Mikailalsys Journal of Mathematics and Statistics
Vol 2 No 3 (2024): Mikailalsys Journal of Mathematics and Statistics

Comparison of Value at Risk (VaR) in Risk Analysis: Historical, Variance Covariance and Monte Carlo Methods

Fauziyah, Meirinda (Unknown)
Dani, Andrea Tri Rian (Unknown)
Koirudin, Hadi (Unknown)
Budi, Ennesya Estya (Unknown)
Avrilia, Khairunnisa (Unknown)
Watika, Noor Hikmah (Unknown)



Article Info

Publish Date
04 Sep 2024

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.

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Journal Info

Abbrev

MJMS

Publisher

Subject

Engineering Mathematics Mechanical Engineering

Description

The journal contains scientific articles covering topics such as mathematical theory, statistical methods, the application of mathematics in various disciplines, and statistical data analysis. The primary objective of this journal is to promote a better understanding of mathematical and statistical ...