[1]胡小平,何建敏.LSSVM-Monte Carlo 定价高维美式期权[J].东南大学学报(自然科学版),2006,36(1):179-182.[doi:10.3969/j.issn.1001-0505.2006.01.036]
 Hu Xiaoping,He Jianmin.Pricing high-dimension American option by LSSVM-Monte Carlo[J].Journal of Southeast University (Natural Science Edition),2006,36(1):179-182.[doi:10.3969/j.issn.1001-0505.2006.01.036]
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LSSVM-Monte Carlo 定价高维美式期权()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
36
期数:
2006年第1期
页码:
179-182
栏目:
经济与管理
出版日期:
2006-01-20

文章信息/Info

Title:
Pricing high-dimension American option by LSSVM-Monte Carlo
作者:
胡小平 何建敏
东南大学经济管理学院, 南京 210096
Author(s):
Hu Xiaoping He Jianmin
College of Economics and Management, Southeast University, Nanjing 210096,China
关键词:
最小二乘支持向量机 改进序列优化 Monte Carlo 高维美式期权
Keywords:
least square support vector machines improved sequential minimal optimization Monte Carlo high-dimension American option
分类号:
F830.59
DOI:
10.3969/j.issn.1001-0505.2006.01.036
摘要:
随着美式期权维数的增加,存在所谓的“维数灾难”问题,为了克服这一难题,最小二乘支持向量机(LSSVM)被应用于定价高维美式期权.首先用M-C方法仿真美式期权标的物的多条价格路径,接着采用最小二乘支持向量机作为求条件期望的回归算子,并提出了一种基于改进序列优化(ISMO)的LSSVM的训练算法.针对4种不同的美式期权支付函数,给出了该方法应用于标的资产的个数分别为5和30的算例.研究结果表明,所提出的方法能很好地解决高维美式期权定价问题.
Abstract:
Least-squares SVM(LSSVM)was applied to pricing high-dimension American option to solve the so-called “dimension curse” problem along with the rise of dimension. Firstly, Monte Carlo(M-C)method was used to simulate many price paths of underlying assets, and LSSVM worked as regress operator for solving the conditional expectation. Moreover, training algorithm of LSSVM was proposed based on improved sequential minimal optimization(ISMO)method. Aiming at four various payment functions, an example was given when the numbers of underlying assets were respectively 5 and 30. Results show that the method proposed can solve high-dimension American option pricing problem well.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(70371035)、江苏省科技创新服务体系资助项目(BM2003 335).
作者简介: 胡小平(1971—),男,博士生; 何建敏(联系人),男,博士,教授,博士生导师,nj.jian@public1.ptt.js.cn.
更新日期/Last Update: 2006-01-20