{"title":"Decoupling Interday and Intraday Volatility Dynamics With Price Durations","authors":"Yifan Li, Ingmar Nolte, Sandra Nolte, 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&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.
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.