Financial Time Series

This book grew out of an MBA course in analysis of financial time series that I have
been teaching at the University of Chicago since 1999. It also covers materials of
Ph.D. courses in time seriesanalysis that I taught over the years. It is an introductory
book intended to provide a comprehensive and systematic account of financial
econometric models and their application to modeling andprediction of financial
time series data. The goals are to learn basic characteristics of financial data, understand
the application of financial econometric models, and gain experience in analyzingfinancial time series.
The book will be useful as a text of time series analysis for MBA students with
finance concentration or senior undergraduate and graduate students in business, economics,mathematics, and statistics who are interested in financial econometrics. The
book is also a useful reference for researchers and practitioners in business, finance,
and insurance facing Value at Riskcalculation, volatility modeling, and analysis of
serially correlated data.
The distinctive features of this book include the combination of recent developments
in financial econometrics in theeconometric and statistical literature. The
developments discussed include the timely topics of Value at Risk (VaR), highfrequency
data analysis, and Markov Chain Monte Carlo (MCMC) methods. Inparticular,
the book covers some recent results that are yet to appear in academic journals;
see Chapter 6 on derivative pricing using jump diffusion with closed-form formulas,
Chapter 7 on Value at Riskcalculation using extreme value theory based on
a nonhomogeneous two-dimensional Poisson process, and Chapter 9 on multivariate
volatility models with time-varying correlations.MCMC methods areintroduced
because they are powerful and widely applicable in financial econometrics. These
methods will be used extensively in the future.
Another distinctive feature of this book is the emphasis on...