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Abstract

One way to achieve profits in a company is through investment activities. However, everything has risks. Investing can also be risky. Therefore, the relationship between risk and investment is important because it will influence the determination of investment selection. The problem faced by investors is choosing an efficient portfolio, or a portfolio that provides the smallest risk. This risk can be done by measuring risk, one of which is using the Value at Risk (VaR) measure. Measurement using Value at Risk has several methods that are quite popular, namely the Historical Method, Variance-Covariance, and Monte Carlo. In this research, the Historical and Monte Carlo methods will be used to measure Value at Risk in stock portfolios. The research results show that Monte Carlo simulations provide greater results at 95% and 90% confidence levels. This is because the Monte Carlo simulation method carries out repeated random generation by including data so that the data samples become larger and make the calculations bigger.

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