|
|
|
|
| LEADER |
04089nmm a2200361 u 4500 |
| 001 |
EB000354819 |
| 003 |
EBX01000000000000000207871 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
130626 ||| eng |
| 020 |
|
|
|a 9780387323480
|
| 100 |
1 |
|
|a Zivot, Eric
|
| 245 |
0 |
0 |
|a Modeling Financial Time Series with S-PLUS®
|h Elektronische Ressource
|c by Eric Zivot, Jiahui Wang
|
| 250 |
|
|
|a 2nd ed. 2006
|
| 260 |
|
|
|a New York, NY
|b Springer New York
|c 2006, 2006
|
| 300 |
|
|
|a XXII, 998 p. 270 illus
|b online resource
|
| 505 |
0 |
|
|a S and S-PLUS -- Time Series Specification, Manipulation, and Visualization in S-PLUS -- Time Series Concepts -- Unit Root Tests -- Modeling Extreme Values -- Time Series Regression Modeling -- Univariate GARCH Modeling -- Long Memory Time Series Modeling -- Rolling Analysis of Time Series -- Systems of Regression Equations -- Vector Autoregressive Models for Multivariate Time Series -- Cointegration -- Multivariate GARCH Modeling -- State Space Models -- Factor Models for Asset Returns -- Term Structure of Interest Rates -- Robust Change Detection -- Nonlinear Time Series Models -- Copulas -- Continuous-Time Models for Financial Time Series -- Generalized Method of Moments -- Seminonparametric Conditional Density Models -- Effcient Method of Moments
|
| 653 |
|
|
|a Mathematics in Business, Economics and Finance
|
| 653 |
|
|
|a Statistics
|
| 653 |
|
|
|a Statistics in Business, Management, Economics, Finance, Insurance
|
| 653 |
|
|
|a Social sciences / Mathematics
|
| 653 |
|
|
|a Econometrics
|
| 653 |
|
|
|a Mathematical statistics / Data processing
|
| 653 |
|
|
|a Statistics and Computing
|
| 700 |
1 |
|
|a Wang, Jiahui
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 028 |
5 |
0 |
|a 10.1007/978-0-387-32348-0
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-0-387-32348-0?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 300.727
|
| 520 |
|
|
|a Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is a Principal and Trading Research Officer at Barclays Global Investors. He received a Ph.D. in Economics from the University of Washington in 1997.
|
| 520 |
|
|
|a He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre
|
| 520 |
|
|
|a The field of financial econometrics has exploded over the last decade. This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This second edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments.
|