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Volatility forecasting with range models: An evaluation of new alternatives to the CARR model

dc.contributor.authorMiralles Quirós, José Luis
dc.contributor.authorDaza Izquierdo, Julio
dc.date.accessioned2012-04-23T12:38:50Z
dc.date.available2012-04-23T12:38:50Z
dc.date.issued2011-07
dc.description.abstractThe aim of this paper is to analyze the forecasting ability of the CARR model proposed by Chou (2005) using the S&P 500. We extend the data sample, allowing for the analysis of different stock market circumstances and propose the use of various range estimators in order to analyze their forecasting performance. Our results show that there are two range-based models that outperform the forecasting ability of the GARCH model. The Parkinson model is better for upward trends and volatilities which are higher and lower than the mean while the CARR model is better for downward trends and mean volatilities.por
dc.identifier.urihttp://hdl.handle.net/10400.21/1430
dc.language.isoengpor
dc.peerreviewedyespor
dc.subjectCARRpor
dc.subjectGARCHpor
dc.subjectRange estimatorspor
dc.subjectForecasting performancepor
dc.titleVolatility forecasting with range models: An evaluation of new alternatives to the CARR modelpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceXII Iberian-Italian Congress of Financial and Actuarial Mathematicspor
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor

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