Impact of personality traits on investment decision-making: Mediating role of investor sentiment in India

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The behavior of investors and their investment decision-making process in the financial markets are guided by psychological (sentiments) and personal characteristics (personality traits). Research in recent years has shown the connection between investor sentiment and personality traits and investment decisions. Though academic works in the field of behavioral finance are growing, studies on personality traits and investment decision-making with investor sentiment as a mediator are sparse. To this end, the paper aims to analyze the effects of Indian retail investors’ Big-five personality traits (Neuroticism, Extraversion, Openness to experience, Agreeableness, and Conscientiousness) on their short-term and long-term investment decision-making with the mediating effect of investor sentiment. The study employs the Partial Least Square-Structural Equation Model to test the framed hypotheses. The findings of the study reveal that Neuroticism has a significant positive effect (β=0.352, p<0.05) on investor sentiment. It further shows that Extraversion has a significant positive effect (β=0.186, p<0.05) on long-term decision-making. On the contrary, the consciousness trait has a significant negative effect (β=-0.335, p<0.05) on short-term investment decision-making. Furthermore, the Openness trait demonstrates a significant effect on both short-term and long-term investment decision-making (β=0.357, p<0.05; β=0.007, p<0.05). However, the findings reveal no significant intervening effect of investor sentiment between personality traits and investment decision-making. Thus, the study strongly exerted the impact of investors’ personality traits on their investment decision-making due to the high influence of personal characteristics over sentiment effects.

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    • Figure 1. Structural model
    • Table 1. Respondents’ measurement profile
    • Table 2. Measurement models
    • Table 3. Fornell-Lacker criterion
    • Table 4. Heterotrait-monotrait ratio (HTMT) test
    • Table 5. Structural path analysis
    • Table 6. Mediation analysis
    • Conceptualization
      Aditi N. Kamath, Abhilash
    • Data curation
      Aditi N. Kamath, Abhilash
    • Formal Analysis
      Aditi N. Kamath, Abhilash, Subrahmanya Kumar N.
    • Investigation
      Aditi N. Kamath, Sandeep S. Shenoy, Abhilash, Subrahmanya Kumar N.
    • Methodology
      Aditi N. Kamath, Abhilash
    • Resources
      Aditi N. Kamath, Sandeep S. Shenoy, Abhilash, Subrahmanya Kumar N.
    • Software
      Aditi N. Kamath, Abhilash, Subrahmanya Kumar N.
    • Validation
      Aditi N. Kamath, Sandeep S. Shenoy, Abhilash
    • Visualization
      Aditi N. Kamath, Sandeep S. Shenoy, Abhilash, Subrahmanya Kumar N.
    • Writing – original draft
      Aditi N. Kamath, Abhilash
    • Writing – review & editing
      Aditi N. Kamath, Sandeep S. Shenoy, Abhilash, Subrahmanya Kumar N.
    • Funding acquisition
      Sandeep S. Shenoy, Subrahmanya Kumar N.
    • Project administration
      Sandeep S. Shenoy
    • Supervision
      Sandeep S. Shenoy