Research On Risk Early Warning System Of Venture Capital Project

Over the last 30 years since reform and opening-up,China's economic growth with an average rate of 10%has been impressing.Facing challenge by a slower global economy,more limited access to resources and escalating economic structure,China needs to innovate more to develop in a unique and effective way,which is also in line with its 'New Normal' economy.Through innovating upon the mechanism of investment and financing,venture capital boosts the development of innovative enterprises,technical innovation,economic growth and employment,which makes it an important part of strengthening national competitiveness.It is widely accepted that venture capital mainly flows into innovative enterprises,which face enormous risks in the developing process.Venture capital are expecting high profits with corresponding risks,Thus to prevent and control risks is the top priority,In the process of pursuing higher capital gains,venture capital hightlights to take risks forwardly,which matchs it is the active management of risk,risk early warning.Based on the above analysis,the dissertation seeks to build a complete early warning system within the venture capital institutions.The effectively-operated system is able to sense and track a program's major risks and trends,follow the risks in real time,warn the highly risky programs and take effective strategies to cope with the risks.All these functions above can help to avoid risks or reduce their losses,improve venture capital institutions' overall risk management level and their yield.The effective operation of venture capital can enlarge macroeconomic effect to promote the development of high and new technology,improve the national competitiveness of science and technology,boost long-term economic growth.The dissertation builds a risk warning system of venture capital programs from the perspective of venture capital institutions.The dissertation adopts various descriptive statistical methods including documentation,statistical graph,statistical table,mean value,variance etc.Non-parameter statistical methods were also adopted,including Kruskal-Wallis Test,Median,Wilcoxon Signed Rank Test and so on.It builds econometric models such as ordered choice model,BP neural network early warning model,RBF neural network early warning model,SVM model,etc.It conducts positive analysis of the questionnaire data by Excel,Eviews,SPSS,Matlab.The structure is as follows:The first chapter introduces the background,significance,content and method of the research,and summarizes risk management and early warning of venture capital investments to build the research of this paper.The second chapter introduces the basic concept and law of the early warning system of venture capital investments.It includes the meaning,characteristics and risk of venture capital investments.Based on the understanding of the risk of venture capital investments,the function and pattern of the early warning system of venture capital investments is analyzed,laying a theoretical foundation forf further analysis.The third chapter is the risk information subsystem.This mainly introduces the risk information collection and processing of the early warning system.Based upon the investment process of venture capital investments,this chapter discusses the collection of information,coving various stages of the investment,such as the source of the investment,the evaluation,the assessment and the management.Because risk information comes from different channels and different populations,the risk information is processed to maintain accuracy.Furthermore,this chapter discusses the screening,classification,collation and analysis of information in different fronts,such as research and development,production,marketing,managing and financing.The chapter provides support for risk identification and risk early warning.Chapter 4 and Chapter 5 are risk identification subsystems.On the basis of the collecting and processing risk information,the information is analyzed,and the risk factors of the venture capital investments are systematically combed.On this basis,the early warning index system of the venture capital investment is established.Following the selection principle of the risk early warning index system of venture capital investments,according to the source of the risks,a preliminary set of 42 indexes were chosen for the early warning index system on technical risk,production risk,market risk,management risk,financial risk,environmental risk.The fifth chapter used the rough set theory to optimize the early warning system using 108 venture capital projects to result in 25 risk early warning indexes and the optimization results are quantitatively and qualitatively evaluated by using the ordered choice model,taking into consideration the characteristics of the data of the sample.The results show that the reduction results are reasonable,providing the analytical basis for risk early warning.The sixth chapter is the risk early warning subsystem,which is based on the risk identification subsystem to analyze the investment's risk factors and optimize the main risk index of the response project.It is also to make models to evaluate the risks and effectively controls them by risk response to projects with different risk.This chapter first introduces the theoretical basis of the construction of the risk early warning model,including the method adopted.The chapter also includes the characteristics and applicability of artificial neural network and support vector machine;Classification of Alert.Finally,the BP neural network early warning model,the RBF neural network early warning model and the nonlinear support vector machine early warning model of the venture capital investments are established and an empirical analysis of them is carried out.Chapter 7 is the risk respond subsystem.That is,through the early warning subsystem's forecast,taking precautions in a moderate-or high-risk investment,to take effective measures to prevent or reduce the occurrence of the risk,or,through ample preparations minimizing the loss.This chapter first introduces the response strategies for venture capital investments;then discusses the response plans for low-,moderate-,and high-risk investments,respectively.Finally,it discuss the decision-making of suspending the investment.The eighth chapter is the support system for the early warning system,that is,to ensure the effective operation of the early warning system,build a control environment within the venture capital investor.It includes cultural,organizational and system building.The ninth chapter talks about the conclusion and the prospect,summarizing the research and innovation of this article,and looks into the direction of future research.This innovation mainly covers four aspects:First,regarding the venture capital project,complete risk early warning system has been established in the investment process to provide new ideas for active risk management of venture capital institutions.The risk early warning system of venture capital project could be used for project risk assessment and early-warning during the selection,evaluation and management of venture capital project.It helps to fold risk elements which may cause losses in advance,and preventive measures could be taken.Risk early warning system includes risk information subsystem,risk indentification subsystem,risk warning subsystem and risk response subsystem.Risk information subsystem is used for the risk information collection,processing and analysis.Risk identification subsystem identifies the main risk factors which affect the project operation,and constructs risk early-warning index system.Risk warning subsystem,is to predict project's risk state through setting up risk early-warning model.Risk response subsystem,is to take appropriate strategies in order to eliminate or control risks.Risk early warning system is a dynamic system,to provide the feedback of risk control results to all systems in time,so that the system could adjust itself dynamically to adapt to the project's risk state.Second,risk early-warning index system is optimized by rough sets,and optimization results are quantitatively evaluated by ordered choice model.Through the risk of venture capital project is uncertain,incomplete,inconsistent,and rough sets can deal with incomplete information without any prior information,selecting rough sets to optimize risk early-warning index system,and collecting project risk data with questionnaire data,25 risk early warning factors which affect venture capital project's operation finally be concluded and the result of ordered choice model shows the index system is reasonable.Third,three risk-warning models in venture capital project are established,by using BP neural network,RBF neural network and nonlinear support vector machine.The models are analyzed and tested by questionnaire data,which provide new thought for risk early-warning research of venture capital project.Fourth,in order to ensure the normal operation of risk early-warning system,the control environment of risk early-warning system is suggested to be established in internal institutions,which should cover three aspects including enterprise risk culture,early-warning management organization construction,and early-warning management system design.