Chapter 8. Searching for High-Frequency Trading Opportunities

This chapter reviews the most important econometric concepts used in the subsequent parts of the book. The treatment of topics is by no means exhaustive; it is instead intended as a high-level refresher on the core econometric concepts applied to trading at high frequencies. Yet, readers relying on software packages with preconfigured statistical procedures may find the level of detail presented here to be sufficient for quality analysis of trading opportunities. The depth of the statistical content should be also sufficient for readers to understand the models presented throughout the remainder of this book. Readers interested in a more thorough treatment of statistical models may refer to Tsay (2002); Campbell, Lo, and MacKinlay (1997); and Gouriéroux and Jasiak (2001).

This chapter begins with a review of the fundamental statistical estimators, moves on to linear dependency identification methods and volatility modeling techniques, and concludes with standard nonlinear approaches for identifying and modeling trading opportunities.


According to Dacorogna et al. (2001, p. 121), "high-frequency data opened up a whole new field of exploration and brought to light some behaviors that could not be observed at lower frequencies." Summary statistics about aggregate behavior of data, known as "stylized facts," help distill particularities of high-frequency data. Dacorogna et al. (2001) review ...

Get High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.