Introduction to Time Series and Forecasting, 3rd Edition

Authors: Peter J. Brockwell, Richard A. Davis



Designed for use in full-year courses introducing univariate and multivariate time series and forecasting at the advanced undergraduate and graduate levels

Exercise problems at the end of each chapter reinforce the methods through use of the programs to study provided data sets

Appendix teaches ITSM2000 Professional package (available as a free download); all material is easily applied to R packages and other programs

This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics.  This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details.

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

Table of contents

Front Matter
Pages i-xiv

Introduction
Pages 1-37

Stationary Processes
Pages 39-71

ARMA Models
Pages 73-96

Spectral Analysis
Pages 97-119

Modeling and Forecasting with ARMA Processes
Pages 121-155

Nonstationary and Seasonal Time Series Models
Pages 157-193

Time Series Models for Financial Data
Pages 195-226

Multivariate Time Series
Pages 227-257

State-Space Models
Pages 259-307

Forecasting Techniques
Pages 309-321

Further Topics
Pages 323-351

Back Matter
Pages 353-425

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