Option pricing : a particle filtering approach
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Date
October 15, 2015
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Abstract
Option pricing is a critical issue in the financial market. An investigation into the
use of Sampling Importance Resampling (SIR) filter for financial option pricing in
the Black-Schole model is performed. The impact of process noise, measurement
noise, and the number of particles on the accuracy and performance of SIR filter is
examined. The Black-Schole model is solved by the finite difference scheme. The
SIR filter is implemented by the use of the GARCH model and the Black-Schole
model with synthetic data. The effect of different process noise, measurement
noise, and number of particles on the SIR filter was examined. It was found that
the SIR filter performed well at lower process noise and high measurement noise
when considering profitability of a call option. Also, as the number of particle
decrease the SIR filter performed very well.
Description
A thesis submitted to the Department of Mathematics,
Kwame Nkrumah University of Science and Technology in
partial fulfillment of the requirement for the Degree
of Master of Science in Industrial Mathematics.