A new edition of the comprehensive, hands-on guide to financial time series, now featuring S-PlusŪ and R software
Time Series: Applications to Finance with R
and S-PlusŪ, Second Edition is designed to present an in-depth introduction
to the conceptual underpinnings and modern ideas of time series analysis.
Utilizing interesting, real-world applications and the latest software
packages, this book successfully helps readers grasp the technical and
conceptual manner of the topic in order to gain a deeper understanding of
the ever-changing dynamics of the financial world.
With balanced coverage of both theory and applications, this Second Edition
includes new content to accurately reflect the current state-of-the-art
nature of financial time series analysis. A new chapter on Markov Chain
Monte Carlo presents Bayesian methods for time series with coverage of
Metropolis-Hastings algorithm, Gibbs sampling, and a case study that
explores the relevance of these techniques for understanding activity in the
Dow Jones Industrial Average. The author also supplies a new presentation of
statistical arbitrage that includes discussion of pairs trading and
cointegration. In addition to standard topics such as forecasting and
spectral analysis, real-world financial examples are used to illustrate
recent developments in nonstandard techniques, including:
- Nonstationarity
- Heteroscedasticity
- Multivariate time series
- State space modeling and stochastic volatility
- Multivariate GARCH
- Cointegration and common trends
The book's succinct and focused organization
allows readers to grasp the important ideas of time series. All examples are
systematically illustrated with S-PlusŪ and R software, highlighting the
relevance of time series in financial applications. End-of-chapter exercises
and selected solutions allow readers to test their comprehension of the
presented material, and a related Web site features additional data sets.
Time Series: Applications to Finance with R and S-PlusŪ is an excellent book
for courses on financial time series at the upper-undergraduate and
beginning graduate levels. It also serves as an indispensible resource for
practitioners working with financial data in the fields of statistics,
economics, business, and risk management.