Investment Risk Analysis Using Value at Risk With Monte Carlo Simulation: Investment risk analysis

Nur Cellia Clara; Fibri Rakhmawati

doi:10.32938/jpm.v7i1.9692

Authors

Nur Cellia Clara Universitas Islam Negeri Sumatera Utara
Fibri Rakhmawati Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.32938/jpm.v7i1.9692

Keywords:

Investment Risk, Value at Risk (VaR), Monte Carlo Simulation, Composite Stock Price Index (IHSG), Gold

Abstract

This study aims to evaluate and compare the investment risk levels of three primary financial instruments in Indonesia: the Indonesia Composite Index (IHSG), Bank Central Asia (BCA) with code BBCA stock, and gold. Using the Value at Risk (VaR) approach based on Monte Carlo simulation, the research integrates these assets into a unified risk assessment model, providing a more comprehensive perspective than prior studies that typically examine individual assets or use historical estimation methods. Monthly historical price data from April 2024 to March 2025 were obtained from the Indonesia Stock Exchange and the Central Bureau of Statistics. The analysis involved calculating asset returns, means, and standard deviations, followed by 10,000 Monte Carlo simulation iterations to generate potential future price paths and estimate losses under market uncertainty. The results, at a 95% confidence level, show that IHSG carries the highest investment risk, with a VaR of IDR 9,331.16, followed closely by BBCA stock at IDR 9,210.31. Gold exhibited the lowest risk level, with a VaR of IDR 6,896.86, confirming its role as a more stable and less volatile investment compared to equity-based assets. These findings highlight the reliability of gold as a defensive asset during turbulent market conditions. The application of Monte Carlo simulation effectively captures the non-normal distribution of returns and accommodates complex market behaviors, making it a robust tool for financial risk modeling. This research offers meaningful insights for investors, analysts, and academics in optimizing portfolio strategies and improving risk management decisions.

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Investment Risk Analysis Using Value at Risk With Monte Carlo Simulation