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VOLATILITY MODELS AND THEIR APPLICATION TO OPTIONS PRICING AND RISK MANAGEMENT.

Sharapov, Andrey (2013) VOLATILITY MODELS AND THEIR APPLICATION TO OPTIONS PRICING AND RISK MANAGEMENT. Master's Thesis, University of Pittsburgh. (Unpublished)

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Abstract

We look at various volatility models and their applications. Starting from a basic linear GARCH model we proceed to more advanced linear GARCH models involving leverage effects
and asymmetry. We also look at some examples of non-linear GARCH models such as TGARCH, smooth transition GARCH and NNGARCH. ML estimation technique is considered. Some applications to options pricing and risk management are presented. Next we turn our attention to discrete and continuous stochastic volatility models. Filtering techniques such as Kalman filter, particle filter are presented and estimation approaches based on filtering as well as efficient method of moments are elaborated on in details. Finally we take a look at the implied volatility surface and some ways of its estimation.

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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Sharapov, Andreysharapov_andrey@mail.ru
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairStoffer, Davidstoffer@pitt.eduSTOFFER
Committee MemberKrafty, Robertkrafty@pitt.eduKRAFTY
Committee MemberJung, Sungkyusungkyu@pitt.eduSUNGKYU
Date: 25 January 2013
Date Type: Publication
Defense Date: 3 December 2012
Approval Date: 25 January 2013
Submission Date: 2 December 2012
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 110
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Statistics
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: volatility, GARCH, stochastic, Heston model, particle filter
Date Deposited: 25 Jan 2013 14:54
Last Modified: 25 Jan 2018 06:15
URI: http://d-scholarship.pitt.edu/id/eprint/16815

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