Generalized Hyperbolic Mmodel: European option Pricing in Developed and Eerging Markets

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