算法的善与恶：投资对价格的敏感性和学习假设

IF 7.2 1区经济学 Q1 BUSINESS, FINANCE

Journal of Corporate Finance Pub Date : 2025-06-11 DOI:10.1016/j.jcorpfin.2025.102834

Nihad Aliyev , Fariz Huseynov , Khaladdin Rzayev

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引用次数: 0

摘要

我们研究了公司经理从股价中学习如何受到两种不同类型的算法交易（AT）活动的影响。我们发现，流动性供给的AT通过鼓励市场上的信息获取，增强了经理人从股价中学习的能力，从而增加了对股价的投资敏感性。然而，流动性要求的AT阻碍了信息获取，从而损害了这一学习过程。企业经营绩效在提供流动性的条件下相应提高，在需要流动性的条件下相应恶化。为了建立因果关系，我们使用纽约证券交易所的自动报价实现作为AT的外生变化的来源。我们的研究结果表明，AT对实际经济结果有重大影响。

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The good and evil of algos: Investment-to-price sensitivity and the learning hypothesis

We investigate how firm managers’ learning from share prices is influenced by two different types of algorithmic trading (AT) activities in their shares. We find that liquidity-supplying AT enhances managers’ ability to learn from share prices by encouraging information acquisition in markets, leading to increased investment sensitivity to share prices. However, liquidity-demanding AT impairs this learning process by discouraging information acquisition. Firm operating performance correspondingly improves with liquidity-supplying AT and deteriorates with liquidity-demanding AT. To establish causality, we use NYSE’s Autoquote implementation as a source of exogenous variation in AT. Our findings demonstrate AT’s significant impact on real economic outcomes.

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来源期刊

Journal of Corporate Finance BUSINESS, FINANCE-

CiteScore

11.80

自引率

3.30%

发文量

期刊介绍： The Journal of Corporate Finance aims to publish high quality, original manuscripts that analyze issues related to corporate finance. Contributions can be of a theoretical, empirical, or clinical nature. Topical areas of interest include, but are not limited to: financial structure, payout policies, corporate restructuring, financial contracts, corporate governance arrangements, the economics of organizations, the influence of legal structures, and international financial management. Papers that apply asset pricing and microstructure analysis to corporate finance issues are also welcome.