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Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series

373 EGP

* Publisher:Cambridge University Press * Copyright:2013 * Language: English * ISBN13 :9781107630024 * Number Of Pages: 278 pages * Edition: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 ... more on Jumia

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Technical Specifications

SKU:JU030BKAKHIWNAFAMZ
Model:BACCAH - 9781107630024
Main Material:Paperback
Author:Andrew C. Harvey

Jumia's Description

  • Publisher:Cambridge University Press
  • Copyright:2013
  • Language: English
  • ISBN13 :9781107630024
  • Number Of Pages: 278 pages
  • Edition: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 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.

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