The impact of COVID-19 on formation and evaluation of portfolio performance: A case of Indonesia

  • Received June 5, 2021;
    Accepted August 2, 2021;
    Published August 6, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.18(3).2021.06
  • Article Info
    Volume 18 2021, Issue #3, pp. 63-73
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This work is licensed under a Creative Commons Attribution 4.0 International License

This paper examines how to build a portfolio and assess the impact of the COVID-19 on portfolio performance using the Sharpe single index model. The research sample consists of ten high market capitalization stocks representing five price fractions of the population listed stocks on the Indonesia Stock Exchange during the COVID-19 outbreak from March 1 to May 31, 2020. The results show that there are four stocks that are included in the portfolio formation, namely CASA with a proportion of 50%, BNLI with a proportion of 26 %, UNVR with a proportion of 15%, and HMSP with a proportion of 9%. Based on portfolio performance testing using the Sharpe single index model, it is known that the portfolio during the COVID-19 has a negative Sharpe ratio, meaning that portfolio performance is underperforming. The findings provide evidence that COVID-19 has had a negative impact on the stock market so that many investors have suffered losses on their portfolios. The implications of findings are that investors must evaluate portfolio performance and restructure the formation of new portfolios by considering the COVID-19 pandemic outbreak as a systematic risk factor that can determine the expected returns.

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    • Table 1. Result of calculation of market return, expected market return, return of variance of IDX composite and BI rate
    • Table 2. The t-test: two-sample with equal variances
    • Table 3. The result of calculation of return, average return or expected return E(Ri), return of variance, standard deviation, alpha (intercept), beta (slope), of the selected samples, unsystematic risk, Ai, Bi, Ci, ERBi
    • Table 4. Values of Ai, Bi, and Ci
    • Table 5. Determination of the candidate of the optimum portfolio, ERB > C*
    • Table 6. Zi and Wi of ERBi and C* values
    • Table 7. Portfolio risk and portfolio performance
    • Conceptualization
      Immas Nurhayati
    • Methodology
      Immas Nurhayati, Renea Shinta Aminda
    • Software
      Immas Nurhayati, Renea Shinta Aminda
    • Validation
      Immas Nurhayati
    • Writing – original draft
      Immas Nurhayati, Titing Suharti
    • Formal Analysis
      Endri Endri
    • Investigation
      Endri Endri
    • Supervision
      Endri Endri, Leny Muniroh
    • Writing – review & editing
      Endri Endri
    • Funding acquisition
      Titing Suharti, Leny Muniroh
    • Project administration
      Titing Suharti, Leny Muniroh
    • Visualization
      Titing Suharti
    • Resources
      Leny Muniroh