机器入侵:信息获取的自动化和股票收益的横截面

IF 2.1 2区经济学 Q2 BUSINESS, FINANCE

Journal of Financial Markets Pub Date : 2023-06-01 DOI:10.1016/j.finmar.2022.100788

Raunaq S. Pungaliya , Yanbo Wang

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引用次数: 0

摘要

我们根据EDGAR网络日志数据集的信息检索强度，通过将机器互联网协议（IP）与人类IP分离，估计“覆盖”一家公司的机器数量。我们研究了机器覆盖率与股票回报率横截面的关系，发现经过风险调整后，机器覆盖率最低五分之一的股票每年比机器覆盖率最高的五分之一股票高6%。我们的研究结果表明，信息处理的自动化对股票回报的横截面有显著影响。

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Machine invasion: Automation in information acquisition and the cross-section of stock returns

We estimate the number of machines “covering” a firm by separating machine Internet protocols (IPs) from human IPs based on the intensity of information retrieval using the EDGAR web log dataset. We investigate the relationship of machine coverage and the cross-section of stock returns and find that stocks in the lowest quintile of machine coverage outperform those in the highest quintile by 6% annually after adjusting for risk. Our results indicate that automation in information processing has a significant impact on the cross-section of stock returns.

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来源期刊

Journal of Financial Markets BUSINESS, FINANCE-

CiteScore

3.40

自引率

3.60%

发文量

期刊介绍： The Journal of Financial Markets publishes high quality original research on applied and theoretical issues related to securities trading and pricing. Area of coverage includes the analysis and design of trading mechanisms, optimal order placement strategies, the role of information in securities markets, financial intermediation as it relates to securities investments - for example, the structure of brokerage and mutual fund industries, and analyses of short and long run horizon price behaviour. The journal strives to maintain a balance between theoretical and empirical work, and aims to provide prompt and constructive reviews to paper submitters.