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dc.contributor.authorChou, RYen_US
dc.date.accessioned2014-12-08T15:20:16Z-
dc.date.available2014-12-08T15:20:16Z-
dc.date.issued2005-06-01en_US
dc.identifier.issn0022-2879en_US
dc.identifier.urihttp://dx.doi.org/10.1353/mcb.2005.0027en_US
dc.identifier.urihttp://hdl.handle.net/11536/14403-
dc.description.abstractWe propose a dynamic model for the high/low range of asset prices within fixed time intervals: the Conditional Autoregressive Range Model (henceforth CARR). The evolution of the conditional range is specified in a fashion similar to the conditional variance models as in GARCH and is very similar to the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998). Extreme value theories imply that the range is an efficient estimator of the local volatility, e.g., Parkinson (1980). Hence, CARR can be viewed as a model of volatility. Out-of-sample volatility forecasts using the S&P500 index data show that the CARR model does provide sharper volatility estimates compared with a standard GARCH model.en_US
dc.language.isoen_USen_US
dc.subjectCARRen_US
dc.subjecthigh/low rangeen_US
dc.subjectextreme valuesen_US
dc.subjectGARCHen_US
dc.subjectACDen_US
dc.titleForecasting financial volatilities with extreme values: The Conditional Autoregressive Range (CARR) Modelen_US
dc.typeArticleen_US
dc.identifier.doi10.1353/mcb.2005.0027en_US
dc.identifier.journalJOURNAL OF MONEY CREDIT AND BANKINGen_US
dc.citation.volume37en_US
dc.citation.issue3en_US
dc.citation.spage561en_US
dc.citation.epage582en_US
dc.contributor.department經營管理研究所zh_TW
dc.contributor.departmentInstitute of Business and Managementen_US
dc.identifier.wosnumberWOS:000230133700010-
dc.citation.woscount68-
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