Analysis of financial data by generalized logistic distribution

Abstract

Risk management of financial assets requires the knowledge of the form of the probability distribution to estimate the probability of extreme price changes. It is not only the shape of the distribution which is important but the methods of estimation also plays a fundamental role to compare the risk-reward tradeoff for different trading strategies with a reasonable adequacy. In the present study the generalized logistic distribution is considered to fit stock market returns of Muscat Securities Market. The extreme quantiles are estimated by the method of probability weighted moments and are compared with that of method of moments.