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This study investigates Iran’s stock market by a non-Gaussian distribution function. To estimate this distribution function, Bayesian methods and Markov chain Monte Carlo simulation technique is used. Tehran stock market daily data during August 23, 2002 to February 19, 2011 has been analyzed in this study. The results confirm the existence of a non-Gaussian distribution with a right skewness and fat tail sequence. Therefore, an unexpected crisis in the Iran stock market could not be ignored. The results also confirmed the hypothesis of asymptotically stable Distribution.