Fast Valuation of Options under Parameter Uncertainty
(2014) In Master's Theses in Mathematical Sciences MASM01 20141Mathematical Statistics
- Abstract (Swedish)
- Option valuation is typically done under the unrealistic assumption of perfect knowledge
about model parameters. This thesis shows that risk-neutral valuation, while
still adressing the parameter uncertainty, can be computed for a variety of models
within the Fourier framework. This results in a computationally inexpensive
method for valuating options. A study of S&P500 index option data shows that the
method improves the predictive performances of the Black&Scholes, Merton and
Heston models.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/4519486
- author
- Wu, Hanna
- supervisor
- organization
- course
- MASM01 20141
- year
- 2014
- type
- H2 - Master's Degree (Two Years)
- subject
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUNFMS-3058-2014
- ISSN
- 1404-6342
- other publication id
- 2014:E41
- language
- English
- id
- 4519486
- date added to LUP
- 2014-06-26 13:07:59
- date last changed
- 2024-10-14 15:23:09
@misc{4519486, abstract = {{Option valuation is typically done under the unrealistic assumption of perfect knowledge about model parameters. This thesis shows that risk-neutral valuation, while still adressing the parameter uncertainty, can be computed for a variety of models within the Fourier framework. This results in a computationally inexpensive method for valuating options. A study of S&P500 index option data shows that the method improves the predictive performances of the Black&Scholes, Merton and Heston models.}}, author = {{Wu, Hanna}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{Fast Valuation of Options under Parameter Uncertainty}}, year = {{2014}}, }