According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifu...According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifurcation of the system based on Hopf bifurcation theory of nonlinear dynamic systems.In order to make the system＇s chaos disappear,we select the feedback gain matrix to design a class of chaotic controller.Numerical simulations are performed to reveal the change process of financial market risk.It is shown that,when the parameter of risk transmission rate changes,the system gradually comes into chaos from the asymptotically stable state through bifurcation.The controller can then control the chaos effectively.展开更多
China’s top financial regulators have warned about risks in complicated financial products and banks’off-balance sheet business,in a bid to prevent cross-market risk contagion,according to senior officials recently.
As technology and the internet develop,more data are generated every day.These data are in large sizes,high dimensions,and complex structures.The combination of these three features is the“Big Data”[1].Big data is r...As technology and the internet develop,more data are generated every day.These data are in large sizes,high dimensions,and complex structures.The combination of these three features is the“Big Data”[1].Big data is revolutionizing all industries,bringing colossal impacts to them[2].Many researchers have pointed out the huge impact that big data can have on our daily lives[3].We can utilize the information we obtain and help us make decisions.Also,the conclusions we drew from the big data we analyzed can be used as a prediction for the future,helping us to make more accurate and benign decisions earlier than others.If we apply these technics in finance,for example,in stock,we can get detailed information for stocks.Moreover,we can use the analyzed data to predict certain stocks.This can help people decide whether to buy a stock or not by providing predicted data for people at a certain convincing level,helping to protect them from potential losses.展开更多
With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal...With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal industry in A-share market from 1995 to 2007. Empirical results show that Year-Based price index of coal price has a negative correlation with the financial risk but has no significance, and coal chain price has a significant negative correlation with the financial risk. Further research indicates that enterprises increase bad investment, and a lot of debts caused by short-term rise in coal prices. The results also show that the financial risk in the coal industry declines with the rise of GDP growth rate and increases with the rise of inflation rate.展开更多
Nowadays, a shortage of funds has evolved into general business issues because raise the necessary funds is the necessary requirement to develop and expand the companies’ scale. The funding would have to face all kin...Nowadays, a shortage of funds has evolved into general business issues because raise the necessary funds is the necessary requirement to develop and expand the companies’ scale. The funding would have to face all kinds of risks associated. Although funding risk cannot be completely eliminated, but the company can be based on their own development needs, and actively respond to risk fi nancing based on their own conditions. In this paper, the business fi nancing risk coping strategies is presented based on analysis of the reasons of business fi nancing risk.展开更多
In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying b...In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying big data technology in Internet finance,including its basic concepts,characteristics,and current state of development in the field.It examines the current situation and primary challenges faced by financial management in Internet financial enterprises,such as risk management,cost control,and data integration.To address these challenges,optimization strategies based on big data are proposed,focusing on areas such as risk control and cost optimization.By constructing a financial data analysis model,this study provides an in-depth analysis of relevant data,demonstrating the role of big data technology in improving financial management.Finally,through a case study,the effectiveness of big data applications in financial management is verified,and future development directions are discussed.展开更多
For discrete time case a characterization of locally risk-minimizing strategies is given. Based on this characterization, it is evident that risk-minimizing strategies must be locally risk-minimizing.
In the last two decades,Internet technologies,such as cloud computing,mobile communications,social media,and big data analytics,have brought tremendous changes to our society and reshaped the business in various indus...In the last two decades,Internet technologies,such as cloud computing,mobile communications,social media,and big data analytics,have brought tremendous changes to our society and reshaped the business in various industries.Specifically,the mushrooming innovations in the financial area fertilized by information and communication technologies indicates the advent of the Internet finance era.Applying the exploratory research approach,we investigate major innovative Internet-based financial services and classify them into five categories,as of e-commerce,e-payment,e-money market,online loan services,and digital currencies.Then we propose a market structure of Internet finance extended from the traditional financial market.We claim that credit management is the key issue in the marketplace of Internet finance,characterized by big data analytics,in which cyber credit appears as whole-process,multi-dimensional,and holographic.We further suggest that cyber credit be represented in the form of vector to overcome the limits of traditional single-value measure in cyber credit management.Based on this framework,we raise main research issues in Internet finance from the perspectives of theory,technology,and governance.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 70271068)
文摘According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifurcation of the system based on Hopf bifurcation theory of nonlinear dynamic systems.In order to make the system＇s chaos disappear,we select the feedback gain matrix to design a class of chaotic controller.Numerical simulations are performed to reveal the change process of financial market risk.It is shown that,when the parameter of risk transmission rate changes,the system gradually comes into chaos from the asymptotically stable state through bifurcation.The controller can then control the chaos effectively.
