Presenting a profit forecasting model based on behavioral tax of companies listed on the Tehran Stock Exchange

Document Type : Research Paper


Department of Accounting, Islamic Azad University, South Tehran Branch, Tehran, Iran



The purpose of this study was to provide a profit forecasting model based on the behavioral tax of companies listed on the Tehran Stock Exchange; Research method in terms of purpose, basic-applied in terms of data type, quantitative; Depending on the time of data collection, it was a combination (time series and cross-sectional) and according to the method of data collection or the nature and method of research, survey and library. The statistical population of the first part of the study included all companies listed on the Tehran Stock Exchange. To determine the samples of this part of the research, a systematic sampling method was used, which was finally selected as a sample by applying the desired filters to 120 companies. The second group of the statistical population of this study included all investors in the Tehran Stock Exchange who were selected using the cluster random sampling method and the Cochran Orkut formula of 385 people as a sample. Modern Rahdavard and Tadbiardazar database software and the distribution of researcher-made questionnaires based on standard questionnaires were used to collect the data. In the inferential and quantitative sections, we used two models of data panel regression and structural equations to answer the research questions. The results showed that behavioral variables such as management overconfidence, stock price information efficiency, stock price synchronization, information efficiency, reluctant effect, mass effect, emotional bias, cognitive bias and exponential bias Corporate profits are effective Also, indicators of economic confidence and information reliability affect the interaction between behavioral decisions and corporate profits.


Articles in Press, Corrected Proof
Available Online from 22 February 2023
  • Receive Date: 19 June 2022
  • Revise Date: 14 August 2022
  • Accept Date: 26 August 2022
  • First Publish Date: 22 February 2023