Abstracts: Based on the theoretical analysis of the influence of green credit on the optimization of industrial structure through capital formation, capital orientation, information transmission, industrial integration and risk distribution mechanism, this paper uses the grey correlation model to make an empirical analysis,and analyze the correlation between green credit and industrial structure optimization.The results show that green credit has the highest correlation with the tertiary industry, the secondary industry takes the second place, and the primary industry is the lowest.Then we select the provincial panel data of China from 2004 to 2017 for regression analysis. At the same time, we do empirical research on Regional Panel and staged panel, and conclude that green credit can promote industrial structure optimization to a certain extent, but the impact is limited.Finally, the government and financial supervision departments, banks and other financial institutions proposed suggestions to promote the effective effect of green credit on the optimization of industrial structure.
Key words: green finance; green credit; industrial structure optimization; influence mechanism; grey correlation analysis
Abstract: In recent years, it is reasonable to develop rapidly for financial majors in Chinese universities from the point of view of the history of financial development and individual rationality, but it is also necessary to deeply understand the direction of financial majors development from the perspective of financial nature and the trend of financial cross-border transformation. From the perspective of macro “financial intensity” and from the perspective of the development of the “science and technology finance” industry, we should understand that the characteristics of “rapid iteration”, “timely service” and “flat organization” of new finance are urgent for the complex talents of science and technology. We should empower the financial professional development, so as to better guide the development of financial majors in colleges and universities.
Key words: financial education; the nature of finance; the finance of science and technology; transfrontier and transformation of finance;financial specialty; financial talents; securities business; financial intensity
Abstract：The current financial network empirical research few concern risks associated with institutional predicament，but the systemic risk in reality is often transmitted through such an extreme case. Based on the data of listed financial institutions from 2008 to 2017, a directed weighted network is established with the extreme risk spillover ability among institutions. The trend of dynamic risk correlation among financial industries in China is analyzed, and the key financial institution nodes are identified with network indicators. The results show that the risk spillover network has a better description of extreme financial events, and the extreme risk correlation level of institutions is higher during the crisis. China’s financial risk declined in 2017. The bank institution nodes have strong risk spillover properties, and the securities institutions are more vulnerable to the risk of other network nodes. The key nodes of risk spillovers in the network are changing from the early state-owned commercial banks to the securities industry.
Abstract: Internet finance provides a large number of low-cost and convenient financial services for rural areas, agriculture and farmers because of its cross-regional, cross-market and cross-business nature, but its mixed business management model is not suitable for sub-industry supervision. Therefore, it is necessary to develop a coordinated regulatory model for joint development of financial regulatory policies, sharing of information, and joint enforcement of laws and regulations by multiple sectors, so as to strengthen the comprehensive nature of regulation to create a sound business environment, achieve transparent governance of financial risks, and address regulatory gaps and overlaps. Promote Internet finance to better serve rural revitalization strategy.
Key words: rural finance; rural revitalization; collaborative regulation; internet finance
Abstract: In this paper, we decompose the earning of companies into systematic component and unsystematic component, and define the unsystematic part as so-called idiosyncratic earning. In further investigation, we take the idiosyncratic earning as an effective indicator of distinguishing good companies from bad companies, and systematically study the relationship between it and stock return. Our results show that: (1) The growth rate of earning of companies, similar to the stock return, is affected by some common exogenous factors, which means it can be decomposed into systematic component and unsystematic component; (2) There is significantly positive relationship between firm idiosyncratic earning and stock return; (3) It can obtain significantly risk-adjusted excess return by buying and holding those stocks with high idiosyncratic earning; (4)Based on the information implied by firm idiosyncratic earning, we propose an enhanced reversal strategy, the portfolio return of which significantly outperforms than traditional reversal strategy, through going long on stocks with high idiosyncratic earning and low historical return, and going short on stocks with low idiosyncratic earning and high historical return.