MODELING STOCK-CLOSING PRICES: EVIDENCE FROM THE BANKING SECTOR OF JORDAN

This study aims to find the best-fitted distribution of the average closing price (ACP) for the Amman Stock Exchange banking sector using various distributions models, namely, Normal, Gamma, Burr, Weibull, Bareto, lognormal, Log logistic, Exponential, and Gumbel distribution. This will enable financial analysts to forecast stock prices to build their buying and selling decisions. The methodology was applied according to the comparison between maximum likelihood estimation, moment matching, quantile matching and maximum goodness-of-fit estimation. The result of computing the different goodness of fit statistics (K.S), (CvM) and (A.D) and the other statistics based on the log-likelihood (AIC and BIC). The best-fitted distributions have the smaller values for each goodness of fit statistics. The results emphasized that the Gamma distribution is the most appropriate one, which has the lowest values of AIC (364.6), and BIC (373.9).