交叉熵蝙蝠算法求解期权定价模型参数估计问题

doi:10.6040/j.issn.1671-9352.0.2018.057

《山东大学学报(理学版)》 ›› 2018, Vol. 53 ›› Issue (12): 80-89.doi: 10.6040/j.issn.1671-9352.0.2018.057

交叉熵蝙蝠算法求解期权定价模型参数估计问题

李国成¹,王继霞^2*

1.皖西学院金融与数学学院, 安徽六安 237012;2.河南师范大学数学与信息科学学院, 河南新乡 453007

出版日期:2018-12-20 发布日期:2018-12-18
作者简介:李国成(1976— ),男,博士,副教授,研究方向为金融工程与计算智能. E-mail:liguocheng@wxc.edu.cn*通信作者简介:王继霞(1978— ),女,博士,副教授,研究方向为过程统计推断与金融风险管理. E-mail:jixiawang_78@163.com
基金资助:
国家自然科学基金资助项目(U1504701);安徽省科技厅软科学研究项目(1607a0202027);安徽省高等学校省级人文社会科学研究重点项目(SK2016A0971)

Calibrating option pricing models with cross entropy bat algorithm

LI Guo-cheng¹, WANG Ji-xia^2*

1. School of Finance &
Mathematics, West Anhui University, Luan 237012, Anhui, China;
2. School of Mathematics and Information Sciences, Henan Normal University, Xinxiang 453007, Henan, China

Online:2018-12-20 Published:2018-12-18

摘要/Abstract

摘要： 期权定价模型的参数估计问题通常是非线性优化问题,且是非凸优化问题,经典的优化方法已不再适用。为此探寻用交叉熵蝙蝠算法来求解Merton跳-扩散模型、Heston随机波动模型和Bates带跳的随机波动模型的参数估计问题。实证结果表明该方法是有效可行的。

关键词: 交叉熵蝙蝠算法, 期权定价模型, 参数估计, 跳-扩散模型, 随机波动模型

Abstract: Parameter estimation of option pricing model is usually a nonlinear optimization problem with no convex, which leads to the classical optimization method cannot be applied. Based on cross entropy bat algorithm, we studied how to solve parameter estimation problems of option pricing models such as Mertons jump-diffusion model, Hestons stochastic volatility model and Batess stochastic volatility with jump model. The empirical results show that the cross entropy bat algorithm is feasible and effective for solving the parameter estimation problems of option pricing model.

Key words: cross entropy bat algorithm, option pricing model, parameter estimation, jump-diffusion model, stochastic volatility model

中图分类号:

O233

李国成,王继霞. 交叉熵蝙蝠算法求解期权定价模型参数估计问题[J]. 《山东大学学报(理学版)》, 2018, 53(12): 80-89.

LI Guo-cheng, WANG Ji-xia. Calibrating option pricing models with cross entropy bat algorithm[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2018, 53(12): 80-89.

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交叉熵蝙蝠算法求解期权定价模型参数估计问题

Calibrating option pricing models with cross entropy bat algorithm

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