Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/53938
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dc.contributor.authorFeunou, Brunoen_US
dc.contributor.authorTédongap, Roméoen_US
dc.date.accessioned2011-10-10en_US
dc.date.accessioned2011-12-15T12:58:28Z-
dc.date.available2011-12-15T12:58:28Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/53938-
dc.description.abstractWe develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on current factors and past information, what we term contemporaneous asymmetry. Conditional skewness is an explicit combination of the conditional leverage effect and contemporaneous asymmetry. We derive analytical formulas for various return moments that are used for generalized method of moments estimation. Applying our approach to S&P500 index daily returns and option data, we show that one- and two-factor SVS models provide a better fit for both the historical and the risk-neutral distribution of returns, compared to existing affine generalized autoregressive conditional heteroskedasticity (GARCH) models. Our results are not due to an overparameterization of the model: the one-factor SVS models have the same number of parameters as their one-factor GARCH competitors.en_US
dc.language.isoengen_US
dc.publisher|aBank of Canada |cOttawaen_US
dc.relation.ispartofseries|aBank of Canada Working Paper |x2011,20en_US
dc.subject.jelC1en_US
dc.subject.jelC5en_US
dc.subject.jelG1en_US
dc.subject.jelG12en_US
dc.subject.ddc330en_US
dc.subject.keywordEconometric and statistical methodsen_US
dc.subject.keywordAsset pricingen_US
dc.titleA stochastic volatility model with conditional skewnessen_US
dc.typeWorking Paperen_US
dc.identifier.ppn669550655en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US

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