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Mini-articles with technical and fundamental analysis on the way as forecasts and levels -
https://www.mql5.com/en/channels/forecast

The analysis of multi-agent behavior plays a crucial role in various domains, including finance, autonomous driving, and surveillance systems. Understanding agent actions requires solving several key tasks: object tracking, identification, trajectory modeling, and action recognition. Among these, trajectory modeling is particularly significant in the process of analyzing agent movements. Despite the complexities associated with environmental dynamics and subtle agent interactions, significant progress has recently been made in addressing this problem. The main achievements are concentrated in three key areas: trajectory prediction, missing data recovery, and spatiotemporal modeling.

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In this article, we introduce a custom MetaQuotes Language 5 (MQL5) Expert Advisor (EA) that empowers traders with a Trade Assistant Tool, combining graphical precision with user-friendly controls to place Buy/Sell Stop and Limit orders efficiently. We’ll cover these steps in this order:

1. Conceptual Design and Objectives of the Trade Assistant Tool
2. Implementation in MQL5
3. Backtesting
4. Conclusion

By the end, you’ll have a clear understanding of how to build and test this tool, paving the way for advanced enhancements in the preceding parts.

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Price forecasting and market trend prediction are central tasks for successful trading and risk management. High-quality price movement forecasts enable traders to make timely decisions and avoid financial losses. However, in highly volatile markets, traditional machine learning models may be limited in their capabilities.

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