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All Journal JISTech (Journal of Islamic Science and Technology)
Tanjung, Aida Febriana
Universitas Islam Negeri Sumatera Utara Medan
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Materials Science & Nanotechnology Other

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Investment Risk Analysis of Gold, the Indonesia Composite Index (IHSG), and BBCA Stock in Indonesia using the Value At Risk (Var) Method With A Variance–Covariance Approach Tanjung, Aida Febriana; Hasibuan, Hani Maulida; Kurahman, Panca Taufik; Nasution, Fakhrur Rozi; Lubis, Riri Syafitri
JISTech (Journal of Islamic Science and Technology) Vol 11, No 1 (2026)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v11i1.28790

Abstract

Investments in various financial instruments such as gold, the Indonesia Composite Index (IHSG), and individual stocks carry different levels of risk due to market price fluctuations. These differences require investors to understand potential risks in order to manage their portfolios optimally. Therefore, a quantitative risk measurement method is needed. Value at Risk (VaR) is a method used to estimate the maximum potential loss at a given confidence level and time horizon. This study aims to analyze and measure investment risk in gold, IHSG, and BBCA stock in Indonesia using the Value at Risk (VaR) method with a variance–covariance approach. The data consist of monthly closing prices from April 2024 to March 2025, implying a 1-month VaR horizon with confidence levels of 90%, 95%, and 99%. The results show that the VaR value at the 95% confidence level (1-month horizon) is (4,033.25) for gold, (8,064.47) for IHSG, and (7,931.17) for BBCA stock. At a higher confidence level of 99%, the VaR increases to (5,704.31) for gold, (11,405.74) for IHSG, and (11,217.20) for BBCA stock. These findings indicate that IHSG and BBCA stock have higher potential maximum losses compared to gold, consistent with their higher volatility levels. These results suggest that the variance–covariance VaR method provides measurable quantitative risk estimates across different confidence levels and time horizons, making it useful for investment decision-making and structured portfolio risk management.
Co-Authors Hasibuan, Hani Maulida Kurahman, Panca Taufik Nasution, Fakhrur Rozi Riri Syafitri Lubis