Multivariate time series analysis :
Tsay, Ruey S., 1951-
Multivariate time series analysis : with R and financial applications / Ruey S. Tsay - Hoboken, N.J. : John Wiley & Sons, 2014. - xvii, 492 p. : ill. ; 25 cm. - Wiley series in probability and statistics .
Includes bibliographical references and index.
"Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The book utilizes the freely available R software package to explore complex data and illustrate related computation and analyses in a user-friendly way. An author-maintained website features additional data sets in R, Matlab and Stata scripts so readers can create their own simulations and test their comprehension of the presented techniques"-- An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: * Over 300 examples and exercises to reinforce the presented content * User-friendly R subroutines and research presented throughout to demonstrate modern applications * Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
9781118617908
2013009453
Time-series analysis
R (Computer program language)
Econometric models
MATHEMATICS / Probability & Statistics / General
519.5/5
Multivariate time series analysis : with R and financial applications / Ruey S. Tsay - Hoboken, N.J. : John Wiley & Sons, 2014. - xvii, 492 p. : ill. ; 25 cm. - Wiley series in probability and statistics .
Includes bibliographical references and index.
"Since the publication of his first book, Analysis of Financial Time Series, Ruey Tsay has become one of the most influential and prominent experts on the topic of time series. Different from the traditional and oftentimes complex approach to multivariate (MV) time series, this sequel book emphasizes structural specification, which results in simplified parsimonious VARMA modeling and, hence, eases comprehension. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The book utilizes the freely available R software package to explore complex data and illustrate related computation and analyses in a user-friendly way. An author-maintained website features additional data sets in R, Matlab and Stata scripts so readers can create their own simulations and test their comprehension of the presented techniques"-- An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: * Over 300 examples and exercises to reinforce the presented content * User-friendly R subroutines and research presented throughout to demonstrate modern applications * Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
9781118617908
2013009453
Time-series analysis
R (Computer program language)
Econometric models
MATHEMATICS / Probability & Statistics / General
519.5/5