In the rapidly evolving world of financial markets, efficient data processing and analysis are crucial. The FinMem framework addresses this need by introducing a large language model (LLM)-based trading agent featuring a sophisticated multi-level memory system. This system, consisting of working and stratified long-term memory, adeptly prioritizes and processes diverse data types. It adapts to market dynamics through a profiling module that tailors risk strategies accordingly. The decision-making module integrates market trends and stored information to form robust trading strategies. Implemented in MQL5 without LLM reliance, the framework enhances algorithmic trading through its innovative memory and decision-making architecture.

👉 Read | NeuroBook | @mql5dev

#MQL5 #MT5 #AI

In the latest iteration of the ChatGPT-integrated MetaTrader 5 system, we've introduced a collapsible sidebar, significantly improving user interface flexibility for algorithmic traders. The sidebar dynamically toggles between expanded and contracted states, optimizing screen space for chart analysis while maintaining access to chat and AI insights. Small and large history pop-ups allow for efficient navigation through historical data, streamlining decision-making processes. This feature is seamlessly integrated, with detailed implementation in MQL5, utilizing elements like toggle buttons and scroll functions for enhanced usability. The result is a robust trading assistant tool, adaptable for both detailed analysis and quick market insights, suited to diverse trading strategies.

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #AI