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dc.contributor.authorCorradi, Valentinaen_US
dc.contributor.authorDistaso, Walteren_US
dc.contributor.authorSwanson, Norman R.en_US
dc.date.accessioned2011-06-14en_US
dc.date.accessioned2012-06-25T12:02:08Z-
dc.date.available2012-06-25T12:02:08Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/59500-
dc.description.abstractIn recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned quantities. The kernel functions used in our analysis are based on different realized volatility measures, which are constructed using the ex post variation of asset prices. A set of sufficient conditions under which the estimators are asymptotically equivalent to their unfeasible counterparts, based on the unobservable volatility process, is provided. Asymptotic normality is also established. The efficacy of the estimators is examined via Monte Carlo experimentation, and an empirical illustration based upon data from the New York Stock Exchange is provided.en_US
dc.language.isoengen_US
dc.publisherDep. of Economics, Rutgers, the State Univ. of New Jersey New Brunswick, NJen_US
dc.relation.ispartofseriesWorking Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,08en_US
dc.subject.jelC22en_US
dc.subject.jelC53en_US
dc.subject.jelC14en_US
dc.subject.ddc330en_US
dc.subject.keyworddiffusionsen_US
dc.subject.keywordintegrated volatilityen_US
dc.subject.keywordrealized volatility measuresen_US
dc.subject.keywordkernelsen_US
dc.subject.keywordmicrostructure noiseen_US
dc.subject.keywordconditional confidence intervalsen_US
dc.subject.keywordjumpsen_US
dc.subject.keywordpredictionen_US
dc.subject.stwBörsenkursen_US
dc.subject.stwVolatilitäten_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwInferenzstatistiken_US
dc.subject.stwNichtparametrisches Verfahrenen_US
dc.subject.stwTheorieen_US
dc.titlePredictive inference for integrated volatilityen_US
dc.typeWorking Paperen_US
dc.identifier.ppn662028244en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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