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dc.contributor.author Chernov, M
dc.contributor.author Gallant, AR
dc.contributor.author Ghysels, E
dc.contributor.author Tauchen, G
dc.date.accessioned 2010-03-09T15:28:56Z
dc.date.issued 2003-09-01
dc.identifier.citation Journal of Econometrics, 2003, 116 (1-2), pp. 225 - 257
dc.identifier.issn 0304-4076
dc.identifier.uri http://hdl.handle.net/10161/1892
dc.description.abstract This paper evaluates the role of various volatility specifications, such as multiple stochastic volatility (SV) factors and jump components, in appropriate modeling of equity return distributions. We use estimation technology that facilitates nonnested model comparisons and use a long data set which provides rich information about the conditional and unconditional distribution of returns. We consider two broad families of models: (1) the multifactor loglinear family, and (2) the affine-jump family. Both classes of models have attracted much attention in the derivatives and econometrics literatures. There are various tradeoffs in considering such diverse specifications. If pure diffusion SV models are chosen over jump diffusions, it has important implications for hedging strategies. If logarithmic models are chosen over affine ones, it may seriously complicate option pricing. Comparing many different specifications of pure diffusion multifactor models and jump diffusion models, we find that (1) log linear models have to be extended to two factors with feedback in the mean reverting factor, (2) affine models have to have a jump in returns, stochastic volatility or probably both. Models (1) and (2) are observationally equivalent on the data set in hand. In either (1) or (2) the key is that the volatility can move violently. As we obtain models with comparable empirical fit, one must make a choice based on arguments other than statistical goodness-of-fit criteria. The considerations include facility to price options, to hedge and parsimony. The affine specification with jumps in volatility might therefore be preferred because of the closed-form derivatives prices. © 2003 Elsevier B.V. All rights reserved.
dc.format.extent 225 - 257
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartof Journal of Econometrics
dc.relation.isversionof 10.1016/S0304-4076(03)00108-8
dc.title Alternative models for stock price dynamics
dc.type Journal Article
dc.department Economics
pubs.issue 1-2
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Faculty
pubs.organisational-group /Duke/Trinity College of Arts & Sciences
pubs.organisational-group /Duke/Trinity College of Arts & Sciences/Economics
pubs.publication-status Published
pubs.volume 116

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