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Sowers, Richard B. Pearson, Neil D. Yang, Jian 2015-09-28T15:19:54Z 2015-09-28T15:19:54Z 10000-01-01 2006 2006 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. Made available in DSpace on 2015-09-28T15:19:54Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3223755.pdf: 2730833 bytes, checksum: 8056e5b8c34b228ae7f8fd737e3741dd (MD5) Previous issue date: 2006 Embargo set by: Seth Robbins for item 88144 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 95 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. http://hdl.handle.net/2142/86863 (MiAaPQ)AAI3223755 eng Economics, Finance Stochastic Volatility Models: Option Price Approximation, Asymptotics and Maximum Likelihood Estimation text Mathematics Mathematics University of Illinois at Urbana-Champaign Dissertation Ph.D.