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(CA) Can Large Language Models Execute Parent Orders?

LLM应用于算法交易以优化订单执行

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了PACE（Plan-Ahead Controlled Execution）框架，该框架利用大型语言模型（LLM）来执行算法交易中的父订单。该方法旨在优化大订单拆分为小订单的过程，以最小化执行成本，且无需特定的市场假设或任务特定训练。在深圳证券交易所数据上的实验表明，PACE优于TWAP和Almgren-Chriss等现有方法，表明LLM可以与人类不同的方式做出执行决策，并且更高的置信度与更好的表现相关。 AI

影响 这项研究表明，LLM可以应用于复杂的金融执行任务，有可能提高算法交易的效率和决策能力。

排序理由 该集群描述了一篇介绍LLM在金融领域新框架的研究论文。

在 arXiv cs.CL 阅读 →

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LLM应用于算法交易以优化订单执行

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报道来源 [2]

  1. arXiv cs.CL TIER_1 (CA) · Zane Shen, Xinli Xu, Guangyi Zhang, Jialong Chen, Jinsong Zhou, Cong Chen, Guibao Shen, Dongyu Yan, Luozhou Wang, Zhen Yang ·

    大型语言模型能执行父级指令吗？

    arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution costs. Existing approaches either rely on pre-specified market assumptions that…

  2. Hugging Face Daily Papers TIER_1 (CA) ·

    大型语言模型能执行父级指令吗？

    Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution costs. Existing approaches either rely on pre-specified market assumptions that may not hold in practice, or require task-specifi…

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