Files in this item

FilesDescriptionFormat

application/pdf

application/pdf3223755.pdf (3MB)Restricted to U of Illinois
(no description provided)PDF

Description

Title:Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation
Author(s):Yang, Jian
Doctoral Committee Chair(s):Sowers, Richard B.; Pearson, Neil D.
Department / Program:Mathematics
Discipline:Mathematics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Economics, Finance
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.
Issue Date:2006
Type:Text
Language:English
Description:95 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.
URI:http://hdl.handle.net/2142/86863
Other Identifier(s):(MiAaPQ)AAI3223755
Date Available in IDEALS:2015-09-28
Date Deposited:2006


This item appears in the following Collection(s)

Item Statistics