A Real-Time GARCH-MIDAS model

Xinyu Wu, An Zhao and Tengfei Cheng

Finance Research Letters, 2023, vol. 56, issue C

Abstract: This paper proposes the Real-Time GARCH-MIDAS model to model and forecast volatility. An empirical application to the Shanghai Stock Exchange Composite Index (SSEC) and Shenzhen Stock Exchange Component Index (SZSEC) of China shows that the Real-Time GARCH-MIDAS model outperforms competing models in terms of both empirical return fitting and out-of-sample volatility forecasting. Moreover, the superior forecasting performance of the Real-Time GARCH-MIDAS model is robust to alternative rolling windows, alternative benchmark models, alternative MIDAS lags and alternative volatility proxy. Further discussion illustrates the flexibility of the Real-Time GARCH-MIDAS model.

Keywords: Real-Time GARCH-MIDAS; Persistence; Current return information; Volatility of volatility; Volatility forecasting (search for similar items in EconPapers)
JEL-codes: C32 C5 G17 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323004750

DOI: 10.1016/j.frl.2023.104103

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