Decoupling Interday and Intraday Volatility Dynamics With Price Durations

IF 1.2 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Yifan Li, Ingmar Nolte, Sandra Nolte, Shifan Yu
{"title":"Decoupling Interday and Intraday Volatility Dynamics With Price Durations","authors":"Yifan Li,&nbsp;Ingmar Nolte,&nbsp;Sandra Nolte,&nbsp;Shifan Yu","doi":"10.1111/jtsa.12849","DOIUrl":null,"url":null,"abstract":"<p>This article introduces a novel framework for volatility estimation based on price durations with an adaptive price change threshold. This innovation allows us to disentangle daily and intraday volatility dynamics from price durations, which greatly simplifies the parametric modelling of price durations and hence leads to more accurate volatility estimators. Simulation results demonstrate superior finite-sample performance of our duration-based estimators for both spot and integrated volatility compared with some established methods. An empirical application based on intraday data for the SPDR S&amp;P 500 ETF highlights the improved forecasting accuracy of our integrated volatility estimator within a standard daily volatility forecasting framework. Furthermore, an intraday analysis of spot volatility estimation shows that our method can capture the immediate and substantial impact of FOMC news announcements on market volatility.</p>","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":"46 6","pages":"1224-1250"},"PeriodicalIF":1.2000,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jtsa.12849","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Time Series Analysis","FirstCategoryId":"100","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jtsa.12849","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

This article introduces a novel framework for volatility estimation based on price durations with an adaptive price change threshold. This innovation allows us to disentangle daily and intraday volatility dynamics from price durations, which greatly simplifies the parametric modelling of price durations and hence leads to more accurate volatility estimators. Simulation results demonstrate superior finite-sample performance of our duration-based estimators for both spot and integrated volatility compared with some established methods. An empirical application based on intraday data for the SPDR S&P 500 ETF highlights the improved forecasting accuracy of our integrated volatility estimator within a standard daily volatility forecasting framework. Furthermore, an intraday analysis of spot volatility estimation shows that our method can capture the immediate and substantial impact of FOMC news announcements on market volatility.

Abstract Image

与价格持续时间的日内和日内波动动态解耦
本文介绍了一种新的基于价格持续时间和自适应价格变化阈值的波动率估计框架。这一创新使我们能够从价格持续时间中分离出每日和日内波动动态,从而大大简化了价格持续时间的参数化建模,从而产生更准确的波动估计器。仿真结果表明,与现有方法相比,基于持续时间的估计方法在有限样本范围内具有较好的实时和综合波动率估计性能。基于SPDR s&p 500 ETF日内数据的实证应用突出了我们在标准日波动率预测框架内的综合波动率估计器的预测准确性。此外,对现货波动率估计的日内分析表明,我们的方法可以捕捉到联邦公开市场委员会新闻公告对市场波动的直接和实质性影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书