# Acknowledgments

Many people have helped with the development of this book. First and foremost, I would like to thank the students at UW who have taken my course over the last fifteen years. I have received countless comments, corrections, and suggestions that have greatly improved the exposition and material in the book.

A lot of how I think about the statistical analysis of financial data has been shaped by many discussions and interactions over the last fifteen years with my colleague and good friend R. Douglas Martin. My very patient wife Nina Sidneva carefully proof-read many early versions of the chapters as they were under development and caught many of my stupid errors. Xiao Yin proof-read most of the chapters after I converted my Latex notes to Lyx and incorporated the R examples with knitr. I could not have written the book without the expert technical help from Bethany Yollin and the wonderful book Dynamics Documents with R and knitr by Yihui Xie. Bethany helped with the conversion of my Latex notes to Lyx and the incorporation of the R examples in the text using knitr. She also helped to develop and maintain the book’s R package, . Any problem I found with Lyx and knitr was solved by referring to Yihui’s book. My interactions with the R community, especially those involved with R/Finance, have been invaluable for learning and using R for the analysis of financial data. In particular, Brian Peterson and Peter Carl have been incredibly helpful and supportive of my book projects. I use their wonderful R package throughout the book. Working with time series data is made so much easier with Achiem Zieles’ zoo package and Jeff Ryan’s xts package. Many University of Washington (UW) econ PhD students (Brian Donhauser, Ming He, Wan-Jung Hsu, Kara Ng, Anthony Sanford, Galib Sultan) acted as TAs for my undergraduate course and gave constructive feedback. I also thank Coursera for helping me convert my undergraduate course into Coursera format.