Developing Autonomous Financial Decision Systems by Synergizing Multi-Agent Large Language Models with Distributed Temporal Learning Pipelines
DOI:
https://doi.org/10.66280/cis.v1i1.237Keywords:
Autonomous Financial Systems, Multi-Agent Systems, Large Language Models, Distributed Learning, Temporal Pipelines, Algorithmic Governance, Socio-Technical InfrastructureAbstract
The evolution of global financial markets has reached a stage where the velocity and complexity of data exceed the cognitive limitations of human analysts and traditional frequentist models. To address this, the current paper presents a comprehensive systems-level framework for autonomous financial decision systems (AFDS) that synergize multi-agent large language models (LLMs) with distributed temporal learning pipelines. While LLMs offer unprecedented capabilities in semantic reasoning and narrative synthesis, their integration into time-critical financial environments requires a robust distributed infrastructure capable of managing high-throughput temporal data. This research investigates the structural trade-offs between centralized reasoning and decentralized execution, proposing a multi-tier architecture that partitions cognitive labor across specialized agentic swarms. We emphasize the development of hardware-aware temporal pipelines that align asynchronous linguistic insights with synchronous numerical market streams. Beyond the technical architecture, the paper provides an in-depth exploration of the socio-technical dimensions of AFDS, including algorithmic governance, fiscal sustainability, and the ethical imperatives of fairness in automated liquidity provision. By treating the financial market as a high-dimensional distributed system, the proposed framework offers a resilient blueprint for autonomous intelligence that balances aggressive alpha generation with systemic stability. The analysis concludes with a forward-looking discussion on the regulatory challenges of agentic finance and the future of interdisciplinary systems research in achieving global economic equilibrium.
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