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Stochastic volatility models: Optio...

Yang, Jian.

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Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation./
Author:	Yang, Jian.
Description:	95 p.
Notes:	Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3841.
Contained By:	Dissertation Abstracts International67-07B.
Subject:	Mathematics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3223755
ISBN:	9780542777660

Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation.
Yang, Jian.

Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation. - 95 p.

Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3841.

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.

This thesis deals with analytical approximation of option pricing; option price asymptotics and maximum likelihood estimation under a general class of stochastic volatility models.

ISBN: 9780542777660Subjects--Topical Terms:

515831
Mathematics.

Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation.
LDR:02265nmm 2200313 4500 001 1834109
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008 130610s2006 eng d
020 $a 9780542777660
035 $a (UMI)AAI3223755
035 $a AAI3223755
040 $a UMI $c UMI
100 1 $a Yang, Jian. $3 1904519
245 1 0 $a Stochastic volatility models: Option price approximation, asymptotics and maximum likelihood estimation.
300 $a 95 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3841.
500 $a Advisers: Richard B. Sowers; Neil D. Pearson.
502 $a Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.
520 $a This thesis deals with analytical approximation of option pricing; option price asymptotics and maximum likelihood estimation under a general class of stochastic volatility models.
520 $a In the first part we develop an asymptotic expansion for short term option price under a general class of stochastic volatility models. The explicit expansion is obtained by decomposing; the pricing PDE operator into the Black-Scholes part and a stochastic volatility correction part. The Black-Scholes part is essentially a heat operator which makes lots of calculation explicit since the resulting integrals are Gaussian. We also study several type of option price asymptotics under stochastic volatility model in the sense of near maturity and near the money.
520 $a 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.
590 $a School code: 0090.
650 4 $a Mathematics. $3 515831
650 4 $a Economics, Finance. $3 626650
690 $a 0405
690 $a 0508
710 2 0 $a University of Illinois at Urbana-Champaign. $3 626646
773 0 $t Dissertation Abstracts International $g 67-07B.
790 1 0 $a Sowers, Richard B., $e advisor
790 1 0 $a Pearson, Neil D., $e advisor
790 $a 0090
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3223755