Structural modeling of the precondition of financial behavior of investors in Iran’s stock market

This study followed the design of a model to predict the financial behavior of investors in the Iranian stock market. To identify the criteria, the content analysis of scientific texts related to the research topic was used and 24 criteria were identified. Self-interactive matrix and expert opinion was based on interpretive structural modeling method and a five-level model was obtained. To determine the type of variables, MICMAC analysis was used. In the five-level model of this study, the variables of informal news and herd behavior were the most influential in the fifth level and believable, personal judgment and decision making error were the most influential variables of the model that were ranked one. The McMask analysis also indicated that informal news variables with low dependence and high conductivity, foregrounding, decision error, believable and personal judgment were also dependent, with strong dependence and low conductivity, and other variables were interface type. Given the level at which the criteria are met and how effective they are at the end, conclusions and suggestions were also provided.