Do weather conditions drive China's carbon-coal-electricity markets systemic risk? A multi-timescale analysis

This paper uses the wavelet coherency method to reveal the timescale-varying driving mechanism of 12 different types of weather conditions data on risk measures of China's Carbon-Coal-Electricity (CCE) system. First, we find that temperature may be a major factor influencing the co-movement pattern of China's CCE system on a long-term timescale, but cannot affect information spillover pattern of the CCE system. Second, snowfall, cloud, and wind levels could influence the long-term variation of the CCE system's risk measurement. Third, none of the selected weather condition indicators could influence the short- and medium-run CCE systemic risk.