不规则时间序列波动率建模:高频与低频的统一被引量：6

Modeling volatility of irregularly spaced time series:Union of high-frequency and low-frequency data

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摘要在Kim和Wang (2016)提出的统一的GARCH-Ito模型的基础上进行推广,提出了一种将高频与低频数据相结合进行波动率建模的更一般的方法.该方法允许在高频波动率中以一种更加灵活的方式嵌入低频的GARCH结构,从而拓宽了模型的适用范围.理论研究表明,模型参数的拟似然估计具有良好的极限性质,模拟研究则验证了估计量在有限样本下的有效性.在实证分析中,新方法被用于改进Easley等(2013, 2016)提出的BVC算法,得到了市场参与者交易意图的更精确的估计. This paper extends the unified GARCH-Ito model proposed by Kim and Wang(2016) and introduces a more general method to model volatility with the combination of high-frequency and lowfrequency data. The new method embeds a low-frequency GARCH structure into high-frequency volatility in a more flexible way, thus embraces a broader application. Theory and simulation study found good asymptotic property and finite sample performances of the quasi-maximum likelihood estimators proposed.In an empirical study, this new method was used to improve the bulk volume classification(BVC, Easley et al.(2013, 2016)). As a result, market participants’ trading intentions were estimated more precisely.

作者吴奔张波赵丽丽 WU Ben;ZHANG Bo;ZHAO Lili(Center for Applied Statistics,School of Statistics,Renmin University of China,Beijing 100872,China;Business College,Yangzhou University,Yangzhou 225127,China)

机构地区中国人民大学应用统计研究中心统计学院扬州大学商学院

出处《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2019年第1期36-48,共13页 Systems Engineering-Theory & Practice

基金国家自然科学基金(71271210 71471173) 教育部人文社会科学重点研究基地项目(14JJD910002) 江苏省高校哲学社会科学研究基金(2018SJA1148)~~

关键词高频数据 GARCH结构 BVC算法 high-frequency data GARCH structure bulk volume classification

分类号 F832.51 [经济管理—金融学]

作者简介通讯作者:张波(1960-),男,汉,黑龙江拜泉人,教授,博士,博士生导师,研究方向:金融高频数据分析,金融计量学,E-mail:mabzhang@ruc.edu.cn;吴奔(1991-),男,汉,浙江富阳人,博士研究生,研究方向:金融高频数据分析,E-mail:wuben1682000@163.com;赵丽丽(1983-),女,汉,山东聊城人,讲师,博士,研究方向:金融数据分析,E-mail:zhaolililut@163.com.

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参考文献3

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