ESTIMASI RISIKO PASAR DENGAN LVaR DAN EXPECTED SHORTFALL MENGGUNAKAN SIMULASI MONTE CARLO - PRATAMA, I PUTU YUDHI; DHARMAWAN, KOMANG; SARI, KARTIKA (E-Jurnal Matematika; Vol 11 No 2 (2022), 2022)
Value at Risk (VaR) is a statistical technique used to manage and calculate the level of financial risk within a certain period of time and a certain level of confidence. VaR can be adjusted to liquidity risk which is called Liquidity adjusted Value at Risk (LVaR). Another alternative calculation is the Expected Shortfall (ES) which is a loss beyond the confidence limit that can occur due to liquidity. This study aims to estimate market risk with LVaR and ES on a stock portfolio incorporated in the LQ45 index using a Monte Carlo simulation. Furthermore, back-testing is carried out using the Kupiec test. The data used in this study are two stocks that are included in the LQ45 index which have the largest sales volume in a period of three years, namely ANTM and BBRI shares. As a result, it was found that the stock portfolio of ANTM and BBRI in the initial fund of Rp. 10,000,000.00 with a 95% confidence level, obtained ES of Rp.496 . 470 , 00 per day and an LVaR value of Rp 499.174 , 00 per day. The ES model obtained is less accurate while the LVaR model is accurate.