creator Xiong, Shuo advisor Unknown The thesis considers the problem of pricing different types of mountain range options by quasi-Monte Carlo simulation. Principal component analysis (PCA), also known as the singular value decomposition (SVD), has been applied widely to reduce the quasi-Monte Carlo sampling error in many financial problems. This is especially true for pricing single asset options. The purpose of this thesis is to investigate whether the singular component decomposition offers advantages for pricing mountain range options, which are exotic options based on multiple underlying assets. We consider our simulation in a complete, standard Black-Scholes market which has constant risk-free interest rate and covariance matrix. There are main two types of mountain range options simulated in this thesis: Altiplano and Himalayan. Key words : Mountain Range Option; Quasi-Monte Carlo; Singular Value Decompo- sition; Altiplano Option; Himalayan Option Submitted by Liana Khananashvili (khananashvili@iit.edu) on 2013-08-21T19:45:47Z No. of bitstreams: 1 Shuo Xiong's Master Thesis.pdf: 3199669 bytes, checksum: 0957e388cc1dcdf28aa968c0d80c1d29 (MD5) Made available in DSpace on 2013-08-21T19:45:47Z (GMT). No. of bitstreams: 1 Shuo Xiong's Master Thesis.pdf: 3199669 bytes, checksum: 0957e388cc1dcdf28aa968c0d80c1d29 (MD5) Previous issue date: 2012-12 M.S. in Applied Math, December 2012 2012-12-03 2012-12 http://hdl.handle.net/10560/3047 en Thesis born digital application/pdf In Copyright http://rightsstatements.org/page/InC/1.0/ Restricted Access MATH / Applied Mathematics Illinois Institute of Technology Affiliated department