高阶矩风险溢酬:信息含量及影响因素  

The High-order Moments Risk Premium:Information Content and Influencing Factors

作　　者：郑振龙[1] 郑国忠 

机构地区：[1]厦门大学管理学院,福建厦门361005 [2]厦门国际银行股份有限公司,福建厦门361005

出　　处：《数理统计与管理》2017年第3期550-570,共21页Journal of Applied Statistics and Management

基　　金：国家自然科学基金面上项目(71371161);国家自然科学基金青年项目(71101121);国家自然科学基金地区项目(71261024)

摘　　要：本文基于台湾股市和期权市场数据,研究波动率、偏度和峰度等高阶矩风险溢酬的信息含量及影响因素,并结合边际贡献度分析了各常见影响因素对高阶矩风险溢酬的解释力。研究结论表明:波动率间的相关性高于偏度和峰度,波动率也更易于预测;期权市场的隐含矩信息对未来实际矩有较好解释力,且引入多个市场信息的预测效果要优于单一市场。市场情绪和异质信念是各高阶矩风险溢酬的主要影响因素;流动性信息次之;市场因子的解释相对较弱。对高阶矩风险溢酬影响因素的分析还应引入市场极端风险、风险厌恶信息和宏观经济变量等因素的考察。Based on Taiwan Residents stock index and index options market data, this paper researches the high- order moment information content and influencing factors. The conclusions show that： The correlation between the volatility information is better than that of skewness and kurtosis, and volatility is easier to predict. Kurtosis risk can transmit through the volatility, but both drivers are not exactly the same. The volatility, skewness and kurtosis risk premia are new pricing factors that cannot be ignored. Market sentiment and heterogeneous beliefs are the main influencing factors. Market sentiment and liquidity can provide pricing information through high-order moments risk premia. In addition to these, to analyzing the high-order moments risk premia should also introduce the extreme risk, risk aversion information and macro-economic factors.

关 键 词：股指期权 高阶矩 风险溢酬 影响因素 

分 类 号：F830[经济管理—金融学] F830.91