9781107630024 - dynamic models for volatility and heavy tails: with applications to financial and economic time series (econometric society monographs, 52, band 52) von harvey, andrew c. c. (9 Ergebnisse)
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Zustand: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Weitere BilderSprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
Anbieter: Bookbot, Prague, TschechienBookbot
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Softcover. Zustand: As New. 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 exh…ibit 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.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9781107630024.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9781107630024.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Zustand: New. In.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Zustand: New. The book presents a statistical theory for a class of nonlinear time-series models. It 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). Dimens…ion: 228 x 156 x 18. Weight in Grams: 396. . 2013. Paperback. . . . . Books ship from the US and Ireland.
Sprache: Englisch
Verlag: Cambridge Univ Pr, 2013
- Softcover
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Paperback. Zustand: Brand New. 397 pages. 8.90x6.00x0.30 inches. In Stock.
Sprache: Englisch
Verlag: Cambridge University Press, 2013
- Softcover
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Takin…g 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.
