ESTIMASI VALUE AT RISK PORTOFOLIO MENGGUNAKAN METODE QUASI MONTE CARLO DENGAN PEMBANGKIT BILANGAN ACAK HALTON

Putu Savitri Devi, K. Dharmawan, L. Harini
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Abstract

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.
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风险投资组合估计价值使用蒙特卡洛速记法与霍尔顿随机数字发生器
评估风险价值(VaR)是投资的一个重要方面。VaR是衡量风险的标准方法,定义为一定时期内在一定置信度下的最大损失。本研究的目的是估计一个投资组合的风险表示为VaR,其中波动性是由蒙特卡洛和拟蒙特卡洛方法模拟。蒙特卡罗方法涉及生成随机数,而拟蒙特卡罗方法使用哈尔顿的拟随机序列。本研究采用二级数据,即每日股价收盘数据。根据计算,拟蒙特卡罗投资组合的VaR产生的最大损失大于蒙特卡罗投资组合。这是由于每种方法使用不同的随机数生成器执行的随机化以及执行的模拟次数。结果表明,拟蒙特卡罗方法比蒙特卡罗方法更适合于电信行业股票投资组合损失风险的估计。
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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