{"title":"Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data","authors":"Jin-Yu Fu, Jin-Guan Lin, Hong-Xia Hao","doi":"10.1016/j.ijforecast.2022.08.006","DOIUrl":null,"url":null,"abstract":"<div><p>This paper introduces a model that can accommodate both the continuous-time-diffusion and discrete-time mixed-GARCH–Jump models by embedding the discrete mixed-GARCH-Jump structure in the continuous volatility process. The key feature of the proposed model is that the corresponding conditional integrated volatility adopts the mixed-GARCH-Jump structure that accounts for the effect of jumps on future volatility. A Griddy–Gibbs sampler approach is proposed to estimate parameters, and volatility forecasting and value-at-risk forecasting based on the peaks-over-threshold method are developed. Simulations are carried out to check the finite sample performance of the proposed methodology, and empirical studies show that, in general, volatility is heavily influenced by the continuous innovations, rather than the extreme reactions. We find that both the simulation and empirical results in most cases support the proposed model.</p></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"39 4","pages":"Pages 1698-1712"},"PeriodicalIF":6.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169207022001157","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper introduces a model that can accommodate both the continuous-time-diffusion and discrete-time mixed-GARCH–Jump models by embedding the discrete mixed-GARCH-Jump structure in the continuous volatility process. The key feature of the proposed model is that the corresponding conditional integrated volatility adopts the mixed-GARCH-Jump structure that accounts for the effect of jumps on future volatility. A Griddy–Gibbs sampler approach is proposed to estimate parameters, and volatility forecasting and value-at-risk forecasting based on the peaks-over-threshold method are developed. Simulations are carried out to check the finite sample performance of the proposed methodology, and empirical studies show that, in general, volatility is heavily influenced by the continuous innovations, rather than the extreme reactions. We find that both the simulation and empirical results in most cases support the proposed model.
期刊介绍:
The International Journal of Forecasting is a leading journal in its field that publishes high quality refereed papers. It aims to bridge the gap between theory and practice, making forecasting useful and relevant for decision and policy makers. The journal places strong emphasis on empirical studies, evaluation activities, implementation research, and improving the practice of forecasting. It welcomes various points of view and encourages debate to find solutions to field-related problems. The journal is the official publication of the International Institute of Forecasters (IIF) and is indexed in Sociological Abstracts, Journal of Economic Literature, Statistical Theory and Method Abstracts, INSPEC, Current Contents, UMI Data Courier, RePEc, Academic Journal Guide, CIS, IAOR, and Social Sciences Citation Index.