摘要
波动率风险溢价是金融学文献关注的核心问题之一.基于非仿射GARCH扩散模型,推导相应的VIX公式,继而采用S&P500与VIX指数联合数据,给出模型客观与风险中性参数基于有效重要性抽样(EIS)的联合极大似然(ML)估计.进一步利用粒子滤波方法给出隐波动率的估计,推断VIX隐含的波动率风险溢价.蒙特卡罗模拟实验表明,提出的估计方法是有效的.采用实际数据进行的实证研究表明,波动率风险被定价,且波动率风险溢价为负,隐含市场投资者整体表现为风险厌恶.
Finance literature has put much effort on studying the volatility risk premia.In this paper,we derive the corresponding implied VIX formula under the non-affine GARCH diffusion model,and develop an efficient importance sampling(ElS)-based joint maximum likelihood(ML) estimation method for the objective and risk-neutral parameters of the model using joint data on the S&P500 and VIX indices.Then a particle filter-based estimation method is developed for the latent volatility.Hence,it allows us to infer the volatility risk premia implied by the VIX.Monte Carlo simulation study shows that our proposed approach performs well.Empirical study based on the actual data demonstrates that the volatility risk is priced by the market and the volatility risk premia are negative,which imply that investors act risk averse in the market.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2014年第S1期1-11,共11页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(71101001)
安徽省自然科学基金(1408085QG139)
安徽省高等学校省级优秀青年人才基金重点项目(2013SQRW025ZD)
