In a grid trading strategy, set the grid distance to manage orders based on price movements. For a price decrease meeting the grid-defined threshold, initiate a long order. Conversely, a price increase securing the grid distance justifies a short order. If the price advances triple the grid distance, close the position. The initial fund allocation for the position is one-tenth of the grid requirement, escalating to two-tenths successively. Upon reaching the predefined profit target, all positions close, and the strategy restarts.

For testing, backtest the EOS/USDT pair from January 1, 2021, to August 31, 2021, using default parameters. Additionally, evaluate the AUD/USD pair from the start of January to the end of June 2021. Such assessments help refine strategy effectiveness and performance.

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Technical indicators are widely used by investors and present both opportunities and challenges. One significant issue is the lag inherent in technical indicators and determining the optimal period to use, which can significantly affect trading outcomes. Short periods often introduce noise, while long periods delay signals.

To address this, employing Dimension Reduction Algorithms, particularly Uniform Manifold Approximation and Projection (UMAP), can help optimize indicator periods. UMAP allows for a representation of all available data, revealing insights beyond the original dataset. Additionally, Object-Oriented Programming in MQL5 can enhance efficiency by managing namespace and memory, essential for building effective trading applications.

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Dive into the latest advancements in MetaTrader 5 development. Enhance trading strategies by automating the selection process through clustering with Python's robust library scikit-learn. Accelerate the efficiency of Expert Advisor optimization by considering cluster analysis to strategically exclude similar strategy instances. This innovative approach not only boosts trading results but also trims down selection time significantly. Seamlessly integrate Python programs within MQL5 to streamline automatic optimization stages. Implement triggers for task tracking, ensuring precise start and end logging, and improve database handling with enhanced SQL queries. Elevate your algorithmic trading strategies by blending MQL5 and Python's power.

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The Cumulative P&L Indicator is a specialized tool for analyzing trading account performance by plotting balance and equity on a chart. Its dual-line presentation offers clarity: the green line reflects realized gains from closed positions, integrating aspects like swaps and commissions, while the blue line represents total equity, combining balance with unrealized profits. With multi-symbol support, it tracks all trading activity across different instruments, ensuring comprehensive accuracy.

Technically, it reconstructs your portfolio's state per bar to maintain historical accuracy in equity curves. Swap charges and currency conversions are seamlessly integrated, making profit calculations straightforward.

Installation involves placing the downloaded file in the MQL5 directory, compiling it in MetaEditor, and attaching it to a chart. The indicator fu...

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Creating graphical controls that can be bound to other elements is an efficient way of managing GUI in programming. A primary focus is developing functionality where moving a panel also moves all controls attached to it. This requires the programmer to handle GUI construction, as there's no built-in visual constructor within the terminal.

The existing library needs enhancements for this task. Defaults are set using macro substitutions within the library, such as color and shadow properties, which can be adjusted as needed. Furthermore, object hierarchy in the code must reflect logical arrangements to enable object grouping.

Introduced improvements include relative coordinates, enabling position specification based on an object's base. The library's virtual methods support descendant object handling, ensuring flexibility in object manipulation. Additionally, ...

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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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