| 000 | 02429nam a2200397 i 4500 | ||
|---|---|---|---|
| 001 | CR9781139540933 | ||
| 003 | UkCbUP | ||
| 005 | 20240906200238.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 120627s2013||||enk o ||1 0|eng|d | ||
| 020 | _a9781139540933 (ebook) | ||
| 020 | _z9781107034723 (hardback) | ||
| 020 | _z9781107630024 (paperback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
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| 050 | 0 | 0 |
_aHB139 _b.H369 2013 |
| 082 | 0 | 0 |
_a330.01/5195 _223 |
| 100 | 1 |
_aHarvey, A. C. _q(Andrew C.), _eauthor. |
|
| 245 | 1 | 0 |
_aDynamic models for volatility and heavy tails : _bwith applications to financial and economic time series / _cAndrew C. Harvey. |
| 246 | 3 | _aDynamic Models for Volatility & Heavy Tails | |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2013. |
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| 300 |
_a1 online resource (xviii, 261 pages) : _bdigital, PDF file(s). |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 1 |
_aEconometric Society monographs ; _v52 |
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| 500 | _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015). | ||
| 520 | _aThe 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. | ||
| 650 | 0 | _aEconometrics. | |
| 650 | 0 |
_aFinance _xMathematical models. |
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| 650 | 0 | _aTime-series analysis. | |
| 776 | 0 | 8 |
_iPrint version: _z9781107034723 |
| 830 | 0 |
_aEconometric Society monographs ; _v52. |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1017/CBO9781139540933 |
| 942 |
_2ddc _cEB |
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| 999 |
_c9603 _d9603 |
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