Santosa, Yoga
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Perhitungan Value at Risk (VaR) pada Saham Sub Sektor Pertanian dengan Metode Simulasi Historis dan Monte Carlo Zebua, Damara Dinda Nirmalasari; Pancasila, Muhammad Rizal; Santosa, Yoga
Mimbar Agribisnis : Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Vol 11, No 2 (2025): Juli 2025
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ma.v11i2.18265

Abstract

Making investment decisions requires the right approach in measuring potential losses, one of which is investing in agricultural sub-sector shares. Potential losses can be seen from the Value at Risk (VaR) value. The aims of this research are 1) to calculate the VaR value of single assets and portfolios in the agricultural sub-sector using two methods; 2) to determine which method is more accurate and reliable in estimating losses in agricultural sub-sector shares; and 3) to provide the best investment alternative for investors to invest in one or both shares. The research uses time series data from two agricultural sub-sector shares, namely PT. Sampoerna Agro Tbk (SGRO) and PT. Perusahaan Perkebunan London Sumatra Indonesia Tbk (LSIP) for the period November 30, 2020-November 30, 2024 totaling 970 data. Data were analyzed using Historical Simulation and Monte Carlo methods with the help of Microsoft Excel (Ms. Excel) software. The research results show 1) with a confidence level of 95%, the estimated loss value of SGRO, LSIP and portfolio shares (50:50) using the Historical Simulation method is Rp9,742,547.43, Rp14,810,924.37 and Rp10,336,139.64 respectively, while using the Monte Carlo method is Rp12,493,847.11, Rp15,996,384.77 and Rp11,257,991.86; 2) based on the results of the VaR analysis, a more accurate and reliable method for estimating losses in agricultural sub-sector shares is the Monte Carlo method because it provides a greater estimate of the value of losses through repeated iterations; and 3) based on VaR calculations, it is recommended for investors to invest in both shares in a 50:50 proportion because it can reduce the estimated value of losses received compared to investing in just one share.