Multivariate time series analysis with R and financial applications Ruey S. Tsay

Por: Colaborador(es): Idioma: Inglés Series Wiley series in probability and statisticsDetalles de publicación: Hoboken (Nueva Jersey, Estados Unidos) Wiley 2014Descripción: 492 páginasISBN:
  • 9781118617908
Tema(s): 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"
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Libro Claustro 4to piso Libro 519.55 T877mu (Navegar estantería(Abre debajo)) Ej.1 Disponible 100148213
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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"

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