基于Lévy过程高阶矩波动模型的期权定价  

Option Pricing Based on Higher Moment Volatility Model with Lévy Processes

作　　者：宫晓莉[1] 庄新田[1] 

机构地区：[1]东北大学工商管理学院,辽宁沈阳110169

出　　处：《系统工程》2016年第9期22-28,共7页Systems Engineering

基　　金：国家自然科学基金资助项目(71171042)

摘　　要：假设新息随机因子服从非高斯Lévy分布,将反映金融资产高阶矩特征NGARCHSK模型与刻画金融价格变化纯跳跃现象Lévy过程相结合,描述了资产收益率无限跳跃情形下的时变性,有效捕获了金融资产收益率尖峰有偏和杠杆效应。收益率时间序列验证了调和稳定分布刻画尖峰厚尾能力的优越性。结合波动率的高阶矩特征进行等价鞅测度变化,对我国首只股票期权进行定价,对比了数值积分的Cosine定价方法与从属过程蒙特卡洛模拟定价方法的效率。Assuming asset prices innovations follow non-gaussian L6vy distribution, ths paper combines higher order moment volatility NGARCHSK model with Levy processes which reflect pure jump phenomena of price change in daily returns. This combined model describes time-varying property of asset returns in infinite jump situation, effectively cap- tures its high peak and fat tail characteristic, as well as leverage effect. Time series analysis of asset returns proves that tempered stable distribution has superiority ability in reflecting high peak and fat tail. Equivalent martingale measure change considers high order moment feature of volatility. When pricing the first stock option in our country, we compare the efficiency of numerical integration Cosine pricing method and subordination process monte carlo simulation pricing method.

关 键 词：时变高阶矩 LEVY过程 调和稳定分布 Cosine方法 期权定价 

分 类 号：F830[经济管理—金融学]