Evaluating the impact of psychological factors on newcomers to the Tehran Stock Exchange through Machine Learning Approach

The Tehran Stock Exchange has prepared the ground of entry a host number of people in recent months, who chiefly have not enough knowledge of the impact of existingpsychological factors in this financial market. Forasmuch as these factors can jeopardize their investments, identifying and assessing these factors seem to be necessary. Therefore, in the present study, after designing a questionnaire with 5-Likert scale and being filled it out by newcomers who were investing in the Tehran Stock Exchange from March to August 2020, their answers have analysed through Machine Learning Approach. The results of the statistical tests have shown that Representativeness Bias and Overconfidence Bias have significant impacts on the investment decision-making, while it cannot be seen any evidence of the influence of Gambler Fallacy and Loss-Aversion Bias on newcomers.

کلیدواژه ها:

Behavioral Finance ، Psychological Factors ، Newcomers’ Decision Making ، The Tehran Stock Exchange ، Machine Learning Approach