Randomized Quasi-Monte Carlo Simulations for Basket Option Pricing where underlying assets follow a Time-Changed 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 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)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8885211
- author
- Säfwenberg, Gustav
- supervisor
- organization
- course
- FMS820 20161
- year
- 2016
- 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
- 2019-09-02 06:51:25
@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 Simulations for Basket Option Pricing where underlying assets follow a Time-Changed Meixner Levy Process}}, year = {{2016}}, }