Randomized QuasiMonte Carlo Simualtions for Basket Option Pricing where underlying assets follow a TimeChanged Meixner Levy Process
(2016) FMS820 20161Mathematical Statistics
 Abstract
 Using derivative securities can help investors increase their expected returns
as well as minimize their exposure to risk. For a riskaverse investor, options
can oer both insurance and leverage and for a more riskloving investor they
can be used as speculation. Basket option is a kind of option whose payo depends
on an arbitrary portfolio of assets. The basket is made out of a weighted
sum of assets. Pricing these kinds of options require multivariate asset pricing
techniques which still remains a challenge. We aim to price basket options
by using dierent Monte Carlo methods and compare their performance. We
will test both quasiMonte Carlo methods as well as randomized quasiMonte
Carlo methods in order to try to speed up the... (More)  Using derivative securities can help investors increase their expected returns
as well as minimize their exposure to risk. For a riskaverse investor, options
can oer both insurance and leverage and for a more riskloving investor they
can be used as speculation. Basket option is a kind of option whose payo depends
on an arbitrary portfolio of assets. The basket is made out of a weighted
sum of assets. Pricing these kinds of options require multivariate asset pricing
techniques which still remains a challenge. We aim to price basket options
by using dierent Monte Carlo methods and compare their performance. We
will test both quasiMonte Carlo methods as well as randomized quasiMonte
Carlo methods in order to try to speed up the convergance rate. We will
assume a Levy market model with stochastic volatility through an integrated
CIRprocess as a stochastic time change. More specically we are going to
model the data using the Meixner distribution. In order to calibrate the
model parameters we use S&P 500 index vanilla options and the fast Fourier
transform (FFT). (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/studentpapers/record/8885211
 author
 Säfwenberg, Gustav
 supervisor

 Magnus Wiktorsson ^{LU}
 organization
 course
 FMS820 20161
 year
 2016
 type
 H2  Master's Degree (Two Years)
 subject
 language
 English
 id
 8885211
 date added to LUP
 20160630 15:49:07
 date last changed
 20160630 15:49:07
@misc{8885211, abstract = {Using derivative securities can help investors increase their expected returns as well as minimize their exposure to risk. For a riskaverse investor, options can oer both insurance and leverage and for a more riskloving investor they can be used as speculation. Basket option is a kind of option whose payo depends on an arbitrary portfolio of assets. The basket is made out of a weighted sum of assets. Pricing these kinds of options require multivariate asset pricing techniques which still remains a challenge. We aim to price basket options by using dierent Monte Carlo methods and compare their performance. We will test both quasiMonte Carlo methods as well as randomized quasiMonte Carlo methods in order to try to speed up the convergance rate. We will assume a Levy market model with stochastic volatility through an integrated CIRprocess as a stochastic time change. More specically we are going to model the data using the Meixner distribution. In order to calibrate the model parameters we use S&P 500 index vanilla options and the fast Fourier transform (FFT).}, author = {Säfwenberg, Gustav}, language = {eng}, note = {Student Paper}, title = {Randomized QuasiMonte Carlo Simualtions for Basket Option Pricing where underlying assets follow a TimeChanged Meixner Levy Process}, year = {2016}, }