Time-Varying Arrival Rates of Informed and Uninformed Trades

We propose a dynamic econometric microstructure model of trading,and we investigate how the dynamics of trades and trade compositioninteract with the evolution of market liquidity, market depth,and order flow. We estimate a bivariate generalized autoregressiveintensity process for the arrival rates of informed and uninformedtrades for 16 actively traded stocks over 15 years of transactiondata. Our results show that both informed and uninformed tradesare highly persistent, but that the uninformed arrival forecastsrespond negatively to past forecasts of the informed intensity.Our estimation generates daily conditional arrival rates ofinformed and uninformed trades, which we use to construct forecastsof the probability of information-based trade (PIN). These forecastsare used in turn to forecast market liquidity as measured bybid-ask spreads and the price impact of orders. We observe thatPINs vary across assets and over time, and most importantlythat they are correlated across assets. Our analysis shows thatone principal component explains much of the daily variationin PINs and that this systemic liquidity factor may be importantfor asset pricing. We also find that PINs tend to rise beforeearnings announcement days and decline afterwards.