Introduction to Time Series and Forecasting / Springer Texts in Statistics (PDF)

The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered.

New to this edition:

• A chapter devoted to Financial Time Series
  
• Introductions to Brownian motion, Lévy processes and Itô calculus
  
• An expanded section on continuous-time ARMA processes
  

Peter J. Brockwell and Richard A. Davis are Fellows of the American Statistical Association and the Institute of Mathematical Statistics and elected members of the International Statistics Institute. Richard A. Davis is the current President of the Institute of Mathematical Statistics and, with W.T.M. Dunsmuir, winner of the Koopmans Prize. Professors Brockwell and Davis are coauthors of the widely used advanced text, Time Series: Theory and Methods, Second Edition (Springer-Verlag, 1991).

From reviews of the first edition:
<This book, like a good science fiction novel, is hard to put down.... Fascinating examples hold one's attention and are taken from an astonishing variety of topics and fields.... Given that time series forecasting is really a simple idea, it is amazing how much beautiful mathematics this book encompasses. Each chapter is richly filled with examples that serve to illustrate and reinforce the basic concepts. The exercises at the end of each chapter are well designed and make good use of numerical problems. Combined with the ITSM package, this book is ideal as a textbook for the self-study student or the introductory course student. Overall then, as a text for a university-level course or as a learning aid for an industrial forecaster, I highly recommend the book. -SIAM ReviewIn addition to including ITSM, the book details all of the algorithms used in the package-a quality which sets this text apart from all others at this level. This is an excellent idea for at least two reasons. It gives the practitioner the opportunity to use ITSM more intelligently by providing an extra source of intuition for understanding estimation and forecasting, and it allows the more adventurous practitioners to code their own algorithms for their individual purposes.... Overall I find Introduction to Time Series and Forecasting to be a very useful and enlightening introduction to time series. -Journal of the American Statistical Association