Cross-Sectional Identification of Private Information

Abstract We propose a new private information measure based on a model of strategic trade optimization in the cross section of securities. Investors receive liquidity and private information shocks and optimize trading across securities, accounting for price impact (Kyle’s λ). The model yields a simple private information measure: λ×OIB (order imbalance). Intuitively, order imbalance is more likely to be information-driven when trading is expensive. We validate our measure by showing that it is greater for smaller firms with higher analyst dispersion, peaks with insider trades, helps explain return reversals, predicts return volatility, and increases before M&A announcements and after analyst coverage terminations. (JEL G11, G12, G14)

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Publication Details

Journal
The Review of Asset Pricing Studies
Published
2025-09-18
DOI
https://doi.org/10.1093/rapstu/raaf010
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Cross-Sectional Identification of Private Information

The Review of Asset Pricing Studies
Geochemistry and Geologic Mapping
article

Cross-Sectional Identification of Private Information

article en

Abstract

Abstract We propose a new private information measure based on a model of strategic trade optimization in the cross section of securities. Investors receive liquidity and private information shocks and optimize trading across securities, accounting for price impact (Kyle’s λ). The model yields a simple private information measure: λ×OIB (order imbalance). Intuitively, order imbalance is more likely to be information-driven when trading is expensive. We validate our measure by showing that it is greater for smaller firms with higher analyst dispersion, peaks with insider trades, helps explain return reversals, predicts return volatility, and increases before M&A announcements and after analyst coverage terminations. (JEL G11, G12, G14)

The Review of Asset Pricing Studies
University at Buffalo, State University of New York (US), Erasmus University Rotterdam (NL)
Partnerships for the goals
Openalex Percentile: Top 26%
Geochemistry and Geologic Mapping
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