dc.contributor.author | Mwaniki, JI | |
dc.contributor.author | Konlack, Virginie S | |
dc.date.accessioned | 2013-06-20T14:14:31Z | |
dc.date.available | 2013-06-20T14:14:31Z | |
dc.date.issued | 2007 | |
dc.identifier.uri | http://www.math.ku.dk/english/research/conferences/levy2007/ALLabstracts.pdf#page=82 | |
dc.identifier.uri | http://hdl.handle.net/11295/36930 | |
dc.description.abstract | Generalized Hyperbolic Distribution and some of it subclas
ses like normal, hyperbolic and variance gamma distri-
butions are used to fit daily log returns of eight listed compa
nies in Nairobi Stock Exchange (NSE) and Montr ́eal
Exchange. We use EM-based ML estimation procedure to locate
parameters of the model. Densities of Simulated
and Empirical data are used to measure how well model fits the d
ata. We use goodness of fit statistics to compare the
selected distributions. Empirical results indicate that G
eneralized hyperbolic Distribution is capable of correcti
ng
bias of Black-Scholes and Merton normality assumption both
in Developed and Emerging markets. Moreover both
markets do have different stochastic time clock | en |
dc.language.iso | en | en |
dc.title | Generalized Hyperbolic Mmodel: European option Pricing in Developed and Eerging Markets | en |
dc.type | Article | en |
local.publisher | College of Physical and Biological Sciences | en |