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Author: Eric Zivot
Publisher: Springer Science & Business Media
ISBN: 0387217630
Category : Business & Economics
Languages : en
Pages : 632
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Book Description
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. 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 an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. 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.
Author: Eric Zivot
Publisher: Springer Science & Business Media
ISBN: 0387217630
Category : Business & Economics
Languages : en
Pages : 632
Get Book Here
Book Description
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. 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 an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. 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.
Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author:
Publisher:
ISBN:
Category : Middle Atlantic States
Languages : en
Pages : 340
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Book Description
Author:
Publisher:
ISBN:
Category : Housing
Languages : en
Pages : 1430
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Book Description
Author: Federal Reserve Bank of Philadelphia
Publisher:
ISBN:
Category : Prices
Languages : en
Pages : 364
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Book Description
Author:
Publisher:
ISBN:
Category : Business
Languages : en
Pages : 88
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Book Description
Author: John Y. Campbell
Publisher:
ISBN:
Category : Equilibrium (Economics)
Languages : en
Pages : 68
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Book Description
Author: M. Ray Perryman
Publisher: Springer Science & Business Media
ISBN: 9400932677
Category : Business & Economics
Languages : en
Pages : 263
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Book Description
This book is the first volume of the International Series in Economic Model ing, a series designed to summarize current issues and procedures in applied modeling within various fields of economics and to offer new or alternative approaches to prevailing problems. In selecting the subject area for the first volume, we were attracted by the area to which applied modeling efforts are increasingly being drawn, regional economics and its associated subfields. Applied modeling is a broad rubric even when the focus is restricted to econometric modeling issues. Regional econometric modeling has posted a record of rapid growth during the last two decades and has become an established field of research and application. Econometric models of states and large urban areas have become commonplace, but the existence of such models does not signal an end to further development of regional econ ometric methods and models. Many issues such as structural specification, level of geographic detail, data constraints, forecasting integrity, and syn thesis with other regional modeling techniques will continue to be sources of concern and will prompt further research efforts. The chapters of this volume reflect many of these issues. A brief synopsis of each contribution is provided below: Richard Weber offers an overview of regional econometric models by discussing theoretical specification, nature of variables, and ultimate useful ness of such models. For an illustration, Weber describes the specification of the econometric model of New Jersey.
Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 618
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Book Description
Author: Patrick T. Brandt
Publisher: SAGE
ISBN: 1412906563
Category : Mathematics
Languages : en
Pages : 121
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Book Description
Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.
