Cross-Sectional Identification of Private Information
提出一种基于证券横截面战略交易优化的私有信息度量方法，通过λ×订单不平衡衡量信息驱动交易，验证其对小公司、分析师分歧、内幕交易等场景的解释力。
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.