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All Journal Mikailalsys Journal of Mathematics and Statistics
Avrilia, Khairunnisa
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Engineering Mathematics Mechanical Engineering

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Comparison of Value at Risk (VaR) in Risk Analysis: Historical, Variance Covariance and Monte Carlo Methods Fauziyah, Meirinda; Dani, Andrea Tri Rian; Koirudin, Hadi; Budi, Ennesya Estya; Avrilia, Khairunnisa; Watika, Noor Hikmah
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v2i3.3778

Abstract

Value at Risk (VaR) is a method used to measure financial risk in a company. VaR calculations are often used to calculate the level of loss from shares in a company, such as bank shares. The aim of this research is to determine the level of losses in Bank Central Asia shares using the historical method, the Variance-covariance method, and the Monte Carlo method. the results showed that with an initial investment of $50 and using the Historical method at a significant level of 95%, the VaR value was obtained at $16.42 or IDR. 267.301 and at the 90% significant level, the VaR value was obtained at $12.41 or IDR. 202.022. Based on the Variance-covariance method with an initial investment of 50$ at the 95% significant level, the VaR value is obtained at $16.42 or IDR. 267,301 and at the 90% significant level, the VaR value is obtained at $12.79 or IDR. 208.208. Meanwhile, based on the Monte Carlo method with an initial investment of $50, at a significant level of 95%, the VaR value is obtained at $16.46 or IDR. 267,952 and at the 90% significance level, the VaR value is obtained at $12.84 or IDR. 209.022. Based on the three methods used, it was concluded that the Monte Carlo method gave greater results compared to the other two methods.
Co-Authors Budi, Ennesya Estya Dani, Andrea Tri Rian Fauziyah, Meirinda Koirudin, Hadi Watika, Noor Hikmah