stock return prediction models; Estimating the distribution of total market returns and its fluctuations based on the Laplace distribution

 In most return forecasting models, the return of the total market is used as one of the factors affecting the return of securities. In most of these models, such as the pricing model of capital assets and Black-Scholes, the data distribution is assumed to be normal. This is while the distribution of the total return is not necessarily normal and often has a significant difference from the normal distribution. If such a hypothesis is confirmed, the expected return predicted by these models will not be very effective in financial decisions. The purpose of this research is to model the total return of Tehran Stock Exchange based on the Laplace distribution and examine the dependence of the total return fluctuations on the desired distribution. In order to examine the distribution of the total daily return and its weekly fluctuations, data related to a 15-year period between 1387 and 1401 and R statistical software were used. The data analysis showed that the total daily return followed the Laplace distribution and the weekly fluctuations of the total return followed the distribution obtained based on the Laplace distribution. These findings make the use of models with the assumption of normality of total return to predict stock returns in Tehran Stock Exchange a major challenge and are a clear proof of the ineffectiveness of these models. .