ESTIMASI RISIKO PASAR DENGAN LVaR DAN EXPECTED SHORTFALL MENGGUNAKAN SIMULASI MONTE CARLO

I. Pratama, K. Dharmawan, Kartika Sari
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引用次数: 1

Abstract

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.
预计短缺实现蒙特卡罗模拟
风险价值(VaR)是一种统计技术,用于管理和计算一定时期和一定置信度的财务风险水平。VaR可以根据流动性风险进行调整,称为流动性调整风险值(LVaR)。另一种可选的计算方法是预期亏损(ES),这是由于流动性而可能发生的超出置信范围的损失。本研究的目的是利用蒙特卡洛模拟,用LVaR和ES对纳入LQ45指数的股票投资组合进行市场风险估计。此外,利用Kupiec检验进行了回测。本研究使用的数据是LQ45指数中三年内销量最大的两只股票,即ANTM和bbi股票。结果发现,在初始基金Rp. 10,000,000.00中,ANTM和bbi的股票投资组合在95%置信水平下,获得ES为Rp.496.47万/天,LVaR值为Rp. 499.17.4万/天。得到的ES模型精度较低,而LVaR模型精度较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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