中国科学技术大学学报 ›› 2017, Vol. 47 ›› Issue (3): 262-266.DOI: 10.3969/j.issn.0253-2778.2017.3.009

• 研究论文:管理科学与工程 • 上一篇    下一篇

Lévy过程下金融期权风险对冲参数的模拟仿真估计

刘刚,崔振嵛,刘彦初,谢金贵   

  1. 1.中国科学技术大学管理学院,安徽合肥230026;2.史蒂文斯理工学院商学院,霍博肯 07030, 美国; 3.中山大学岭南学院金融系,广东广州 510275
  • 收稿日期:2016-01-22 修回日期:2016-05-10 接受日期:2016-05-10 出版日期:2023-03-27 发布日期:2016-05-10
  • 通讯作者: 谢金贵
  • 作者简介:刘刚,男,1992年生,硕士. 研究方向:金融工程. E-mail: liugang1@mail.ustc.edu.cn
  • 基金资助:
    国家自然科学基金(71571176),国家自然科学基金青年基金(71501196),中央高校基本科研业务费专项资金(14wkpy63)资助.

A simulation approach to financial options Greeks estimation under Lévy processes

LIU Gang, CUI Zhenyu, LIU Yanchu, XIE Jingui   

  1. 1.School of Management, University of Science and Technology of China, Hefei 230026, China; 2.Financial Engineering Division, School of Systems and Enterprises, Stevens Institute of Technology, Hoboken,NJ 07030,United States; 3.Department of Finance, Lingnan (University) College, Sun Yat-sen University, Guangzhou 510275, China
  • Received:2016-01-22 Revised:2016-05-10 Accepted:2016-05-10 Online:2023-03-27 Published:2016-05-10

摘要: 金融期权风险对冲参数的精确估计是衍生品风险管理实践的重要环节,也是金融工程学术界研究的热点之一.模拟仿真方法由于规避了“维度灾难”问题,近年来成为金融工程的主流技术之一.提出了一种基于路径求导的新的模拟仿真方法,来高效地估计Lévy过程下的金融期权风险对冲参数.对于满足Lévy过程的资产价格模型,仅有特征函数是已知的,通过Fourier逆变换并且通过线性插值方法来构造其分布函数和密度函数,从而可以生成随机样本并得到风险对冲参数的模拟仿真估计.数值试验验证了该方法的实际效果,结果显示,与文献中现有的方法相比,提出的估计方法具有更高的计算效率.

关键词: 风险对冲参数, 路径求导法, 特征函数, Lévy过程

Abstract: Accurate estimation of the Greeks for financial options is an important practical procedure for risk management of financial derivatives. It is also an important topic in financial engineering research. Monte Carlo simulation method, being capable of avoiding the problem of “curse of dimensionality”, is one of the most popular computational tools in financial engineering. Here a new Monte Carlo simulation method was developed to estimate Greeks for financial options under Lévy processes. For asset price models following Lévy processes, only the characteristic functions are known. By building our method on Fourier transform inversion and linear interpolations, approximations of the cumulative distribution functions and the probability density functions can be obtained, paving the way for generating random samples and constructing Monte Carlo simulation estimates to the Greeks. Numerical experiments were conducted to illustrate the efficiency of the proposed method and the results show that it performs more efficiently than alternatives in the literature.

Key words: Greeks, pathwise derivative method, characteristic function, Lévy process

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