Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01z029p490h
Title: CDO PRICING IN PRACTICAL TIME: GPU Accelerated Monte Carlo Methods
Authors: Yang, Kevin
Advisors: Carmona, Rene
Department: Operations Research and Financial Engineering
Class Year: 2014
Abstract: The objective of this thesis is to explore the viability of Monte Carlo based methods of pricing Collateralized Debt Obligations (CDOs). From the early 2000s up until the global financial crisis, the single-factor Gaussian copula was the de-facto means of pricing these securities products. In recent years, usage of the copula has fallen out of favor due to the unreliability of measuring association of securities using correlation. Monte Carlo pricing methods have historically been too computationally expensive for generating timely quotes. The 2007-2008 global financial crisis and subsequent implosion of the CDO market coincided with massive growth in the field of parallel computing, namely the advent of NVidia’s GPU-based CUDA. In light of the partial recovery of the CDO market over the last two years, it is worth reexamining the feasibility of Monte Carlo methods in producing practical valuations.
Extent: 39
URI: http://arks.princeton.edu/ark:/88435/dsp01z029p490h
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

Files in This Item:
File SizeFormat 
Yang, Kevin final thesis.pdf594.73 kBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.