Fast Valuation of Options under Parameter Uncertainty
(2014) 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
@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}}, language = {{eng}}, note = {{Student Paper}}, title = {{Fast Valuation of Options under Parameter Uncertainty}}, year = {{2014}}, }