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Maximum likelihood estimation of non-affine volatility processes

  • Chourdakis, Kyriakos
  • Dotsis, George
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    In this paper we develop a new estimation method for extracting non-affine latent stochastic volatility and risk premia from measures of model-free realized and risk-neutral integrated volatility. We estimate non-affine models with nonlinear drift and constant elasticity of variance and we compare them to the popular square-root stochastic volatility model. Our empirical findings are: (1) the square-root model is misspecified; (2) the inclusion of constant elasticity of variance and nonlinear drift captures stylized facts of volatility dynamics and (3) the square-root stochastic volatility model is explosive under the risk-neutral probability measure.

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    Article provided by Elsevier in its journal Journal of Empirical Finance.

    Volume (Year): 18 (2011)
    Issue (Month): 3 (June)
    Pages: 533-545

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    Handle: RePEc:eee:empfin:v:18:y:2011:i:3:p:533-545
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