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Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market

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  • Yu, Honghai
  • Fang, Libing
  • Sun, Wencong

Abstract

This paper investigates the impact of global economic policy uncertainty (GEPU) on the volatility of the Chinese stock market and whether GEPU has predictive power for the volatility of the Chinese stock market. We apply the generalized autoregressive conditional heteroscedastic mixed data sampling (GARCH–MIDAS) model to evaluate the impact of the monthly GEPU index on the daily Shanghai Composite index. Our empirical results show that GEPU has a positive and significant influence on the volatility of the Chinese stock market, which reflects that Chinese stock market has been gradually integrated into the global economy. In addition, the forecasts generated by the GARCH–MIDAS model with GEPU and RV (Realized Volatility) produce substantially smaller errors than the GARCH (1,1) model and the GARCH–MIDAS model with RV (measured by RMSE, RMAE, RMSD, RMAD loss functions and DM test), which confirms the important role of GEPU for predicting the volatility of the Chinese stock market. Overall, our findings imply that GEPU is an additional driving factor of long-term volatility in the Chinese stock market.

Suggested Citation

  • Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
  • Handle: RePEc:eee:phsmap:v:505:y:2018:i:c:p:931-940
    DOI: 10.1016/j.physa.2018.03.083
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