Forecasting the Chinese low-carbon index volatility

Dexiang Mei, Chenchen Zhao, Qin Luo and Yan Li

Resources Policy, 2022, vol. 77, issue C

Abstract: This paper investigates the predictive power of economic policy uncertainty on the Chinese low-carbon market volatility and takes into account realized measures. First, in-sample analysis shows that both economic policy uncertainty and intraday high-frequency information have a significant impact on low-carbon index volatility. Second, out-of-sample evaluations show that the model combining China's economic policy uncertainty and intraday high-frequency information has the best predictive power. Finally, we use several robustness tests of alternative macroeconomic variable, alternative forecasting window, and alternative realized measure to prove that the results of this study are robust. This study enriches the market volatility model research. In addition, it can also promote low-carbon investment and provide a reference for national macro-control.

Keywords: GARCH model; China'S economic policy uncertainty; Realized measure; The Chinese low-carbon index (search for similar items in EconPapers)
JEL-codes: C22 C53 C58 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001805

DOI: 10.1016/j.resourpol.2022.102732

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