Open AccessRisk analysis of five stocks indexed by LQ45 using credible value at risk and credible expected tail loss
Author(s) -
Evy Sulistianingsih,
Dedi Rosadi,
Abdurakhman Abdurakhman
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1918/4/042023
Subject(s) - portfolio , value at risk , stock (firearms) , actuarial science , credibility , asset (computer security) , asset allocation , economics , econometrics , business , financial economics , risk management , finance , computer science , geography , computer security , archaeology , political science , law
Value at Risk (VaR) and Expected Tail Loss (ETL) are two risk measures that are used frequently to measure the investment risk. Even though VaR can estimate maximum loss when the investor holds a single asset in a particular period and interval confidence, the investor frequently develops a portfolio of assets. This condition can create shared risk among assets in the portfolio so that there will be a chance of an asset for getting loss caused by the other assets developing the portfolio. On the other hand, there is a fact that VaR cannot provide loss information at the tail loss part so that we also need ETL that can overcome this problem. Because of that reason, this paper uses Credible Value at Risk (CredVaR) and Credible Expected Tail Loss (CredETL), which are formulated based on the Buhlman credibility concept. Both methods can estimate an investment risk that can overcome the shortcoming of VaR and ETL that do not consider the risk among assets inside the portfolio. The application of both methods was utilized to evaluate the individual risk of each asset in a portfolio comprised of five stocks in the LQ-45 Index (period of February 2019 until July 2019). The data divided into ten periods of risk analysis comprises of ten-year daily data of each stock from June 2009 to May 2019. According to the result of the analysis, it can be concluded that both methods are powerful in measuring the risk.