산업경영시스템학회지 (Journal of Korean Society of Industrial and Systems Engineering)

  • 제43권4호
  • /
  • Pages.229-235
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  • 2020
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  • 2005-0461(pISSN)
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  • 2287-7975(eISSN)
한국산업경영시스템학회 (Society of Korea Industrial and System Engineering)
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애널리스트 목표가를 활용한 최적 투자의사결정 방안에 관한 연구

Optimization of Investment Decision Making by Using Analysts' Target Prices

  • Cho, Su-Ji (School of Business Administration, Dankook University) ;
  • Kim, Heung-Kyu (School of Business Administration, Dankook University) ;
  • Lee, Ki-Kwang (School of Business Administration, Dankook University)
  • 투고 : 2020.10.29
  • 심사 : 2020.11.25
  • 발행 : 2020.12.31
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초록

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts' target price and to suggest the strategy that could maximize individual's return rate. Most previous literature revealed that the optimistic bias exists in the analysts' target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named 'alpha(α)' which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts' proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts' target price practically.

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과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2019S1A5A2A03038389).

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