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Review of Financial Studies Vol. 34 No. 1 2021

Implied Stochastic Volatility Models

Yacine Aït-Sahalia1; Chenxu Li2; Chen Xu Li3

1 Department of Economics, Princeton University, and NBER · 2 Guanghua School of Management, Peking University · 3 School of Business, Renmin University of China

Abstract

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.

DOI
10.1093/rfs/hhaa041
Volume
34
Issue
1
Pages
394-450
Language
en
Sources
openalex bibtex:phds-export.bib crossref

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