Modeling Investors' Behavior by Using Psychological Variables with Interpretive Structural Modeling Approach to Recognize Investment Decision Making Errors

Interpretive structural modeling is one of the methods of system design, especially management and accounting systems. This technique starts by identifying the variables and then establishes the underlying relationships between the variables using the expertise and knowledge of the experts and finally the multilevel structural model. In this study, using this approach, behavioral biases are structured to influence the decision making of real active investors in the stock market. For this purpose, expert experts in this field were used and 12 behavioral influences affecting investor behavior / decision making were identified and then coded using the matrix of initial access, their impact on investor behavior / decision model. Finally, they were leveled using the final matrix. The results of interpretive structural modeling showed that behavioral bias affecting investors' decision making was modeled at six levels, and imaginative power bias was at the highest level and more effective than other bias and late bias bias.