Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation
Yang, Jian
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https://hdl.handle.net/2142/86863
Description
Title
Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation
Author(s)
Yang, Jian
Issue Date
2006
Doctoral Committee Chair(s)
Sowers, Richard B.
Pearson, Neil D.
Department of Study
Mathematics
Discipline
Mathematics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Economics, Finance
Language
eng
Abstract
The second part of this thesis describes an approach that uses the above asymptotic expansion to invert, the option pricing function and extract the latent volatility, thereby overcoming one of the key difficulties in the estimation problem. The method is applied to estimate three popular stochastic volatility models, two of which have not previously been amenable to maximum likelihood estimation with option price data other than through the use of proxies for the latent volatility.
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