Accurate CO2 forecasting plays an important role in energy planning. However, in the annual forecasting studies on CO2 emissions, the seasonal effects cannot be predicted. To overcome this problem, this study proposed a novel prediction model based on the seasonally optimised fractional...

This paper employs the quantile autoregressive (QAR) model to examine the forecasting relationship between stock volatility and crude oil volatility. We firstly employ the sup-Wald test to evaluate Granger causality across various quantile levels, which provides valuable information in...