This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine) model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine) is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search), PSO (particle swarm optimization), and GA (genetic algorithm). Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

In the context of “new normal” economy and frequent “haze”, the strategy of energy conservation and emission reduction aiming to lower costs and reduce pollution is currently still a major strategic direction in China and the world, and will remain so for some time in the future. This paper uses the annual data of West Texas Intermediate (WTI) crude oil price in 1987–2014 as samples. We firstly present the direction and mechanism of the influence of oil price change on total consumption of every kind of energy by path analysis, and then consider establishing a Structural Vector Autoregression model of energy conservation and emission reduction in three statuses. Research shows that if the international oil price increases by 1%, the energy consumption per GDP and carbon dioxide emission increase by 0.092% and 0.053% respectively in the corresponding period. In the status of high energy consumption and high emission, if the international oil price increases by 1%, the energy consumption per GDP and carbon dioxide emission increase by 0.043% and 0.065% respectively in the corresponding period. In the status of low energy consumption and low emission, if the international oil price increases by 1%, the energy consumption per GDP per unit increases by 0.067% and carbon dioxide emission decreases by 0.085% in the corresponding period.

Under the concept of green development, coal and oil control policies were frequently introduced, but the “cold” thinking under the “hot” environment is more conducive to the smooth promotion of the “transitional period” of China’s power-structure transformation. How to better consider production efficiency and environmental benefits is the theme that thermal power enterprises need to constantly break through. The most feasible “transitional period” path for thermal power enterprises is improving the efficiency of energy saving, reducing emissions, and simultaneously ensuring benefits and social awareness. This paper selected 17 listed companies in China’s thermal power sector, combined with their input resources, output, and other indicators, using a slacks-based measure–data envelopment analysis (SBM–DEA) model with undesirable outputs, and comprehensively analyzed the relationship among the technical efficiency improvement and the industry status, including price earnings ratio (P/E ratio) in the recent two years. The results show that the improvement of energy efficiency can indeed optimize enterprises’ operations and improve P/E ratio. Although clean-energy power generation has better environmental benefits, it is still lacking in efficiency; therefore, the balance between efficiency and environment sustainability should concern us.