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Randomized Quasi-Monte Carlo Simualtions for Basket Option Pricing where underlying assets follow a Time-Changed Meixner Levy Process

Säfwenberg, Gustav (2016) FMS820 20161
Mathematical Statistics
Abstract
Using derivative securities can help investors increase their expected returns
as well as minimize their exposure to risk. For a risk-averse investor, options
can oer both insurance and leverage and for a more risk-loving 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 quasi-Monte Carlo methods as well as randomized quasi-Monte
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 risk-averse investor, options
can oer both insurance and leverage and for a more risk-loving 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 quasi-Monte Carlo methods as well as randomized quasi-Monte
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
CIR-process 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)
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author
Säfwenberg, Gustav
supervisor
organization
course
FMS820 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8885211
date added to LUP
2016-06-30 15:49:07
date last changed
2016-06-30 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 risk-averse investor, options
can oer both insurance and leverage and for a more risk-loving 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 quasi-Monte Carlo methods as well as randomized quasi-Monte
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
CIR-process 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 Quasi-Monte Carlo Simualtions for Basket Option Pricing where underlying assets follow a Time-Changed Meixner Levy Process},
  year         = {2016},
}