Study On The Credit Evaluating Methods Of High-tech SMEs For Venture Capital

With the matchless advantages of the mechanism and efficiency of innovation, High-tech S mall a nd Medium-sized E nterprises ( High-tech S MEs) a re t he m ost remarkable and promising enterprises in recent years. Although the development of high-tech SMEs turns to be dynamic, it is realized that financing problem has become the most universal and crucial restraining factor to be faced with. As one of the most important equity f inancing investors, v enture c apital institutions urgently need t o evaluate the credit of High-tech SMEs as an important basis for investment decisions. Consequently it has theoretical and practical significance to explore the crucial factors and applicable methods of credit evaluation of High-tech SMEs. Unfortunately, the venture capital industry has just started in our country, the venture capital market is still immature, and the academia has not paid enough attention to High-tech SMEs, which lead the research in this area to a standstill.Aiming a t ve nture capital assessment, t hrough l iterature r eview, que stionnaire survey and factor analysis, this article intends to screen the crucial influencing factors of the credit of High-tech SMEs, build the indicator system of the credit evaluation of High-tech S MEs w hich i s t argeting ve nture capital assessment, and explore using different a nd o perational c redit e valuation m ethods t o a ccomplish ve nture capital assessment. T he r esearch r esults a re ex pected t o s upport d ecision-making theoretically f or reducing t ransaction c osts of bot h pa rties i n ve nture capital, expanding the financing channels for High-tech SMEs, and increasing the conversion rate of technology achievements.The research results are summarized as follows:(1) By factor analysis, 5 major categories common factors is extracted:①Credit quality②Organization le vel③Operation l evel④Development l evel⑤Network status, which screens the influencing factors and builds the indicator system for credit evaluation of High-tech SMEs. Eventually the credit evaluation indicator system is designed and established to support investment decision-making for venture capital institutions.(2) Considering the features of venture capital assessment of High-tech SMEs such as complicated conditions, variety of indicators, both qualitative and quantitative indicators, a DEA Fuzzy Comprehensive assessment is proposed: First, process the available history data of quantitative indicators by DEA, output the efficiency value on qua ntitative i ndicators f or e ach e nterprise unde r e valuated, t hen f uzzy the efficiency v alue. For t he qua litative i ndicators with unc ertainty, t he m embership functions are given by experts using fuzzy comprehensive assessment. According to the weight, the comprehensive evaluation is made on all quantitative and qualitative indicators.(3) Considering t he c ondition t hat t he a ttributes w eights a re known, a nd subjective p reference e xists w hen v enture cap ital i nstitutions ev aluate H igh-tech SMEs'credit, by the combination of Interval Number Ranking and Grey Relational Analysis, a cr edit ev aluation method i s proposed i n t he article. T he relations and influences between each credit evaluation indicators are extracted from the interval number de cision m atrix, a nd t he r elation de grees be tween each credit e valuation indicators are quantified by correlation coefficient. Rank High-tech SMEs by Multiple Attribute Decision Making Approach and Grey Relational Analysis, and then provide the suggestion for investment decision.(4) Considering t hat t he r esult of e xisted e valuation m ethods c annot comprehensively r eflect t he f uzziness a nd r andomness of obj ective t hings, cloud models theory is introduced in the research of credit evaluation of High-tech SMEs, aiming at uncertainty, by the idea of membership degree in fuzzy theory, establish the conversion model between qualitative concept and quantitative expression, which is breaking the division limitation of traditional evaluation methods.(5) Considering the advantages of CART such as output tree structure, briefly and directly, processing non-quantitative indicators, a credit evaluation method for High-tech S MEs i s pr oposed, which is b reaking th e limita tion o f r elatively w eak predictive capability of traditional evaluation methods.