高频数据HMCMC方法在Black-Scholes模型中的应用  

APPLICATION OF HIGH FREQUENCY DATA HMCMC METHOD IN BLACK-SCHOLES MODEL

作　　者：赖俊峰[1,2] 闫在在 LAI Junfeng;YAN Zaizai(Science College,Inner Mongolia University of Technology,Hohhot 010051,China;Inner Mongolia Key Laboratory of Statistical Analysis Theory for Life Data and Neural Network Modeling,College of Sciences,Inner Mongolia University of Technology,Hohhot 010051,China)

机构地区：[1]内蒙古工业大学理学院,呼和浩特010051 [2]内蒙古自治区生命数据统计分析理论与神经网络建模重点实验室,呼和浩特010051

出　　处：《内蒙古农业大学学报（自然科学版）》2021年第5期100-103,共4页Journal of Inner Mongolia Agricultural University(Natural Science Edition)

基　　金：国家自然科学基金项目(11361036);内蒙古工业大学博士基金项目(BS201930)。

摘　　要：通过期权定价Black-Scholes模型,采用贝叶斯方法对模型中未知参数给出后验分布,通过高频数据扩充(HFA)的Mone Carlo(MC)方法(HMCMC)给出Black-Scholes模型参数波动率的数值结果,并和矩估计的方法做了比较,数值结果表明,所提出的方法具有较好的应用价值.Through the option pricing Black-Scholes model,the Bayesian method was used to give the posterior distribution of the unknown parameters in the model,and the Mone Carlo(MC)method(HMCMC)of the high frequency data expansion(HFA)was used to give the numerical results of the Black-Scholes model and compared with the moment estimation method.The numerical results show that the proposed method has good application value.

关 键 词：BLACK-SCHOLES模型 Monte Carlo(MC) 数值模拟 R软件 

分 类 号：O242.1[理学—计算数学]