A Portfolio Optimization Approach to Identifying Private Information
46 Pages Posted: 1 Dec 2014 Last revised: 8 Oct 2018
Date Written: November 30, 2014
We propose a portfolio optimization approach to identifying private information. In our model, investors are exposed to liquidity and private information shocks and optimize their trading across stocks taking into account price impact (Kyle's Lambda). We obtain a very simple expression for a stock's private information shock: Lambda x OIB (order imbalance). Intuitively, observed order imbalance is more likely to be information-driven when trading is expensive. Consistent with our measure capturing private information, we show empirically that it is greater for smaller firms with higher analyst dispersion, helps to explain return reversals, predicts return volatility, and increases before M&A announcements.
Keywords: XPIN, informed trading, private information, portfolio optimization model
JEL Classification: G11, G12, G14, D82
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