Monte Carlo methods for the estimation of value-at-risk and related risk measures

Master Thesis

2011

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http://hdl.handle.net/11427/10966
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thesis_com_2011_marks_d.pdf (1.21 MB)
Authors
Marks, Dean
Supervisors
Becker, Ronald
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University of Cape Town

Department
Division of Actuarial Science
Faculty
Faculty of Commerce
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Abstract
Nested Monte Carlo is a computationally expensive exercise. The main contributions we present in this thesis are the formulation of efficient algorithms to perform nested Monte Carlo for the estimation of Value-at-Risk and Expected-Tail-Loss. The algorithms are designed to take advantage of multiprocessing computer architecture by performing computational tasks in parallel. Through numerical experiments we show that our algorithms can improve efficiency in the sense of reducing mean-squared error.
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Mathematical Finance

Reference:

Marks, D. 2011. Monte Carlo methods for the estimation of value-at-risk and related risk measures. University of Cape Town.

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