IDEAS home Printed from https://ideas.repec.org/a/vls/finstu/v27y2023i3p25-39.html
   My bibliography  Save this article

Constant Correlation Model For Optimal Portfolio Formation And Expected Shortfall Risk Measurement: Empirical Evidence From Indonesian Stock Market

Author

Listed:
  • DEVITA, Febrina

    (Department of Statistics, Diponegoro University, Semarang, Indonesia.)

  • WILANDARI, Yuciana

    (Department of Statistics, Diponegoro University, Semarang, Indonesia.)

  • MARUDDANI, Di Asih I

    (Department of Statistics, Diponegoro University, Semarang, Indonesia.)

Abstract

Stock investment is one option of investment choice with risks. Investors can reduce their risk by combining several stocks and then forming a portfolio. One method to form an optimal portfolio is by using the Constant Correlation Model (CCM) method. The CCM method focuses on the correlation between stocks and the Excess Return to Standard Deviation (ERS) value. Calculation of risk in the portfolio can use the Expected Shortfall (ES) method. ES is defined as a loss with a value exceeding VaR. ES is considered appropriate for measuring portfolio risk compared to VaR because it fulfils the subadditivity property. The subadditivity shows the advantage of portfolio formation. The object of this research is to form an optimal portfolio using the CCM method and ES risk measure on the Indonesian Stock Market Indices, that is IDX30 index. The daily return of IDX30 Index is analysed for the period January 2021 - December 2022. The formed portfolio contains 3 stocks, namely BMRI with a weight of 46.263%, KLBF of 39.255%, and MDKA of 14.482%. The Expected Shortfall value at a trust level of 95% is 5.408% for the next week.

Suggested Citation

  • DEVITA, Febrina & WILANDARI, Yuciana & MARUDDANI, Di Asih I, 2023. "Constant Correlation Model For Optimal Portfolio Formation And Expected Shortfall Risk Measurement: Empirical Evidence From Indonesian Stock Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 27(3), pages 25-39, September.
    • Handle: RePEc:vls:finstu:v:27:y:2023:i:3:p:25-39
    as

    Download full text from publisher

    File URL: http://www.icfm.ro/RePEc/vls/vls_pdf/vol27i3p25-39.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    cut off rate; excess return to standard deviation; IDX30; Monte-Carlo simulation; optimum weight;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vls:finstu:v:27:y:2023:i:3:p:25-39. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Daniel Mateescu (email available below). General contact details of provider: https://edirc.repec.org/data/cfiarro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.