Value At Risk Analysis Using Historical Method and Monte Carlo Simulation in Banking and Mining Sector Companies - Darman Saputra; Zukhri , Nizwan; Altin, Darus; Agung Nugroho, Ari; Daddy Setiawan, Ryand; Fitari, Tiara; Thohari, Mustofa (International Journal of Applied Management and Business, 2023)
Purpose – Investments in the capital market must be able to understand the risks that exist, because investments that will be faced in the future contain uncertainty. The growth of trading activity and the increasingly uncertain market makes market participants feel the need to develop more accurate and reliable risk measurement techniques. One of the risk measurement techniques is Value at Risk (VaR). Methodology/approach – Value at Risk (VaR) is a method of calculating market risk to determine the maximum risk of loss that can occur in a portfolio, both single and multi-instrument, especially the level of confidence, during a certain holding period, and under normal conditions. market conditions. This study uses secondary data in the form of stocks listed on the Indonesia Stock Exchange, the samples obtained are 2 companies. Processing data in this study using Microsoft Excel program for measuring Value at Risk in portfolios using Monte Carlo simulation. Findings – The results of the study show that a greater return will provide a greater level of risk, judging from the return and VaR values of each portfolio. Where portfolio one has a greater return than the second portfolio, and portfolio one also has a greater risk level than the second portfolio. Investment in the capital market requires a good risk calculation in buying or selling shares, so the purpose of this study is to help investors take steps or policies that are in accordance with the company's conditions.. Novelty/value – The results in this study illustrate that the purchase of BBRI shares with the banking sub-sector and ANTM's shares in the Mining Company sub-sector has its respective risks and benefits. Therefore, the VaR Monte Carlo simulation method can describe each stock.