Sun, Qiang
(2010)
ANALYSIS OF AN IMPORTANCE SAMPLING IN A STOCHASTIC VOLATILITY MODEL.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
This thesis analyzes an importance sampling method whose effectiveness relies in many cases onthe selection of sampler's parameters. In its typical application of a Taylor's stochasticvolatility model, a new approach, referred to as `universal importance sampling', was designedand shown to be much more efficient than those in the literature, such as the sequential importancesampling. One obvious advantage of the universal sampling is that the parameters selected do notrely on the sampling process, so that Monte Carlo simulations can be done on different computerswith a final averaging.
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Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
1 October 2010 |
Date Type: |
Completion |
Defense Date: |
19 May 2010 |
Approval Date: |
1 October 2010 |
Submission Date: |
16 July 2010 |
Access Restriction: |
5 year -- Restrict access to University of Pittsburgh for a period of 5 years. |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Mathematics |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
Importance Sampling; Maximum Likelihood.; Monte Carlo; Stochastic Volatility |
Other ID: |
http://etd.library.pitt.edu/ETD/available/etd-07162010-131350/, etd-07162010-131350 |
Date Deposited: |
10 Nov 2011 19:51 |
Last Modified: |
15 Nov 2016 13:46 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/8408 |
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