{"title":"Evaluating Wave Random Path Using Multilevel Monte Carlo","authors":"Behrouz Fathi-Vajargah , Ayoob Salimipour","doi":"10.1016/j.enavi.2017.06.001","DOIUrl":null,"url":null,"abstract":"<div><p>Wind waves are important due to their high energy and impact on marine activities. This phenomenon is affects directly or indirectly the construction of coastal infrastructure, shipping and recreational activities. Due to the issues presented, marine parameters are very important. In this study, we try to pay attention to wave as one of the most important marine parameters. As the movements of waves have high uncertainty, financial models can be used to simulate the wave's paths. We use the Monte Carlo method for this purpose. The Monte Carlo simulation is a flexible and simple tool that is widely used in the evaluation of random paths. To compute a random path, we require an integral discretization. In this paper, we study the valuation of European options using Monte Carlo simulation and then compare this result with multi-level Monte Carlo approach and other antithetic variables. Then, we use the multi-level Monte Carlo approach proposed by (M. B. <span>Giles, 2008</span>) for pricing under the two-factor stochastic volatility model. We show that the multi-level Monte Carlo method reduces the computational complexity and also cost of the two-factor stochastic volatility model when compared with the standard Monte Carlo method. Also, we compare the multi-level Monte Carlo method and standard Monte Carlo method using an Euler discretization scheme and then, analyze the numerical results.</p></div>","PeriodicalId":100696,"journal":{"name":"International Journal of e-Navigation and Maritime Economy","volume":"7 ","pages":"Pages 1-10"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.enavi.2017.06.001","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of e-Navigation and Maritime Economy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405535217300165","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Wind waves are important due to their high energy and impact on marine activities. This phenomenon is affects directly or indirectly the construction of coastal infrastructure, shipping and recreational activities. Due to the issues presented, marine parameters are very important. In this study, we try to pay attention to wave as one of the most important marine parameters. As the movements of waves have high uncertainty, financial models can be used to simulate the wave's paths. We use the Monte Carlo method for this purpose. The Monte Carlo simulation is a flexible and simple tool that is widely used in the evaluation of random paths. To compute a random path, we require an integral discretization. In this paper, we study the valuation of European options using Monte Carlo simulation and then compare this result with multi-level Monte Carlo approach and other antithetic variables. Then, we use the multi-level Monte Carlo approach proposed by (M. B. Giles, 2008) for pricing under the two-factor stochastic volatility model. We show that the multi-level Monte Carlo method reduces the computational complexity and also cost of the two-factor stochastic volatility model when compared with the standard Monte Carlo method. Also, we compare the multi-level Monte Carlo method and standard Monte Carlo method using an Euler discretization scheme and then, analyze the numerical results.
由于其高能量和对海洋活动的影响,风波很重要。这一现象直接或间接地影响到沿海基础设施的建设、航运和娱乐活动。由于所提出的问题,海洋参数是非常重要的。在这项研究中,我们试图关注波浪作为最重要的海洋参数之一。由于波浪的运动具有很高的不确定性,因此可以使用金融模型来模拟波浪的路径。为此,我们使用蒙特卡罗方法。蒙特卡罗模拟是一种灵活而简单的工具,广泛应用于随机路径的评估。为了计算随机路径,我们需要一个积分离散化。本文利用蒙特卡罗模拟方法对欧式期权的估值进行了研究,并与多级蒙特卡罗方法和其他反变量进行了比较。然后,我们使用(M. B. Giles, 2008)提出的多层蒙特卡罗方法在双因素随机波动模型下定价。结果表明,与标准蒙特卡罗方法相比,多级蒙特卡罗方法降低了双因素随机波动模型的计算复杂度和成本。采用欧拉离散化方法,对多级蒙特卡罗方法和标准蒙特卡罗方法进行了比较,并对数值结果进行了分析。