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Do Individual Investors Learn from Their Trading Experience?

Author

Listed:
  • Gina Nicolosi
  • Liang Peng
  • Ning Zhu

Abstract

This paper investigates whether individual investors adjust their stock trading according to their stock selection abilities, which can be inferred from their trading history. Fixed-effect panel regressions provide strong evidence that the ability to forecast future stock returns significantly affects investors' trading activity: investors purchase more actively if they are more likely to have stock selection ability. Furthermore, trading experience - measured by the number of purchases, the number of different stocks purchased, and the variance of purchase dollar amounts - significantly helps improve investors' portfolio performance. In addition, we find that learning behavior varies across investors, which corroborates the heterogeneity of individual investors.

Suggested Citation

  • Gina Nicolosi & Liang Peng & Ning Zhu, 2003. "Do Individual Investors Learn from Their Trading Experience?," Yale School of Management Working Papers ysm439, Yale School of Management, revised 01 Sep 2009.
  • Handle: RePEc:ysm:wpaper:ysm439
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    File URL: https://repec.som.yale.edu/icfpub/publications/2428.pdf
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    References listed on IDEAS

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    4. Andreas Oehler & Matthias Horn & Stefan Wendt, 2022. "Investor Characteristics and their Impact on the Decision to use a Robo-advisor," Journal of Financial Services Research, Springer;Western Finance Association, vol. 62(1), pages 91-125, October.
    5. Congmin Peng & Po-Wen She & Ming-Kun Lin, 2022. "Financial Literacy and Portfolio Diversity in China," Journal of Family and Economic Issues, Springer, vol. 43(3), pages 452-465, September.
    6. Neenu Chalissery & Mosab I. Tabash & T. Mohamed Nishad & Ibtehal M. Aburezeq & Linda Nalini Daniel, 2023. "Does the Investor’s Trading Experience Reduce Susceptibility to Heuristic-Driven Biases? The Moderating Role of Personality Traits," JRFM, MDPI, vol. 16(7), pages 1-21, July.
    7. Adrià Pons & Eduard Cristobal-Fransi & Carla Vintrò & Josep Rius & Oriol Querol & Jordi Vilaplana, 2023. "An Application of the IFM Method for the Risk Assessment of Financial Instruments," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 295-315, January.
    8. Xing Gao & Daniel Ladley, 2022. "Noise trading and market stability," The European Journal of Finance, Taylor & Francis Journals, vol. 28(13-15), pages 1283-1301, October.
    9. Pikulina, E.S. & Renneboog, L.D.R. & ter Horst, J.R. & Tobler, P.N., 2014. "Bonus schemes and trading activity," Other publications TiSEM 834aee67-a175-4bc6-91e6-6, Tilburg University, School of Economics and Management.
    10. Xu, Rong & Liu, Yaodong & Hu, Nan & Guo, Jie (Michael), 2022. "What drives individual investors in the bear market?," The British Accounting Review, Elsevier, vol. 54(6).
    11. Itzhak Ben-David & Justin Birru & Viktor Prokopenya, 2018. "Uninformative Feedback and Risk Taking: Evidence from Retail Forex Trading [Two methods of reducing overconfidence]," Review of Finance, European Finance Association, vol. 22(6), pages 2009-2036.
    12. Brent W. Ambrose & Lily Shen, 2023. "Past Experiences and Investment Decisions: Evidence from Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 66(2), pages 300-326, February.
    13. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
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