ESTIMASI VALUE AT RISK PORTOFOLIO MENGGUNAKAN METODE QUASI MONTE CARLO DENGAN PEMBANGKIT BILANGAN ACAK HALTON - DEVI, PUTU SAVITRI; DHARMAWAN, KOMANG; HARINI, LUH PUTU IDA (E-Jurnal Matematika; Vol 11 No 2 (2022), 2022)
Estimating the value at risk (VaR) is an important aspect of investment. VaR is a standard method of measuring risk defined as the maximum loss over a certain period of time at a certain level of confidence . The purpose of this study is to estimate the risk of a portfolio represented as a VaR where the volatilities were simulated by th the Monte Carlo and Quasi Monte Carlo methods. The Monte Carlo method involves generating random numbers and the Quasi Monte Carlo method uses Halton's quasi-random sequences. This study uses secondary data, namely daily stock price closing data. Based on the calculation, the VaR of the Quasi Monte Carlo Portfolio produces a maximum loss greater than that of the Monte Carlo Portfolio. This is due to randomization performed with different random number generators for each method and the number of simulations performed. It can be concluded that the Quasi Monte Carlo method is a better method than the Monte Carlo method in estimating the risk of portfolio losses in stocks in the telecommunications sector.