Syarifah Inayati, Sahid, Rosita Kusumawati
In a stock investment, the greater the desired profits, the greater risks will be implied. The big changes in the stock market prices encourage us to measure the financial risks. The value at risk (VaR), a parametric method under the assumption of normally distributed data, is one of the most popular and accurate risk measurement methods. If the stock data does not match a normal distribution, then the normal mixture distribution can be implemented. In this study, we calculate the risk data of the shares of three companies registered in the Jakarta Islamic Index (JII) using the VaR methods through the normal mixture approach. Those companies are PT. Astra International Tbk (ASII), PT. Telekomunikasi Indonesia Tbk (TLKM) and PT. Unilever Indonesia Tbk (UNVR). The data were taken in 2019. The parameter estimation was done using the Bayesian Markov Chain Monte Carlo (MCMC) approach. Based on the obtained VaR values, the highest risk is 0.124272 for TLKM, then 0.02533735 for ASII, and the lowest one is 0.02298288 for UNVR. © 2022 Author(s).
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia; Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
