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Data cloning for a threshold asymmetric stochastic volatility model

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dc.affiliation.dptoUC3M. Departamento de Estadísticaes
dc.contributor.authorMarín Díazaraque, Juan Miguel
dc.contributor.authorLopes Moreira Da Veiga, María Helena
dc.contributor.editorUniversidad Carlos III de Madrid. Departamento de Estadísticaes
dc.date.accessioned2023-02-14T17:25:14Z
dc.date.available2023-02-14T17:25:14Z
dc.date.issued2023-02-14
dc.description.abstractIn this paper, we propose a new asymmetric stochastic volatility model whose asymmetry parameter can change depending on the intensity of the shock and is modeled as a threshold function whose threshold depends on past returns. We study the model in terms of leverage and propagation using a new concept that has recently appeared in the literature. We find that the new model can generate more leverage and propagation than a well-known asymmetric volatility model. We also propose to estimate the parameters of the model by cloning data. We compare the estimates in finite samples of data cloning and a Bayesian approach and find that data cloning is often more accurate. Data cloning is a general technique for computing maximum likelihood estimators and their asymptotic variances using a Markov chain Monte Carlo (MCMC) method. The empirical application shows that the new model often improves the fit compared to the benchmark model. Finally, the new proposal together with data cloning estimation often leads to more accurate 1-day and 10-day volatility forecasts, especially for return series with high volatility.en
dc.identifier.issn2387-0303es
dc.identifier.urihttps://hdl.handle.net/10016/36569
dc.identifier.uxxiDT/0000002054es
dc.language.isoenges
dc.relation.ispartofseriesWorking paper Statistics and Econometricsen
dc.relation.ispartofseries23-03
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.otherAsymmetric Stochastic Volatilityen
dc.subject.otherData Cloningen
dc.subject.otherLeverage Effecten
dc.subject.otherPropagationen
dc.subject.otherVolatility Forecastingen
dc.titleData cloning for a threshold asymmetric stochastic volatility modelen
dc.typeworking paper*
dspace.entity.typePublication
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