Investors in Malaysia often choose stocks as a way to grow their wealth. To help investors understand the risks involved, this study used Value at Risk (VaR) and Conditional Value at Risk (CVaR) models to measure the monthly market risk of stock portfolios. These models predict the maximum potential loss and average predicted loss of a portfolio at a 95% confidence level. By comparing the accuracy of VaR and CVaR, the study found that VaR is better at estimating risk, with a lower Mean Absolute Percentage Error (MAPE) of 6.9% compared to CVaR's 8.64%. This means that using VaR and CVaR models can help investors make more informed decisions about their stock investments.