FinAgent
A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
Wentao Zhang, Lingxuan Zhao, Haochong Xia, Shuo Sun, Jiaze Sun, Molei Qin, et al. · 2024-02-28
- Management
- T2 Dynamic Memory
- Memory changes during deployment through a stable management policy.
- Representation
- Cross-represented explicit
How experience becomes memory
Each path is one memory component, traced from what is stored to how it is found again.
memory module holding market-intelligence summaries plus low-level and high-level reflection analyses, embedded with an LLM and matched by vector similarity
- Represented asPerception-to-text records & summariesCross-represented explicit
- Stored inVector-indexed collection
- Retrieved bySimilarity search
- Source evidenceUnclear
Sec. 4.2 states that all analyses and summaries produced by the market-intelligence, low-level-reflection and high-level-reflection modules are stored in the memory module, which uses a vector storage architecture. Sec. 4.1 adds a dedicated query-text field to each market-intelligence output and embeds it with an LLM so that past entries with similar content are retrieved by vector similarity. The stored items are natural-language records distilled from numeric, textual and chart inputs; the paper does not state that the Kline chart images themselves are kept or linked from the memory entries, hence source accessibility is left unclear.Full paper: 4.1 Market Intelligence Module; 4.2 Memory Module; 4.3 Reflection Module · arXiv HTML v3, Sec. 4.1-4.3 · Figure 2 (overall architecture)
How memory changes (T2 operations)
Update · Rule-based update
At every trading step of the deployed decision loop the newly produced market-intelligence summary and the new low-/high-level reflections are written into the memory module and become retrievable for subsequent trading days; the memory content therefore grows and is reused during inference under a fixed write rule, with no change to the write or retrieval policy itself.
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