Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model

Lu Wang, Chenchen Zhao, Chao Liang and Song Jiu

Finance Research Letters, 2022, vol. 48, issue C

Abstract: Given that the new energy stock market plays a vital part in the development of China's new energy industry, we first introduce the REGARCH-MIDAS model to predict volatility in the new energy stock market. Intraday, daily and monthly data, and the leverage effect are simultaneously fully introduced in a MIDAS setting, the in-sample results show that the REGARCH-MIDAS model can obtain an optimal estimate. Moreover, the out-of-sample results demonstrate that the REGARCH-MIDAS model exhibits the strongest predictive power in all selected models. Finally, our conclusions are robust to further robustness checks. Our work provides deep insights into how to predict the volatility of China's new energy by using three different frequency data.

Keywords: China's new energy; Realized EGARCH-MIDAS; Volatility prediction; New energy stock market (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:48:y:2022:i:c:s1544612322002306

DOI: 10.1016/j.frl.2022.102981

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