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University of Illinois at Urbana-Champaign

Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation

Abstract

dc:description

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.

Degree

thesis:*
Name thesis:degree_name
Ph.D.
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Mathematics
Grantor
University of Illinois at Urbana-Champaign
Year dc:date
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Yang, Jian
Contributors dc:contributor
  • Sowers, Richard B.
  • Pearson, Neil D.

Subjects

dc:subject × 1

Rights

Language dc:language
eng

Identifiers

dc:identifier.*
Identifier
(MiAaPQ)AAI3223755
OAI identifier oai:identifier
oai:www.ideals.illinois.edu:2142/86863

Chain of custody

source
Harvested from
University of Illinois - Urbana-Champaign
Base URL
www.ideals.illinois.edu/oai-pmh
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Yang, Jian. Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation. Dissertation thesis, University of Illinois at Urbana-Champaign, 2015. http://hdl.handle.net/2142/86863