文摘China’s top financial regulators have warned about risks in complicated financial products and banks’off-balance sheet business,in a bid to prevent cross-market risk contagion,according to senior officials recently.
文摘As technology and the internet develop,more data are generated every day.These data are in large sizes,high dimensions,and complex structures.The combination of these three features is the“Big Data”[1].Big data is revolutionizing all industries,bringing colossal impacts to them[2].Many researchers have pointed out the huge impact that big data can have on our daily lives[3].We can utilize the information we obtain and help us make decisions.Also,the conclusions we drew from the big data we analyzed can be used as a prediction for the future,helping us to make more accurate and benign decisions earlier than others.If we apply these technics in finance,for example,in stock,we can get detailed information for stocks.Moreover,we can use the analyzed data to predict certain stocks.This can help people decide whether to buy a stock or not by providing predicted data for people at a certain convincing level,helping to protect them from potential losses.
文摘With the rise of coal price, the proportion of loss-making enterprises shows an upward trend in China＇s coal industry. This paper uses Altman Z-Score model to measure financial risk of 19 listed companies in the coal industry in A-share market from 1995 to 2007. Empirical results show that Year-Based price index of coal price has a negative correlation with the financial risk but has no significance, and coal chain price has a significant negative correlation with the financial risk. Further research indicates that enterprises increase bad investment, and a lot of debts caused by short-term rise in coal prices. The results also show that the financial risk in the coal industry declines with the rise of GDP growth rate and increases with the rise of inflation rate.
文摘Nowadays, a shortage of funds has evolved into general business issues because raise the necessary funds is the necessary requirement to develop and expand the companies’ scale. The funding would have to face all kinds of risks associated. Although funding risk cannot be completely eliminated, but the company can be based on their own development needs, and actively respond to risk fi nancing based on their own conditions. In this paper, the business fi nancing risk coping strategies is presented based on analysis of the reasons of business fi nancing risk.
文摘In the context of the rapid development of big data technology,the financial management model of Internet financial enterprises is undergoing a profound transformation.This paper analyzes the key aspects of applying big data technology in Internet finance,including its basic concepts,characteristics,and current state of development in the field.It examines the current situation and primary challenges faced by financial management in Internet financial enterprises,such as risk management,cost control,and data integration.To address these challenges,optimization strategies based on big data are proposed,focusing on areas such as risk control and cost optimization.By constructing a financial data analysis model,this study provides an in-depth analysis of relevant data,demonstrating the role of big data technology in improving financial management.Finally,through a case study,the effectiveness of big data applications in financial management is verified,and future development directions are discussed.
文摘For discrete time case a characterization of locally risk-minimizing strategies is given. Based on this characterization, it is evident that risk-minimizing strategies must be locally risk-minimizing.
文摘In the last two decades,Internet technologies,such as cloud computing,mobile communications,social media,and big data analytics,have brought tremendous changes to our society and reshaped the business in various industries.Specifically,the mushrooming innovations in the financial area fertilized by information and communication technologies indicates the advent of the Internet finance era.Applying the exploratory research approach,we investigate major innovative Internet-based financial services and classify them into five categories,as of e-commerce,e-payment,e-money market,online loan services,and digital currencies.Then we propose a market structure of Internet finance extended from the traditional financial market.We claim that credit management is the key issue in the marketplace of Internet finance,characterized by big data analytics,in which cyber credit appears as whole-process,multi-dimensional,and holographic.We further suggest that cyber credit be represented in the form of vector to overcome the limits of traditional single-value measure in cyber credit management.Based on this framework,we raise main research issues in Internet finance from the perspectives of theory,technology,and governance.
