AI Democratization and Trading Inequality

ABSTRACT We are among the first to investigate how Generative AI (GenAI) shapes investors' trading activities. Using an AI‐sentiment measure extracted from earnings‐call transcripts to proxy for textual signals, we find notable shifts in trading behaviors around earnings calls. Before the wide deployment of ChatGPT, short selling was aligned with AI‐sentiment, whereas retail trading was not. However, following ChatGPT's deployment, the alignment of retail traders with AI‐sentiment significantly increases, while the alignment of short sellers weakens, albeit insignificantly. Stocks with higher information processing costs exhibit a more pronounced increase in retail trading alignment, scenarios where retail investors are likely to benefit more from AI. Using retail‐AI alignment as a proxy for the extent to which retail investors trade based on AI signals, we show that information asymmetry declines and retail investors' trading profitability improves, whereas short sale profitability declines in high retail‐AI alignment stocks. Exogenous outages reduce the alignment between retail trading and AI‐sentiment, allowing us to draw causal inferences. Collectively, this study suggests that AI is a promising technology for narrowing the information gap in the trading of complex textual financial disclosures between investor classes with clear disparities in the ability to process public disclosures.

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Publication Details

Journal
Journal of Accounting Research
Published
2026-04-22
DOI
https://doi.org/10.1111/1475-679x.70063
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Democratization and Trading Inequality

Xiumin Martin, Changyun Zhou, ANNE YANRU CHANG, XI DONG
Journal of Accounting Research
Stock Market Forecasting Methods
article

AI Democratization and Trading Inequality

Xiumin Martin, Changyun Zhou, ANNE YANRU CHANG, XI DONG
article en

Abstract

ABSTRACT We are among the first to investigate how Generative AI (GenAI) shapes investors' trading activities. Using an AI‐sentiment measure extracted from earnings‐call transcripts to proxy for textual signals, we find notable shifts in trading behaviors around earnings calls. Before the wide deployment of ChatGPT, short selling was aligned with AI‐sentiment, whereas retail trading was not. However, following ChatGPT's deployment, the alignment of retail traders with AI‐sentiment significantly increases, while the alignment of short sellers weakens, albeit insignificantly. Stocks with higher information processing costs exhibit a more pronounced increase in retail trading alignment, scenarios where retail investors are likely to benefit more from AI. Using retail‐AI alignment as a proxy for the extent to which retail investors trade based on AI signals, we show that information asymmetry declines and retail investors' trading profitability improves, whereas short sale profitability declines in high retail‐AI alignment stocks. Exogenous outages reduce the alignment between retail trading and AI‐sentiment, allowing us to draw causal inferences. Collectively, this study suggests that AI is a promising technology for narrowing the information gap in the trading of complex textual financial disclosures between investor classes with clear disparities in the ability to process public disclosures.

Journal of Accounting Research
Baruch College (US), Washington University in St. Louis (US), Southwestern University of Finance and Economics (CN)
Openalex Percentile: Top 4%
Stock Market Forecasting Methods
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