A new tool is available for traders who need immediate visibility of their potential financial outcomes in their deposit currency. This indicator, originally developed for the MQL5 community, assists by showing the value of the defined stop loss and the take profit settings directly in terms of deposit currency. While it offers quick approximations, users should consider that it provides estimates that do not include brokerage commissions. This makes it an essential, yet basic, tool for traders in strategizing their positions without the need for complex manual calculations.

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The Fibonacci Retracement Indicator is an advanced technical tool that incorporates the principles of the ZigZag indicator to enhance its utility in identifying crucial support and resistance levels in financial markets. This tool, originally developed for Metatrader 4, automates the integration of ZigZag extremes with Fibonacci gridlines, thereby facilitating more precise trading decisions based on key retracements.

For developers interested in integrating similar functionalities or enhancing their financial analysis tools, the underlying logic can be adapted from existing code found at a prominent financial technology site. This offers an opportunity for technical refinement and customization in various trading platforms.

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The Metatrader 4 indicator for Linear Regression Value is an adaptation from the original Metatrader 5 version. This tool is designed to assist traders in gauging the linear regression value, thereby providing insights into market trends and potential price directions.

For those using Metatrader 4 platforms, this indicator can be a significant addition to their trading toolkit by enabling enhanced analysis of market dynamics. Further details about the usage and features of this indicator can be found in the original detailed post on the Linear Regression Value for Metatrader 5.

Traders are encouraged to review the original post to fully understand the capabilities and implementation of this analytical tool in their trading strategies.

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This article presents a comprehensive guide on implementing the Cascade Order Trading Strategy using Forex Trading Expert Advisor (EA) in MetaQuotes Language 5 (MQL5) for MetaTrader 5. It highlights the use of moving average crossovers to automate trading decisions on the MetaTrader 5 platform, which takes advantage of the Trade.mqh library for effective order management.

The strategy employs two exponential moving averages (EMA) to generate buy or sell signals based on their crossover direction. Detailed steps include setting orders with specified take profit and stop loss, adjusted dynamically according to market conditions. Furthermore, the script intelligently identifies new bars, ensuring that decisions are based on completed candle formations, and adjusts holdings when profit targets are reached.

The article also details the use of MQL5's CTrade class for streamlined order p...

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Exploring the integration of MetaTrader 5 with Python, C++, and Java opens new horizons in algorithmic trading and financial analysis. This project showcases a CGI character, "Price Man," whose size alters based on real-time market data, reflecting the prevalent market emotions such as optimism and fear. This creative approach uses CGI animations to depict market dynamics in an intuitive manner, making it accessible for various audiences.

The backbone of this concept involves key technologies and tools: MetaTrader 5 for extracting price data, and Python for data manipulation. Exporting price data involves a straightforward process in MetaTrader 5, where data is extracted and normalized using Python scripts to ensure uniformity and precision in analyses. Tools like Pandas play a crucial role here, facilitating efficient data handling and transformations necessary for subsequent visual...

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In the latest development for MetaQuotes Language 5 (MQL5) users, significant advancements have been made in GUI panel automation enhancing interaction and dynamism. Moving forward from a static setup, the article discusses transitioning to a responsive and interactive panel that accommodates live updates and mobility of components. Key enhancements include relative positioning and flexible layouts, real-time data integrations, and interactive features such as clickable and draggable elements.

The implementation reviews start with the closure of the panel upon interaction with a designated button and extend to dynamic updating of trading volumes and price quotes in real-time. Additionally, components now react to mouse hover effects, modifying visibility as an interaction cue. These improvements aim to refine user experience by ensuring the interface is not only visually engaging but...

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The new Risk/Reward Box Indicator automatically generates a visual tool on any open chart, utilizing historical candle high and low values. Originating from a reliable source, this tool has been adapted for ease of use. Users can adjust the box size and reposition it to match specific trading strategies and price targets. This allows traders to better assess potential risks and gains on trades, enhancing decision-making efficiency in active markets. A useful addition for traders looking for precise control and analysis in their trading environment.

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Machine learning in financial markets heavily relies on the quality of training data to predict market behavior accurately. Sophisticated tools often struggle due to noisy data masking valuable information. The quality of indicators, acting as data purveyors, significantly impacts model performance. Timothy Masters' book, Testing and Tuning Market Trading Systems, discusses using entropy to evaluate the informational content of indicators.

Entropy measures the unpredictability in the data, providing insight into its usefulness for model training. By employing entropy, strategy developers can objectively assess which indicators bring the most value and which might mislead due to insufficient information content. Such methodologies uphold the importance of data cleanliness and relevance in developing effective market strategies using machine learning technologies.

Understanding entr...

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Understanding the nuances of MT4 and MT5 trading platforms can significantly enhance your trading performance. MT4 suits forex specialists seeking robustness and simplicity, while MT5 offers advanced functionalities for assets beyond forex, accommodating strategies that involve futures or stocks. Both platforms support automated trading but remember, selecting the right platform aligns with specific trading goals and the market being tackled. Analyze your trading needs to choose effectively between MT4 and MT5.

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In Python programming, utility classes such as Utils play a significant role by providing reusable functions without needing to instantiate the class itself. One classic utility in technical computing involves handling matrices—essential data structures in machine learning, physics simulations, and more. Python's standard libraries offer foundational methods for matrix manipulation, including initialization, transformation, and other operations. However, there's always scope to expand these libraries to include additional functionalities tailored to specific application needs.

