High-frequency trading is an algorithm-based computerized trading
practice that allows firms to trade stocks in milliseconds. Over the
last fifteen years, the use of statistical and econometric methods for
analyzing high-frequency financial data has grown exponentially. This
growth has been driven by the increasing availability of such data, the
technological advancements that make high-frequency trading strategies
possible, and the need of practitioners to analyze these data. This
comprehensive book introduces readers to these emerging methods and
tools of analysis.Yacine Aït-Sahalia and Jean Jacod cover the
mathematical foundations of stochastic processes, describe the primary
characteristics of high-frequency financial data, and present the
asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod
also deal with estimation of the volatility portion of the model,
including methods that are robust to market microstructure noise, and
address estimation and testing
questions involving the jump part of the model. As they demonstrate, the
practical importance and relevance of jumps in financial data are
universally recognized, but only recently have econometric methods
become available to rigorously analyze jump processes.Aït-Sahalia and
Jacod approach high-frequency econometrics with a distinct focus on the
financial side of matters while maintaining technical rigor, which makes
this book invaluable to researchers and practitioners alike.
