A Study On The Credit Risk Measurement And Loan Portfolio Management Of Startup Enterprises

Start-up enterprises make a great contribution to economic growth and social development. They play as an irreplaceable role in pushing the technology advances, adjusting the industrial structure and increasing the employment. To some extent, the fast economic growth in the past two decades in China benefits from the release of the spirit of start-ups. Along with the continuous progress in system reforms in economy and technology in China, the start-ups, taking the high-tech industry as a representative, have been in vigorous development and become a highlight of economic growth. However, because of their inherent characteristics, like the limit assets at the early stage of the business, the uncertainty of the future development direction, no credit record, high risks and so on, start-ups are facing the difficulties to assess the finance, which to a great extent limits their potential development.With the purpose to build credit risk valuation model applied to venture companies in China, the thesis is specifically focus on them and explore the"best practices"to measure their credit risks, basing on revisit methods, models, and comparison to measure credit risk. And it, in a groundbreaking way, combines the Logit credit rating with investment decision theories to apply credit risk measurement for venture companies in their process of financing. Generally speaking, start-ups use equity financing, debt financing and quasi-equity financing to assess finance. The thesis applies various equity pricing models, including real options, market comparison and cash flow analysis, to resolve the problems of equity financing pricing in different life-cycle stages of start-up enterprises. The thesis uses the risk-adjusted return on equity as a basis for pricing of credit financing; and uses the adjusted Black-Scholes option pricing model on the pricing of the convertible bonds for Chinese start-up enterprises. This study provides theoretical foundation and technical support for the establishment of the credit decision-making system of the credit risk measurement for the start-up enterprises in China.The thesis contains seven chapters. Chapter I is the preface, which introduces the purpose, the significance, the thesis structure and the main innovation points of the research. Chapter II summarizes and analyses the research literature on credit-risk measurements at home and abroad, and on contemporary studies of risk management at different stages of enterprise life cycle. Chapter III studies how to build the credit-risk valuation model that suites the current situation in China. Based on the differences among the business mode, the characteristics and the size of the capital required, this chapter proposes the theory and build the valuation model of credit-risk at different stages of enterprise life cycle. Considering the data availability, Chapter III demonstrates how to evaluate the credit risk of an individual enterprise by using the data of 75 SMEs listed companies in Shenzhen Stock Exchange as the sample. Chapter IV regards the pricing of equity financing, debt financing, and quasi-equity financing for start-ups. Developed from core value and characteristics of venture companies, the chapter compares and evaluates traditional and new pricing methods applied to venture companies and selects practical and precisive models with adjustments to conduct pricing for equity financing, debt financing, and quasi-equity financing separately in starts-up, growth, and mature start-ups. Chapter V investigates loan portfolio management on start-up enterprises. Based on portfolio risk management theories, loan portfolio models can be built for start-up enterprises in different industries and different life-cycle stages by combining the theories of"Credit Risk+"with"0-1 Integer Programming". It would help ease the enterprise financing bottlenecks and decision making in loan approvals by evaluating both risks and returns. Chapter VI presents some packaged policy making suggestions regarding both financing start-up enterprises and portfolio management models, based on analytics of the enterprise credits and the means of financing. Chapter VII concludes the research and analyzes its limitations. It also makes an outlook on further studies of our risk evaluation system for start-up enterprises.There are mainly four innovation points in this thesis.Firstly, it innovatively combines the credit-rating models with the investment decision-making theory, and analyzes the credit-risk measurement of start-up enterprises, which provides significant theoretical reference to developing credit decision system for risk measurement and management on the enterprises.Secondly, it uses a stepwise discriminant analysis method to select discriminant variables from different stages of enterprise lifespan, and measures the credit risk of the enterprises at those points.Thirdly, by carrying out applicability analysis on pricing of enterprise financing, finding pricing models for different stages of enterprise life span, and helping stakeholders to find the right prices for start-up enterprises upon risk measurement.Fourthly, based on current model and principle of optimizing portfolio loans, the characteristics of different stages of enterprise life span, by building a decision making model on optimized portfolio loans, and comparing it with the traditional management in case studies, we proved its validity and applicability.On the other hand, this paper studies the start-up enterprises against their whole life-cycle. Based on their different characteristics at different stages, it evaluates their credit risks, analyzes and discusses possible financing portfolio and provides some subjective opinions on growth of enterprises and their potential value. In the background of keeping consistency with supporting the start-up enterprises, this thesis provides some applicable advices for financial intermediaries, which is also an innovative highlight.In the mean time, the thesis has its own limitations. Firstly, the data in the demonstration analysis came from SME board of Shenzhen Stock Exchange, which is different from their start-up counterparts, along with a very limited sample pool. Secondly, the sample threshold system is limited by data source. Thirdly, the selected demonstration model is limited. Fourthly, we did not consider the impacts brought by macro environment on defaults of credits cycles. Therefore, our next research would involve a greater scope and scale, with improved sample accuracy and capacity, a more systematic indexing mechanism, and employ PROBIT or other models that would better evaluate enterprises at different stages. And, we would incorporate macro-economic and financial environment into our analysis.