Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1368-423X.2011.00357.x
DC FieldValue
dc.titleNon-stationary non-parametric volatility model
dc.contributor.authorHan, H.
dc.contributor.authorZhang, S.
dc.date.accessioned2014-05-05T10:25:35Z
dc.date.available2014-05-05T10:25:35Z
dc.date.issued2012-06
dc.identifier.citationHan, H., Zhang, S. (2012-06). Non-stationary non-parametric volatility model. Econometrics Journal 15 (2) : 204-225. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1368-423X.2011.00357.x
dc.identifier.issn13684221
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/52115
dc.description.abstractWe investigate a new non-stationary non-parametric volatility model, in which the conditional variance of time series is modelled as a non-parametric function of an integrated or near-integrated covariate. Importantly, the model can generate the long memory property in volatility and allow the unconditional variance of time series to be time-varying. These properties cannot be derived from most existing non-parametric or semi-parametric volatility models. We show that the kernel estimate of the model is consistent and its asymptotic distribution is mixed normal. For an empirical application of the model, we study the daily S&P 500 index return volatility using the VIX index as the covariate. It is shown that our model performs reasonably well both in within-sample and out-of-sample forecasts. © 2012 The Author(s). The Econometrics Journal © 2012 Royal Economic Society.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1368-423X.2011.00357.x
dc.sourceScopus
dc.subjectKernel estimation
dc.subjectlong memory property
dc.subjectnon-parametric ARCH
dc.subjectnon-parametric cointegrating regression
dc.subjectnon-stationarity
dc.subjectvolatility persistence
dc.typeArticle
dc.contributor.departmentECONOMICS
dc.description.doi10.1111/j.1368-423X.2011.00357.x
dc.description.sourcetitleEconometrics Journal
dc.description.volume15
dc.description.issue2
dc.description.page204-225
dc.identifier.isiut000311707800003
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