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 Ait-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. Ait-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.
Ait-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."
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