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Implied Stochastic Volatility Models
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DOI：10.1093/rfs/hhaa041.png)
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Abstract
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This paper proposes implied stochastic volatility models designed to fit option-implied volatility data and implements a new estimation method for such models. The method is based on explicitly linking observed shape characteristics of the implied volatility surface to the coefficient functions that define the stochastic volatility model. The method can be applied to estimate a fully flexible nonparametric model, or to estimate by the generalized method of moments any arbitrary parametric stochastic volatility model, affine or not. Empirical evidence based on S&P 500 index options data show that the method is stable and performs well out of sample.
Keywords:
MAXIMUM-LIKELIHOOD-ESTIMATION
NONPARAMETRIC-ESTIMATION
ASYMPTOTIC-EXPANSION
RISK PREMIA
OPTIONS
APPROXIMATION
SPECIFICATION
DYNAMICS
RETURNS
FORMULA
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