications.

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A comprehensive repository of Python scripts and classes is structured within the Trade classes Python.zip folder. Designed for trading systems, it includes multiple modules tailored for specific tasks. Each module encapsulates a different aspect of trading operations in Python.

Modules:

- `AccountInfo.py`: Implements `CAccountInfo` for account-related queries.
- `DealInfo.py`: Houses the `CDealInfo` class for managing trade deals.
- `HistoryOrderInfo.py`: Contains `CHistoryOrderInfo` for historical order data.
- `OrderInfo.py`: Defines `COrderInfo` for active order data management.
- `PositionInfo.py`: Features `CPositionInfo` for tracking open trading positions.
- `SymbolInfo.py`: Includes `CSymbolInfo` for obtaining symbol-specific data.
- `TerminalInfo.py`: Details `CTerminalInfo` for terminal state information.
- `Trade.py`: Contains `CTrade` to...

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A comprehensive overview of various optimization algorithms implemented for advanced computational tasks demonstrates significant progress across algorithmic research. Among them, ANS (across neighbourhood search) and CLA (code lock algorithm) provide robust frameworks for complex searches. P_O_ES ((P+O) evolution strategies), CTA (Comet Tail Algorithm), and SDSm (stochastic diffusion search M) emphasize evolution and adaptation in dynamic environments.

Algorithms like ESG (evolution of social groups) and SIA (simulated isotropic annealing) highlight social dynamics and thermodynamic principles. ACS (artificial cooperative search) and TSEA (turtle shell evolution algorithm) explore cooperative and protective strategies. DE (differential evolution) and CRO (chemical reaction optimisation) cater to specialized search and reaction-based processes.

E...

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Explore an advanced MetaTrader 5 Expert Advisor blending the Fractals indicator with Exponential Moving Averages (EMA) to enhance price action analysis. This system integrates fractal patterns with EMA 14 and 200 to identify potential market reversals aligned with trend directions. By marking critical fractal support/resistance levels and confirming breakouts with EMA trends, traders gain clearer, more reliable entry points. The modular code allows for customization, while visual cues such as arrows and labels streamline decision-making. The EA's effectiveness in both backtesting and live environments demonstrates its ability to provide early reversal signals and improve trading precision.

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Machine learning often focuses on individual candlesticks, sidelining patterns that reveal significant market trends. These patterns, formed under similar conditions, provide insight into market behavior. The Atom-Motif Contrastive Transformer (AMCT) framework was developed to enhance molecular prediction by utilizing atom and motif representations. Through contrastive learning, AMCT aligns atom and motif views of the same entity, improving molecular representation quality.

Implementation in programming environments like MQL5 involves creating parallel pathways for atoms and motifs, using tools like OpenCL to efficiently handle data gradients. Emphasizing consistency across molecules, motif contrastive loss bolsters the robustness of predictions. Integrating relative encoding enhances framework architecture, ensuring cohesive model training.

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This Expert Advisor (EA) is engineered to automate triangular arbitrage among EURUSD, USDJPY, and EURJPY currency pairs. It systematically identifies arbitrage opportunities by calculating the implied EURJPY price via the Ask prices of EURUSD and USDJPY, comparing it with the direct EURJPY price. When a predefined relative difference threshold is surpassed, an opportunity arises.

The EA executes trades based on this analysis: purchasing EURJPY and offloading EURUSD and USDJPY if the implied price exceeds the direct price, or conducting the inverse trades if otherwise. It employs a specific Magic Number for effective tracking of positions, isolating its transactions from others. Positions are closed when cumulative profits surpass the set target. Robust error handling mechanisms ensure seamless operations, automatically addressing issues during trade execution. ...

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Developing a multi-timeframe scanner dashboard in MQL5 enhances strategic trading through real-time trading signals. This tool features a grid layout with buy/sell indicators across timeframes like RSI, STOCH, CCI, ADX, and AO, helping traders spot trends without switching charts. Key to implementation is object management, with specific constants for dashboard design, enabling organized UI structuring. Functions like "calculate_signal_strength" assess market conditions for actionable insights. Dynamic updates ensure responsive interaction, while a close button facilitates user-friendly control. This setup supports adaptability for further enhancements, such as automated alerts, thus empowering traders with a streamlined monitoring process.

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The development of an Expert Advisor (EA) in MQL5 revolves around precise identification of trend lines which facilitate automated trade decisions. This programmatic approach requires a deep dive into MQL5 functions, emphasizing efficient data retrieval and analysis of chart patterns. Key components include accessing exact price values through ObjectGetValueByTime(), which enables the EA to align trade execution precisely with trend movements.

Trend lines, differentiated as ascending or descending, serve as the core markers of market direction. Ascending lines indicate support in an uptrend, presenting buying opportunities when price action aligns. Conversely, descending lines act as resistance in downtrends, signaling potential sell points. An EA exploiting these dynamics observes candlestick behaviors such as wicks and closes to confirm pattern breaks or re...

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Time series forecasting is critical in predicting future values from historical data. It involves key variables: time (independent) and target variable (dependent). This ensures informed predictions by leveraging past trends. Univariate and multivariate approaches exist.

ARIMA (AutoRegressive Integrated Moving Average) is specialized for time series analysis, using past values and prediction errors to forecast future values. Composed of AR (p - past value influence), I (d - differencing to achieve stationarity), and MA (q - lagged errors). Determining optimal p, d, q values involves PACF and ACF plots.

In Python, ARIMA can model financial data like EURUSD. The SARIMA extends ARIMA, incorporating seasonality, for data with regular patterns. Both models assume stationarity and are linear, offering accurate forecasting within their domains. Understanding ...

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Modifying the mouse indicator to receive order book events is essential when using replay systems in simulation applications. Understanding previous modifications is key for following current content. Integration of order book events allows improved usage of the OnCalculate function through iSpread data retrieval in MetaTrader 5.

In transitioning code from a test service to a replay/simulation service, attention must be given to proper loading sequences for modules. It is important to handle control indicators before the mouse indicator for effective execution. With order book messages, initializing appropriate variables and constants in the class constructor can ensure auction states display correctly, enhancing the visual accuracy of mouse indicators.

Handling time gaps requires careful event management to prevent flickering effects and ensure seamle...

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An essential indicator has been developed to meet the requirements of Expert Advisors (EAs) seeking to monitor fluctuations in volume. This tool offers a straightforward method of calculating the average volume over a specified time period using candles. It accommodates both Tick Volume and real volume. To determine if the volume has increased, EAs need only compare whether the volume from a longer period is less than that from a shorter period. The indicator integrates seamlessly with MQL5 and FX Dreema EAs. In scenarios where only Tick Volume is available, the indicator displays a pink line representing average tick volume. Should real volume data be provided, it is illustrated as a blue line, providing a comprehensive volume analysis.

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The recent update addresses fundamental issues in Windows Forms-style control development. Initial graphical object handling encountered problems when switching chart timeframes, leading to graphical objects not being displayed. This was accompanied by journal messages indicating object creation failures. While only form objects were interactive with the mouse, the core graphical element did not include mouse-handling capabilities. This necessitated changes to ensure form objects could serve as minimum graphical objects for interaction.

Additionally, enhancements were made to the library classes. The introduction of the new GraphINI.mqh file enables rapid styling of graphical elements by defining color schemes and various display styles. This reorganization aims to improve parameter readability. To prevent memory leaks during object inheritance, c...

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