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Alternative models for stock price dynamics

Chernov, Mikhail (2003) Alternative models for stock price dynamics. Journal of Econometrics, 116 (1-2). pp. 225-257. ISSN 0304-4076

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Identification Number: 10.1016/S0304-4076(03)00108-8

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 previous termmodelsnext term 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.

Item Type: Article
Official URL: http://www.journals.elsevier.com/journal-of-econom...
Additional Information: © 2003 Elsevier
Divisions: Finance
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation and Selection
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications
G - Financial Economics > G1 - General Financial Markets > G13 - Contingent Pricing; Futures Pricing
Date Deposited: 10 Nov 2011 10:26
Last Modified: 22 Feb 2024 06:30
URI: http://eprints.lse.ac.uk/id/eprint/39397

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