Modelling the distribution of the extreme share returns in Singapore

This study aims to model the probability distribution of the extreme daily share returns in Singapore Stock Exchange over the period 1973 to 2005. For that reason the suitability of the Generalized Extreme Value (GEV), Generalized Pareto (GP) and Generalized Logistic (GL) distributions are investigated. The empirical results indicate that the GL distribution best fitted the empirical data over the period of study. Using the too much celebrated GEV and GP distributions for risk assessment could, therefore, lead to underestimation of the extreme risk which could potentially lead to inadequate protection against catastrophic losses.