Monte Carlo & Quasi-Monte Carlo approach in option pricing

M. A. Maasar, N. Nordin, M. Anthonyrajah, W. Zainodin, A. M. Yamin
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引用次数: 5

Abstract

Monte Carlo simulation has been proven to be a valuable tool for estimating security prices. This study is about comparing Monte Carlo and Quasi-Monte Carlo approach in pricing European call option. Both approaches has an attractive properties of numerical valuation of derivatives, with Quasi-Monte Carlo simulation using low discrepancy sequences for valuing derivatives versus the traditional Monte Carlo method using pseudo-random sequences. The performance of these methods is evaluated based on pricing European call options and by John Birge's paper in 1995. Option price using Black Scholes method generated by MATLAB will be the benchmark to testify results from both Monte Carlo and Quasi-Monte Carlo approach. At the end of the study, it is proven that Quasi-Monte Carlo approach does give better result than Monte Carlo approach in pricing a call option. It is discovered that Quasi-Monte Carlo using hybrid Halton sequence gave better results compared to Quasi-Monte Carlo because of the random sequence it generated.
期权定价中的蒙特卡罗与拟蒙特卡罗方法
蒙特卡罗模拟已被证明是估计证券价格的一种有价值的工具。本研究比较了蒙特卡罗法和拟蒙特卡罗法在欧式看涨期权定价中的应用。这两种方法在导数数值估值方面都具有吸引人的特性,与使用伪随机序列的传统蒙特卡罗方法相比,使用低差异序列的拟蒙特卡罗模拟对导数进行估值。基于欧洲看涨期权定价和John Birge(1995)的论文对这些方法的性能进行了评估。使用MATLAB生成的Black Scholes方法的期权价格将作为基准来验证蒙特卡罗方法和拟蒙特卡罗方法的结果。在研究的最后,证明了拟蒙特卡罗方法在看涨期权定价方面确实比蒙特卡罗方法具有更好的结果。研究发现,利用混合霍尔顿序列的拟蒙特卡罗算法由于产生的序列是随机的,因此比拟蒙特卡罗算法得到了更好的结果。
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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