东南大学学报（自然科学版）2011，Vol.41Issue(1)：210-214,5.DOI:10.3969/j.issn.1001-0505.2011.01.041
基于GMD的隐含最小距离风险中性概率测度提取
Recovering implied minimum distance risk-neutral probability measure using GMD
摘要
Abstract
A new approach to estimate the implied risk-neutral probability measure of the underlying assets from option prices is presented. Under incomplete market conditions, Gaussian mixture distribution (GMD) was used to construct the mathematical optimization model of restoring the minimum distance implied risk-neutral probability measure. Furthermore, solving methods and techniques of the optimization model were discussed. The effectiveness of the model was tested using European option data. The results show that the real risk-neutral probability measure can be approximated by the Gaussian mixture distribution of two components; the shape of it is more leptokurtic, being bimodal with a smaller peak at the left tail. This indicates that market participants expect the future with higher concentration. However, expectation for extremely unfavorable price movement (left tail) is higher than that for the extremely favorable price movement (right tail ), so traditional assumptions on the underlying asset with lognormal distribution would underestimate potential loss.关键词
风险中性概率测度/高斯混合分布/最小距离Key words
risk-neutral probability measure/ Gaussian mixture distributions/ minimum distance分类
管理科学引用本文复制引用
崔海蓉,胡小平..基于GMD的隐含最小距离风险中性概率测度提取[J].东南大学学报（自然科学版）,2011,41(1):210-214,5.基金项目
国家自然科学基金资助项目(70671025). （70671025）
