designing the optimal investment model based on the parameters of predicting stock returns and the risk factors of disruptive traders

Noise traders cause severe fluctuations and deviation of asset values from their intrinsic value; thus, this article designs an optimal investment model based on the parameters of predicting stock returns and noise trader risk factors. this is an applied post-event paper. in this article, first, the stock returns predicting parameters are obtained followed by the noise traders’ risk factors obtained through behavioural error or the beta difference in transactions, according to the combined regression model or models, which are the results of the risk factors. then, noise traders and stock return predictor variables were designed and tested using econometric software, including eviews9 software and matlab algorithmic models. the statistical population of this research includes all companies admitted to the tehran stock exchange, whose shares were traded until march 19, 2020. also, in this research, pca, gsadf, and logit methods were used to determine the impact of noise traders in determining the incidence of the bubble used in the tehran stock exchange. the research findings show that noise traders have a positive and significant effect on the occurrence of a bubble, and an increase of one unit of optimistic sentiments and optimistic sentiments with a break in the stock market increases the probability of a bubble occurrence.