Modeling Informed State in Fixed Income Market : Empirical Evidence from HFT Data

Motivated by findings in the existing literature on the information content of order flows, we specify Probability of Informed Trading – Asymmetric Autoregressive Conditional Duration (PIN-AACD) model to identify the ‘informed state' in the Fixed Income Markets. Using tick-by-tick price and order flow data, we obtain the estimates for the probability of informed (PIN) state throughout the trading day. The trade direction (buy versus sell orders) and the duration between trades are modeled jointly. The model allows the Probabilities of Good News and Bad News to vary each interval. Results show that intraday patterns of the PIN estimates are consistent with the scheduled arrival of public information or news. Further, we show that PIN is positively related to overall market depth. The effect of realized volatility on information asymmetry is unexpectedly found to be negative. We also find positive correlation between news and trading volume. The study intends to support trading and sales teams in identifying informed trades