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＜電子ブック＞
Time Series in Economics and Finance / by Tomas Cipra

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
本文言語	英語
大きさ	IX, 410 p. 94 illus., 15 illus. in color : online resource
著者標目	*Cipra, Tomas author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Econometrics LCSH:Social sciences -- Mathematics  全ての件名で検索 LCSH:Financial engineering FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Econometrics FREE:Mathematics in Business, Economics and Finance FREE:Financial Engineering
一般注記	1. Introduction -- I. Subject of Time Series -- 2. Random Processes -- II. Decomposition of Economic Time Series -- 3. Trend -- 4. Seasonality and Periodicity -- 5. Residual Component -- III. Autocorrelation Methods for Univariate Time Series -- 6. Box-Jenkins Methodology -- 7. Autocorrelation Methods in Regression Models -- IV. Financial Time Series -- 8. Volatility of Financial Time Series -- 9. Other Methods for Financial Time Series -- 10. Models of Development of Financial Assets -- 11. Value at Risk -- V. Multivariate Time Series -- 12. Methods for Multivariate Time Series -- 13. Multivariate Volatility Modeling -- 14. State Space Models of Time Series -- References -- Index This book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance HTTP:URL=https://doi.org/10.1007/978-3-030-46347-2

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