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Overconfidence and Investment Loss Tolerance: A Large-Scale Survey Analysis of Japanese Investors

Author

Listed:
  • Honoka Nabeshima

    (School of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashihiroshima 739-8525, Japan)

  • Mostafa Saidur Rahim Khan

    (School of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashihiroshima 739-8525, Japan)

  • Yoshihiko Kadoya

    (School of Economics, Hiroshima University, 1-2-1 Kagamiyama, Higashihiroshima 739-8525, Japan)

Abstract

Accepting a certain degree of investment loss risk is essential for long-term portfolio management. However, overconfidence bias within financial literacy can prompt excessively risky behavior and amplify susceptibility to other cognitive biases. These tendencies can undermine investment loss tolerance beyond the baseline level shaped by sociodemographic, economic, psychological, and cultural factors. This study empirically examines the association between overconfidence and investment loss tolerance, which is measured by the point at which respondents indicate they would sell their investments in a hypothetical loss scenario. Using a large-scale dataset of 161,765 active investors from one of Japan’s largest online securities firms, we conduct ordered probit and ordered logit regression analyses, controlling for a range of sociodemographic, economic, and psychological variables. Our findings reveal that overconfidence is statistically significantly and negatively associated with investment loss tolerance, indicating that overconfident investors are more prone to prematurely liquidating assets during market downturns. This behavior reflects an impulse to avoid even modest losses. The findings suggest several possible practical strategies to mitigate the detrimental effects of overconfidence on long-term investment behavior.

Suggested Citation

  • Honoka Nabeshima & Mostafa Saidur Rahim Khan & Yoshihiko Kadoya, 2025. "Overconfidence and Investment Loss Tolerance: A Large-Scale Survey Analysis of Japanese Investors," Risks, MDPI, vol. 13(8), pages 1-14, July.
    • Handle: RePEc:gam:jrisks:v:13:y:2025:i:8:p:142-:d:1708176
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    References listed on IDEAS

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