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新研究提出使用LLM代理进行自主资产定价发现

一篇新论文介绍了Agentic Empirical Asset Pricing (AEAP),一个在其中LLM代理自主进行资产定价科学发现过程的范式。该研究定义了AEAP,概述了其核心组成部分,并提出了一个严格的评估标准来衡量这些自主发现系统,而不仅仅是回测输出。论文还提出了一个参考架构和一种用于发现系统本身样本外回测的方法,通过负面发现和局限性突出了潜在的评估陷阱。 AI

影响 引入了一个使用LLM代理在金融领域进行自主科学发现的新颖框架。

排序理由 该集群包含一篇发表在arXiv上的研究论文,详细介绍了一种新方法论。[lever_c_demoted from research: ic=1 ai=1.0]

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新研究提出使用LLM代理进行自主资产定价发现

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该集群包含一篇发表在arXiv上的研究论文,详细介绍了一种新方法论。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Yingjian Pan, Xiaowei Ding, Kay Giesecke ·

    Agentic Empirical Asset Pricing: Methodological Foundations

    arXiv:2609.00731v1 Announce Type: new Abstract: Recent advances in LLM agents enable a new paradigm for asset pricing, which we call Agentic Empirical Asset Pricing (AEAP): systems that autonomously conduct the scientific discovery process itself. We define AEAP and identify its …