期权交易量能预测波动率吗——来自上证50ETF期权的证据  

Can option trading volume forecast volatility?Evidence from Shanghai Stock Exchange 50ETF option

作　　者：万谍[1] 田毅 WAN Die;TIAN Yi(School of Finance,Zhejiang Gongshang University,Hangzhou 310018,China)

机构地区：[1]浙江工商大学金融学院,杭州310018

出　　处：《系统工程理论与实践》2023年第3期755-771,共17页Systems Engineering-Theory & Practice

基　　金：浙江省社科基金青年项目(23NDJC353YB);浙江省自然科学基金一般项目(LY18G030011,LY21G010001);浙江省属高校基本科研业务费专项资金(XR202211)。

摘　　要：本文基于上证50ETF期权日交易量,按在值程度构建虚值,平值和实值期权的交易量占比,测试各类期权交易对上证50ETF已实现波动率的预测能力.结果发现虚值期权能显著提升HAR,HAR-CJ模型的波动率预测效果.进一步研究发现,虚值期权中的信息含量主要来自于深度虚值期权,非深度虚值期权对波动率预测效果较弱.相比隐含波动率,深度虚值期权对波动率的样本内拟合和样本外预测效果都更佳.深度虚值期权中,看涨期权的信息含量大于看跌期权,且看涨期权交易量与未来波动率负相关,看跌期权交易量与未来波动率正相关.这些结果表明,信息交易者倾向于使用深度虚值期权交易,而深度虚值看跌和看涨期权与未来波动率的不同关联性恰好与杠杆效应一致.本文的发现可用于改进现有的波动率预测模型,还将有助于完善监管者的风控指标体系.Using daily trading volume of Shanghai Stock Exchange 50ETF option,the paper calculates the volume percentages of out-of-the-money(OTM),at-the-money(ATM),in-themoney(ITM)options and investigates the forecasting ability of each kind of option trading on the realized volatility of underlying ETF.The results show that OTM option trading can significantly promote the predicting power of HAR and HAR-CJ models.Further findings show that,the information of OTM option mainly comes from the deep-out-of-the-money(DOTM)option,while the non-DOTM option has weaker performance in forecasting volatility.Comparing with implied volatility,DOTM option has better performance in in-sample fitting and out-ofsample forecasting volatility.Among the DOTM options,call option has more information than put option,and the call option trading negatively relates to future volatility while the put option trading positively relates to future volatility.These results indicate that informed traders prefer to using DOTM option,and the opposite correlations of DOTM call and put option with future volatility are consistent with leverage effect.Our findings can be applied in improving current volatility forecasting models,and can also be helpful in optimizing governors’risk monitoring systems.

关 键 词：深度虚值期权 已实现波动率 HAR模型 波动率预测 中国期权市场 

分 类 号：F832.5[经济管理—金融学]