Performance of GPU for a Tree Model for Convertible Bonds Pricing with Stock Price, Interest Rate, and Default Risks
Date Issued
2008
Date
2008
Author(s)
Wu, Yi-Chun
Abstract
Convertible bonds are now popular derivativeshich incorporate the features of bonds and equities.t is difficult to price convertible bonds with their various features. Chambers and Lu propose an accurate two-factor tree model for convertible bonds pricing.he time complexity of that algorithm is the relatively high O(n^3).n this thesis, we implement Chambers and Lu''s tree model on GPUs and CPUs. The code exploits GPUs'' computational power in parallel processing and high memory bandwidth.he numerical results show that the execution time on GPUs is several times faster than on CPUs, especially with n > 1000. The pricing results on GPUs are also as accurate as on CPUs. We can now obtain convertible bonds'' price much faster with Chamber and Lu''s model without sacrificing accuracy.
Subjects
convertible bonds
pricing
interest rate
default rate
option pricing
tree model
GPU
CUDA
parallel processing
Type
thesis
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