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In this paper, we provide an exact formula for the skewness of stock returns implied in the Heston (1993) model by using a moment-computing approach. We compute the moments of Itô integrals by using Itô's Lemma skillfully. The model's affine property allows us to obtain analytical formulas for cumulants. The formulas for the variance and the third cumulant are written as time-weighted sums of expected instantaneous variance, which are neater and more intuitive than those obtained with the characteristic function approach. Our skewness formula is then applied in calibrating Heston's model by using the market data of the CBOE VIX and SKEW.

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Climate change is one of the most serious threats facing the world today. Environmental pollution and depletion of natural resources have been highlighted by the United Nations Sustainable Development Goals (SDGs), paving the way for modern concepts such as sustainable growth to be introduced. Therefore, this research explores the relationship between green finance, energy efficiency, and CO2 emissions in the G7 countries. The study uses panel data model technique to examine the dependence structure of green finance, energy efficiency, and CO2 emissions. Moreover, we use DEA to construct an energy efficiency index of G7 countries. A specific interval exists between the values of the energy efficiency indexes. Japan, the United Kingdom, and the United States were named the most energy-efficient countries in the world, based on results obtained for five consecutive years in this category. However, according to the comparative rankings, France and Italy are the most successful of all the G7 members, followed by the United Kingdom and Germany. Our overall findings of the econometric model confirm the negative impact of green finance and energy efficiency on CO2 emissions; however, this relationship varies across the different quantiles of the two variables. The findings in the study confirm that green finance is the best financial strategy for reducing CO2 emissions.

In this research, we analyzed green finance, small and medium-sized businesses, and financial literacy in China to boost the green economy. Green finance and financial literacy were examined holistically using a rigorous empirical approach and data envelopment analysis to provide the way to advance green economic recovery in this research. According to empirical evidence, green financing impacts SMEs at 0.31, 0.41, and 2.02 on green economic recovery. China’s green finance and small businesses contribute significantly to the country’s overall green economic revival. A more accurate forecast of green economic recovery was made possible by including other variables such as population expansion, development, and small business development. The analysis used the data envelopment analysis, and the results were solid. Additional hypothetical time-dependent instances demonstrated China’s predicted green financing and small business’s nexus for 2000 to 2020. The proportion of SMEs is decreasing, and as a result, green financing and financial literacy have increased by an average of 12.5% during this time. China’s green financing would fall dramatically if the country’s industrial structure is reduced. According to our findings, financial literacy is positively correlated with green economic recovery, while illiteracy is negatively correlated with growth. Finally, the report provides some ideas for China’s future green economic recovery.