For developers handling data files and matrices, the ability to read matrices from CSV files is crucial. This function streamlines the import of data, converting CSV formatted data directly into matrices which can then be manipulated within Python. Similarly, encoding values directly from CSV files enhances fun...

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Introducing two cutting-edge portfolio optimization programs designed to enhance trading strategies and maximize returns while curbing risks. The first tool, based on Python, integrates seamlessly with MetaTrader 5 and utilizes advanced libraries including pandas, Numpy, and cvxpy for data analysis, asset allocation optimization, and visualization via Matplotlib. The second tool employs MQL5 and capitalizes on the native capabilities of MetaTrader 5, facilitating a seamless operational experience within the trading platform.

These tools are crucial in modern financial management, enabling a scientific approach to portfolio construction that mitigates human biases and adjusts to market dynamics effectively. Both programs utilize complex algorithms to examine vast datasets, analyze market trends, and explore asset correlations, thus delivering data-informed strategies that conform to v...

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Introspective Sort, also known as Introsort, is a hybrid sorting algorithm renowned for its efficiency and is implemented as a standard in many modern software libraries. Introsort incorporates the methodologies of three distinct sorting algorithms: Quicksort, Heapsort, and Insertion Sort, each selected based on specific conditions during the sorting process.

Quicksort operates on the divide and conquer principle, using a pivot to partition the array and achieving average time complexity of O(n log n). Heapsort, leveraging a binary heap structure, also manages average and worst-case scenarios in O(n log n) time but differs as it is an unstable sorting method. Insertion Sort, simplest of the three, optimally sorts small datasets or final pieces of larger collections with a time complexity ranging up to O(n^2) in the worst case.

The Introsort algorithm begins with Quicksover and shift...

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MQL5 Cloud Network has reached 16 billion completed tasks. Algo traders use it every day to test their strategies faster.

We have upgraded it for even higher performance:

• 7 upgraded servers that manage connected agents and distribute tasks more efficiently
• 60 Gbps increased network bandwidth for fast data transfer between algo traders and agents
• Improved server "hot cache" with historical data for quicker data distribution
• No more slow agents from virtual environments to make sure you always get the best CPUs for your tasks

Try cloud calculations and spend your time developing strategies instead of waiting for test results.

We also invite you to join the network. Daily activities like browsing, office work or watching videos require a tiny portion of your PC power, leaving the rest unused. Why not share it and earn? Just download the Strategy Tester Manager and run a quick setup.

Download the agent manager and start earning...

Understanding the complexities of fish schooling behavior has led to the development of the Fish School Search (FSS) algorithm, a notable contribution to the field of swarm intelligence. Introduced by Bastos Filho and Lima Neto in 2008, the FSS is designed primarily for continuous optimization problems in multimodal search spaces and focuses on mimicking the collective movement patterns observed in fish schools.

The algorithm features distinct components such as the feeding and swimming operators, which handle the simulation of feeding success and coordinated school movement. The feeding mechanism encourages fish to move towards regions of higher yield, impacting their 'weight', which in turn influences the school's collective movement. The swimming operators divided into individual, instinctive-collective, and collective-volitional movements, facilitate exploration and exploitation ...

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A useful adaptation has been made to a common trading code available at MQL5's Codebase. The developer responsible for the tweak has added functionality that filters out Volume levels in conditions where Spreads are notably high. This adjustment could bring considerable advantage by enhancing the strategy's execution and efficacy during volatile market conditions. The revised code is accessible for further review, allowing other developers in the community to assess and potentially adopt this updated method for optimizing trade performance.

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Explore a sophisticated hybrid trading strategy for the S&P 500 using MQL5, blending AI and technical analysis to enhance trading decisions. This approach leverages vast datasets from MetaTrader 5, utilizing linear algebra for efficient analysis and pattern recognition. Understand how traditional indicators like the Commodity Channel Index and Relative Strength Index integrate with AI models to predict market movements.

The strategy involves constructing a dynamic Expert Advisor in MQL5 that combines the strengths of artificial intelligence with the reliability of technical analysis. The article includes detailed insights into the programming principles needed to analyze large datasets and techniques for uncovering non-obvious patterns in market data.

Further, the strategy is outlined with a step-by-step guide on setting up indicators, importing libraries, and handling data within t...

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Understanding and Implementing a Consolidation Range Breakout Strategy Using MQL5

In financial markets, strategies based on market consolidation and breakout are key for capturing major price movements post low volatility periods. This post discusses building an Expert Advisor (EA) with a Consolidation Range Breakout strategy using MQL5 for the MT5 platform.

A consolidation range marks a period where price oscillates horizontally and volatility is low, with distinct upper and lower boundaries referred to as resistance and support levels. Breaking these levels often results in substantial price moves. Traders can leverage these movements through a systematic approach that includes identifying and trading breakouts—both key components of the discussed strategy.

To implement, traders first identify the consolidation range through historical price data analysis, watching for breakouts ...

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Understanding the daily initialization process in automated trading systems is critical for bot performance. In this strategy, the bot starts each day by erasing all previous orders. It then determines the highest and lowest values from the previous day's bar to set up new pending orders: a BUY_STOP and a SELL_STOP. Noticeably, there is no TakeProfit set for these orders.

Key functions include:
- Initial setup where local variables are initialized.
- Regular checks and updates through the main code, which include:
1. Generating trading signals and executing new orders.
2. Implementing a trailing StopLoss that adjusts as the price moves beneficially, thereby potentially increasing profits.
3. Daily management of old orders to ensure the strategy starts fresh each day.

Additional factors monitored by the bot to optimize trade executions are volume values, account's free margin l...

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