 Mixed-frequency SV model for stock volatility and macroeconomicsYuhuang Shang and Tingguo Zheng Economic Modelling, 2021, vol. 95, issue C, 462-472 Abstract: This paper develops a stochastic volatility-mixed frequency data sampling (SV-MIDAS) model with low frequency macro variables and further extends it to an asymmetric SV-MIDAS model. Empirical study is then implemented on both Chinese and U.S. stock markets. Our results show that the SV-MIDAS model is useful to identify the macroeconomic volatility source of stock volatility and improve the in-sample fitting performance. Moreover, the out-of-sample forecast performances of SV-MIDAS model are significantly superior to that of traditional SV model for both Chinese and U.S. stock markets. In particular, among the macroeconomic variables, the Composite Leading Indicator has the best forecast performance. In addition, we find that the asymmetric SV-MIDAS model is applicable for capturing leverage effects in both stock markets and it outperforms the corresponding benchmark model in the in-sample fitting. Keywords: SV-MIDAS model; Component decomposition; Forecast; Macroeconomic; Leverage effect (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:95:y:2021:i:c:p:462-472 DOI: 10.1016/j.econmod.2020.03.013 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.