The distribution of extreme share return in different Malaysian economic circumstances

Abstract

This paper presents a study on the performance of probability distribution in various financial periods by investigating the effect of economic cycle on extreme stock return activity. Malaysian stock price KLCI data from 1994-2008 were split into three economy periods corresponding to the growth, financial crisis, and recovery. Four prevalent distributions, specifically generalized lambda distribution (GLD), generalized extreme value (GEV), generalized logistic (GLO), and generalized pareto (GPA) had been employed to model weekly and monthly maximum and minimum share returns of Kuala Lumpur Composite Index (KLCI). L-moment approach had been used to estimate the parameter, while k-sample Anderson darling (k-ad) test had been applied to measure the goodness of fit estimation. In conclusion, GLD is the most appropriate distribution to represent weekly maximum and minimum returns for overall three economic scenarios in Malaysia.