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November 2022
[Finance] Raunaq Pungaliya, Yanbo Wang - Machine invasion: Automation in information acquisition and the cross-section of stock returns
Professors Raunaq Pungaliya and Yanbo Wang's paper, "Machine invasion: Automation in information acquisition and the cross-section of stock returns," has been accepted for publication in the Journal of Financial Markets. The Journal of Financial Markets publishes high quality original research on applied and theoretical issues related to securities trading and pricing.
Abstract
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.
Abstract
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.
Keywords
automation, sec filings, demand for financial information, big data, stock returns, machine-readable disclosure
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