Cross-sectional identification of informed trading

We propose a new approach to measuring informed trading in individual securities based on a portfolio optimization model for investors facing information and liquidity shocks. These shocks induce speculative and liquidity-motivated order flow, taking into account the price impact of trading. The model allows us to back out the amount of informed trading from a security’s aggregate order flow, based on the cross-section of price impact parameters ($\lambda$) and order imbalances (OIB). Furthermore, we obtain a very simple expression for a security’s aggregate private information shock: its lambda times OIB, in excess of the same term for a benchmark security that is insulated from informed trading. We validate our private information measure (based on daily data for all S&P 1500 stocks over 2001-2010) by showing that it is strongly related to contemporaneous returns, and that return reversals are significantly weaker following stock-days with high private information estimates.