Salience theory has been proposed as a new stock trading strategy. Therefore, to assess the validity of this proposal, a complex decision trading system was constructed based on salience theory, a variational mode decomposition (VMD) model, a bidirectional gated recurrent unit (BiGRU) model, and high-frequency trading. The system selected 30 Chinese new energy concept stocks, ranked the stocks using salience theory, and selected the top and bottom three stocks for two portfolios. Twelve stages were established, after which the VMD and BiGRU models were applied to the predictions. The final predicted returns for the high ST group A (GA) were 194.06% and for the low ST group B (GB) were 165.88%. This paper validated the powerful utility of salience theory and deep learning to analyze Chinas new energy market. And it explains the issues and questions raised by previous researchers.

This study examines the impact of ESG rating events on innovation in China's new energy vehicle industry. The baseline Difference-in-Differences (DID) analysis demonstrates that ESG ratings promote innovation among new energy vehicle companies. A series of robustness tests, including parallel trend analysis and placebo tests, support the baseline results. The channel tests in the mechanism analyses indicate that ESG ratings promote innovation in new energy vehicle enterprises by increasing R&D investment and the number of R&D personnel. Other mechanism analyses suggest that ESG ratings also enhance innovation output and quality by stimulating green patent applications, encouraging joint patent applications, and increasing the number of high-quality patents.

The existing literature mainly documents the relationship between international and domestic fossil energy markets; however, empirical evidence of the dynamic relationships between fossil energy market and new energy market is lacking. This paper combines TGARCH model and copula model to explore the dynamic linkages and spillover effects between international fossil energy (crude oil, coal and natural gas) markets and China's new energy market using daily data from 4 January 2012 to 3 September 2018. The empirical results indicate that fossil energy returns and new energy returns are positive related over time. And the crude oil returns and new energy returns, as well as the coal returns and new energy returns have lower tail dependence, while there is upper tail dependence structure between natural gas returns and new energy returns. Furthermore, the extreme upside and downside risk spillover from international fossil energy markets to China's new energy market is asymmetric. Among the spillover effects, the downward risk spillover of crude oil market exerts the most significant impact on China's new energy market.