中国期权市场隐含信息与股票波动率的研究  

Chinese Option-implied Information and Stock Volatility Forecasting

作　　者：崔海蓉[1] 陶亦李 Hairong Cui;Yii Tao(School of Management Engineering,Nanjing University of Information Engineering,Nanjing,Jiangsu,210007)

机构地区：[1]南京信息工程大学,江苏南京210007

出　　处：《管理科学与研究（中英文版）》2022年第8期29-35,共7页Management Science and Research

摘　　要：20世纪90年代爆发的一系列金融危机促使各国寻求各种途径来强化金融系统稳健性和保障金融可持续发展,其中波动率预测发挥着不可或缺的作用。现有研究中,波动率的预测模型层出不穷,而期权作为一种风险管理工具,其灵活的设计吸引了众多投资者进行交易,也吸引了众多对于期权前瞻性隐含信息的研究。为探讨基于期权价格形成的隐含信息是否能够预测股票市场的波动率,我们提取了中国上证50ETF期权价格中的隐含信息,包括隐含波动率、隐含波动率差、风险中性偏度和方差风险溢价,基于GARCH模型和EGARCH模型进行研究。结果表明,在上证50ETF期权市场中,隐含波动率差无论在周数据还是日数据拟合和预测能力都优于其他三个指标,并且EGARCH模型优于GARCH模型。The series of financial crises that erupted in the 1990s prompted countries to seek ways to enhance the robustness of the financial system and safeguard financial sustainability.Volatility is an important tool for strengthening the soundness of the financial system and financial sustainability.There are many different models that have been used to predict volatility in the existing literature.Options as a risk management tool have attracted more informed investors to trade them.To explore whether implicit information from option price can predict stock market volatility,we extract the implied information from the China SSE 50 ETF option prices,including implied volatility,implied volatility spread,risk-neutral skewness and variance risk premium.Then,we take the implied information as an explanatory variable to build the forecasting model of volatility based on the GARCH and EGARCH model.We find that the predictive power of the implied volatility spread outperforms the other three variables in both daily and weekly data,and that the EGARCH model outperforms the GARCH model.

关 键 词：期权隐含信息 GARCH模型 买卖权平价关系 

分 类 号：F83[经济管理—金融学]