Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series (Econometric Society Monographs)

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9781107630024: Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series (Econometric Society Monographs)

The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling, and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility, such as those arising from data on the range of returns and the time between trades. Furthermore, the more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. As such, there are applications not only to financial data but also to macroeconomic time series and to time series in other disciplines. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling. The practical value of the proposed models is illustrated by fitting them to real data sets.

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Book Description:

The book presents a statistical theory for a class of nonlinear time-series models. It has particular relevance for the modeling of volatility in financial time series but the overall approach will be of interest to econometricians and statisticians in a variety of disciplines.

About the Author:

Andrew Harvey is Professor of Econometrics at the University of Cambridge and a Fellow of Corpus Christi College. He is a Fellow of the Econometric Society and of the British Academy. He has published more than one hundred articles in journals and edited volumes and is the author of three books, The Econometric Analysis of Time Series, Time Series Models, and Forecasting and Structural Time Series Models and the Kalman Filter (Cambridge University Press, 1989). He is one of the developers of the STAMP computer package.

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Andrew C. Harvey
Editorial: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2013)
ISBN 10: 1107630029 ISBN 13: 9781107630024
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2013. Paperback. Estado de conservación: New. Language: English . Brand New Book. The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey s new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling. Nº de ref. de la librería AAA9781107630024

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Descripción 2013. PAP. Estado de conservación: New. New Book. Shipped from US within 10 to 14 business days. Established seller since 2000. Nº de ref. de la librería VM-9781107630024

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Andrew C. Harvey
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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2013. Paperback. Estado de conservación: New. Language: English . Brand New Book. The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey s new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling. Nº de ref. de la librería AAA9781107630024

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Descripción 2013. PAP. Estado de conservación: New. New Book.Shipped from US within 10 to 14 business days. Established seller since 2000. Nº de ref. de la librería IB-9781107630024

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Descripción Cambridge University Press. Paperback. Estado de conservación: New. New copy - Usually dispatched within 2 working days. Nº de ref. de la librería B9781107630024

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Descripción Cambridge University Press, 2013. Estado de conservación: New. 2013. Paperback. Presents a statistical theory for a class of nonlinear time-series models. The overall approach will be of interest to econometricians and statisticians. Series: Econometric Society Monographs. Num Pages: 278 pages, 43 b/w illus. 14 tables. BIC Classification: KCH; PBT. Category: (U) Tertiary Education (US: College). Dimension: 228 x 156 x 18. Weight in Grams: 396. . . . . . . Nº de ref. de la librería V9781107630024

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Descripción Cambridge University Press, 2013. PAP. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería FM-9781107630024

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Descripción Cambridge University Press 2013-04-22, Cambridge, 2013. paperback. Estado de conservación: New. Nº de ref. de la librería 9781107630024

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Descripción Cambridge University Press. Estado de conservación: New. 2013. Paperback. Presents a statistical theory for a class of nonlinear time-series models. The overall approach will be of interest to econometricians and statisticians. Series: Econometric Society Monographs. Num Pages: 278 pages, 43 b/w illus. 14 tables. BIC Classification: KCH; PBT. Category: (U) Tertiary Education (US: College). Dimension: 228 x 156 x 18. Weight in Grams: 396. . . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9781107630024

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Descripción Paperback. Estado de conservación: New. Not Signed; The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically ex. book. Nº de ref. de la librería ria9781107630024_rkm

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