已实现波动GAS-HEAVY模型及其实证研究

doi:10.16381/j.cnki.issn1003-207x.2019.01.001

中国管理科学 ›› 2019, Vol. 27 ›› Issue (1): 1-10.doi: 10.16381/j.cnki.issn1003-207x.2019.01.001

• 论文 • 下一篇

已实现波动GAS-HEAVY模型及其实证研究

沈根祥^1,2, 邹欣悦¹

1. 上海财经大学经济学院, 上海 200433;
2. 上海财经大学数理经济学教育部重点实验室, 上海 200433

收稿日期:2017-08-29 修回日期:2017-12-14 出版日期:2019-01-20 发布日期:2019-03-25
通讯作者: 沈根祥(1964-),男(汉族),河南许昌人,上海财经大学经济学院教授,博士生导师,研究方向:金融计量经济学、金融市场数量分析,E-mail:sgxman@shfue.edu.cn. E-mail:sgxman@shfue.edu.cn
基金资助:
国家社科基金重大项目（16ZDA031）

GAS-HEAVY Model for Realized Measures of Volatility and Returns

SHEN Gen-xiang^1,2, ZOU Xin-yue¹

1. Economics School, Shanghai University of Finance and Economics, Shanghai 200433, China;
2. Key Laboratory of Mathematical Economics, Ministry of Education, Shanghai 200433, China

Received:2017-08-29 Revised:2017-12-14 Online:2019-01-20 Published:2019-03-25

摘要/Abstract

摘要： 引入日内高频数据计算的已实现波动，能够提高波动模型预测能力。本文将日收益和已实现波动联合建模，提出一种新的波动模型。选取尺度调整t分布和F分布作为日收益和已实现波动的分布，更为充分和灵活地捕捉厚尾性，采用得分驱动方法设定波动模型更新项，得出广义自回归得分（GAS）波动模型，提高对实际模型的逼近效率。本文对模型遍历性和平稳性进行证明，并与同类模型进行比较。蒙特卡罗模拟实验显示，在数据生成过程误设的情况下本文提出的GAS-HEAVY模型比同类模型具有更好的数据拟合效果。基于沪综指、深成指和沪深300指数2013.1至2017.4日内1分钟高频数据实证分析表明，不同损失函数的SPA检验下GAS-HEAVY模型的波动预测能力显著强于其它同类模型。本文给出的GAS-HEAVY模型为有关理论研究和市场应用提供了新的波动计量工具。

关键词: 已实现波动, 厚尾分布, 得分驱动

Abstract: A new volatility model named GAS-HEAVY is introduced to model returns and realized measures of volatility jointly. The key features are fat-tailed distributions for returns and realized volatilities and autoregressive score-driven (GAS) model for dynamics of the latent volatility. By assuming a rescaled t distribution for daily returns and a rescaled F distributionfor realized volatility measures, the score dynamics for the latent volatility are robust to outliers and incidental large observations. Parameter restrictions are formulated to prove ergodicity and stationarity.Our simulation study shows that the new model fit data better than other alternatives. An empirical application of our model is provided to daily returns and 1-minute intraday high-frequency prices of Shanghai Composite Index,Shenzhen Component Index and CSI300 Index. The empirical evidences justify the superior volatility predictive ability of the new model in our paper.

Key words: realized volatility, fat-tailed distribution, score-driven

中图分类号:

F803.9

沈根祥, 邹欣悦. 已实现波动GAS-HEAVY模型及其实证研究[J]. 中国管理科学, 2019, 27(1): 1-10.

SHEN Gen-xiang, ZOU Xin-yue. GAS-HEAVY Model for Realized Measures of Volatility and Returns[J]. Chinese Journal of Management Science, 2019, 27(1): 1-10.

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已实现波动GAS-HEAVY模型及其实证研究

GAS-HEAVY Model for Realized Measures of Volatility and Returns

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