| Much recent attention has focused on modeling high-frequency stock price behavior. On the theoretical side, market microstructure theory is providing valuable insights into the trade-by-trade stock price process. On the empirical side, a wealth of research has focused on capturing salient features of calendar period stock data, including conditional heteroskedasticity in calendar period price changes, or stochastic volatility. I explore several topics in this arena, focusing in particular on market microstructure models and their estimation. In the first chapter, a theory-based link among asymmetric information, the behavior of market participants, and stochastic volatility is established through a market microstructure model of securities markets. In the second chapter, using insight from market microstructure theory and the mixture of distributions hypothesis, a new class of conditional heteroskedasticity models is specified that attempts to better explain stock price volatility through the inclusion of information arrival proxy variables suggested by economic theory. In the third chapter, the estimation of sequential-trade, asymmetric information market microstructure models of securities markets is explored. |
