Econometric modeling of high-frequency financial data with applications to market microstructure

The recently available high frequency transaction data from financial markets provide researchers with unprecedented opportunities to study financial market mechanisms and test market microstructure theories.; Chapter 1 presents a new model that improves upon several inadequacies of the original Autoregressive Conditional Duration (ACD) model considered in Engle and Russell (1998). We propose a Threshold Autoregressive Conditional Duration (TACD) model to allow the expected duration to depend nonlinearly on past information variables. Conditions for the TACD process to be ergodic and existence of moments are established. Strong evidence is provided to suggest that fast transacting periods and slow transacting periods of NYSE stocks have quite different dynamics. Based on the improved model, we identify multiple structural breaks in the transaction duration data considered, and those break points match nicely with real economic events.; In Chapter 2 we explore the information determinants of market liquidity and volatility through econometric modeling of the dynamics of the intraday bid and ask quotes. We estimate an empirical microstructure model of intraday bid and ask quotes with shocks to market microstructure variables enter into the equations for the underlying costs of market making and the efficient market price, which jointly determine the observed bid and ask prices through an asymmetric rounding mechanism. The model is designed to answer the central question in information based market microstructure literature: what is the role information asymmetry played in determining the time varying market liquidity and volatility.