Forecasting the Chinese Low-Carbon Index Volatility

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.