Time Series in Economics and Finance

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...

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Main Author: Cipra, Tomas
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2020, 2020
Edition:1st ed. 2020
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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100 1 |a Cipra, Tomas 
245 0 0 |a Time Series in Economics and Finance  |h Elektronische Ressource  |c by Tomas Cipra 
250 |a 1st ed. 2020 
260 |a Cham  |b Springer International Publishing  |c 2020, 2020 
300 |a IX, 410 p. 94 illus., 15 illus. in color  |b online resource 
505 0 |a 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 
653 |a Quantitative Finance 
653 |a Econometrics 
653 |a Economics, Mathematical  
653 |a Statistics  
653 |a Financial engineering 
653 |a Econometrics 
653 |a Statistics for Business, Management, Economics, Finance, Insurance 
653 |a Financial Engineering 
710 2 |a SpringerLink (Online service) 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
856 |u https://doi.org/10.1007/978-3-030-46347-2?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 330.015195 
520 |a 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