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The Way to Use Information on Long-term Returns: Focus on U.S. Equity Funds

장기 수익률 정보의 활용 방안: 미국 주식형 펀드를 대상으로

  • Ha, Yeon-Jeong (Department of International Trade, Gyeongsang National University) ;
  • Oh, Hae-June (Department of Information & Statistics, Gyeongsang National University)
  • 하연정 (경상국립대학교 국제통상학부) ;
  • 오해준 (경상국립대학교 정보통계학과)
  • Received : 2022.02.28
  • Accepted : 2022.03.25
  • Published : 2022.03.30

Abstract

Purpose - The purpose of this study is to show the need to use the past long-term returns for investment decisions in U.S. equity funds and to suggest an investment strategy using long-term returns. Design/methodology/approach - This study solves the problem of high return volatility in long-term returns and proposes new investment portfolios based on the behavior of fund investors according to past returns. For the investment portfolio of this study, 60 months are divided into several periods and the average of the performance ranks for each period is used. Findings - First, funds with high average returns over multiple periods have lower future outflows and higher future returns than funds with high 60-month cumulative returns. Second, funds with low average returns over multiple periods have lower future inflows and lower future returns than funds with low 60-month cumulative returns. The findings mean that when making decisions based on past long-term returns, it is a smarter investment choice to buy funds with high average returns over multiple periods and sell funds with low average returns over multiple periods. Research implications or Originality - This study shows that it is necessary to use long-term returns in fund investment by analyzing the characteristics of the portfolio based on past returns. In addition, the study is meaningful in that it suggests a way to use long-term returns more efficiently based on the behavior of fund investors and shows that such investments lead to higher returns in the future.

Keywords

Acknowledgement

이 논문은 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 논문임 (NRF-2020R1G1A1A01014362).

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