{"title":"A modified VAR-deGARCH model for asynchronous multivariate financial time series via variational Bayesian inference","authors":"Wei-Ting Lai , Ray-Bing Chen , Shih-Feng Huang","doi":"10.1016/j.ijforecast.2024.06.002","DOIUrl":null,"url":null,"abstract":"<div><div><span>This study proposes a modified VAR-deGARCH model, denoted by M-VAR-deGARCH, for modeling asynchronous multivariate financial time series<span><span> with GARCH effects and simultaneously accommodating the latest market information. A variational Bayesian (VB) procedure is developed for the M-VAR-deGARCH model to infer structure selection and parameter estimation. We conduct extensive simulations and empirical studies to evaluate the fitting and forecasting performance of the M-VAR-deGARCH model. The simulation results reveal that the proposed VB procedure produces satisfactory selection performance. In addition, our empirical studies find that the latest market information in </span>Asia can provide helpful information to predict market trends in Europe and </span></span>South Africa, especially when momentous events occur.</div></div>","PeriodicalId":14061,"journal":{"name":"International Journal of Forecasting","volume":"41 1","pages":"Pages 345-360"},"PeriodicalIF":6.9000,"publicationDate":"2024-06-21","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/S0169207024000566","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 study proposes a modified VAR-deGARCH model, denoted by M-VAR-deGARCH, for modeling asynchronous multivariate financial time series with GARCH effects and simultaneously accommodating the latest market information. A variational Bayesian (VB) procedure is developed for the M-VAR-deGARCH model to infer structure selection and parameter estimation. We conduct extensive simulations and empirical studies to evaluate the fitting and forecasting performance of the M-VAR-deGARCH model. The simulation results reveal that the proposed VB procedure produces satisfactory selection performance. In addition, our empirical studies find that the latest market information in Asia can provide helpful information to predict market trends in Europe and South Africa, especially when momentous events occur.
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.
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