Athenarabetaathenara:~$ registry show agents/finmem
FinMem
An LLM trading agent that combines a configurable character profile with a layered memory module modeled on human trader cognition.
added 2026-08-15 · MIT · external
$ git clone https://github.com/pipiku915/FinMem-LLM-StockTradingFinMem is built from three modules: profiling, which defines the agent’s professional character and risk personality; memory, a layered store with an adjustable cognitive span that ranks and retains market information over different time horizons; and decision-making, which converts retrieved memories into trade actions. The authors report that adjusting the agent’s cognitive span and personality settings changes trading performance.
The implementation supports OpenAI models, Hugging Face models served via Text Generation Inference, and Google Gemini, using text-embedding-ada-002 for retrieval. The repository’s worked example trades TSLA over June–October 2022; the system was also entered in the IJCAI 2024 FinLLM Challenge single-stock trading task.
trading [●●···] basic ai [●●●●·] advanced programming [●●●··] moderate setup [●●●●·] advanced
described in finmem-paper
extended by Can LLM-based Financial Investing Strategies Outperform the Market in Long Run? · FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making · From Deep Learning to LLMs: A Survey of AI in Quantitative Investment · QuantHarness: Price-Driven Multi-Agent LLMs for High-Frequency Trading · FINSABER
athenara:~$