Compilation and presentation of a trend model for the volume of transactions of investors based on the components of psychology by Fuzzy Neural Network Approach

Analyzing the impact of investor psychological components, including their attitudes and behaviors on investment decisions in financial-behavioral theory, can lead to a fair distribution of services to capital market participants. Creating such justice requires understanding the decision-making behaviors of investors. By conceptually and operationally defining the components affecting this process, a comprehensive model for the formation of the trading volume process based on the components of investor psychology in the Tehran Stock Exchange was developed using the fuzzy neural network approach. The research period is from 2013 to 2018 and the statistical sample consists of 138 companies listed on the Tehran Stock Exchange. The psychological components of research include rationality, investor optimism, and pessimism, loss aversion, and momentum. Findings indicate that there is a significant negative and positive relationship between the variables of investors' pessimism and optimism and the process of trading volume, respectively; but there is no significant relationship between the variables of investors' rationality, loss-aversion, and momentum with the process of the trading volume.