Modeling the effects of Tehran Stock Exchange investors' sentiment on stock price within a heterogeneous agent model

The purpose of this article is to investigate the effects of investors' sentiments on stock prices and its modeling in the framework of the heterogeneous agent model. In this regard, by using simulation, stock prices are calculated at the time of investors' sentiments, and the results are compared with stock prices in the real market to determine how much the simulated market matches the real market. The current research is descriptive in terms of purpose and content analysis has been used to evaluate the simulation results. Therefore, first, the point of crash of the stock market was determined in the framework of theoretical discussions. Then, the input variables including positive sentiments, negative sentiments and herd behavior were entered into the model and the price simulation process was done for each of the biases during the market crash. Considering the heterogeneous agents in the market and the dynamics of investors' behavior, Monte Carlo simulation was used and coding was done in MATLAB. By comparing simulated prices with real market prices at the time of investors' sentiments, the model's ability to estimate real market prices was investigated. The research results show that the heterogeneous factor model can predict the effects of investors' emotions when the stock market falls. Especially when negative emotions appear in the market, the presented model provides the best estimate compared to the real market.