【作者】 王鹏；

【导师】 陈晓红；

【作者基本信息】 中南大学 ， 管理科学与工程， 2010， 博士

【摘要】 进入21世纪以来,高新技术企业迅速发展,在我国更是成为推动经济发展的主要力量之一。风险投资作为高新技术企业发展的重要资金来源,如何提高其投资效率,优化资源配置成为国内外热点研究问题。本文从风险投资视角出发,探讨风险企业的价值、投资风险与投资组合决策,既能提高风险投资机构的投资决策水平,又能引导我国风险企业良性发展,具有重要意义。本文在回顾风险投资、企业价值、投资价值来源等理论的基础上,对风险投资视角下的投资价值进行了界定。从风险投资机构关注的投资额度、投资回报、投资风险、回报时间四个方面出发,结合不同的风险投资者的资金实力、投资偏好等,提出了投资价值的相对性概念,给出了高新技术企业投资价值构成公式,讨论了公式涉及的四个函数的基本特征,为风险投资者确定投资价值提供了新的思路。为提高风险投资机构的投资效率,本文以高新技术企业投资价值的构成公式为依据,设计了以基本数据库、主要功能模块、算法库为主要构成单元的风险投资决策支持体系。该决策支持体系具备风险企业投资价值判断功能、风险企业投资风险的评价功能以及提供风险投资组合决策的功能。本文利用模糊理论,着重讨论了三个功能的实现：(1)决策支持体系中的企业价值评估模块是各种资产定价方法集合,由于风险投资者在决策过程中,对项目价值、项目投资额度存在模糊性,本文引入正态模糊集进行刻画,在推导了正态模糊集的运算法则的基础上,建立了单个增长期权的模糊实物期权定价模型、复合期权的模糊实物期权定价模型和多阶段复合期权的模糊实物期权定价模型,给出了各个模糊实物期权定价的公式。通过实际投资案例说明了风险投资者可以通过模糊实物期权定价方法加入自身对项目的模糊认识,对项目投资价值进行判断。(2)投资风险评估模块的功能是对某个高新技术企业投资风险的综合评价,本文讨论了风险投资的风险构成,建立了风险评价流程,设计了市场风险、技术风险、财务风险、管理风险、信用风险、金融风险和退出风险七类风险评价指标体系,采用隔栅获取和模糊Borda数方法确定了各级各评价指标的权重。为最大挖掘专家打分信息,根据设定的风险级别,建立了白化函数,运用模糊灰关联的方法,给出了风险等级的综合评分。(3)风险投资组合模块通过风险企业的投资组合来降低风险投资机构的整体风险,本文以多位专家对多个指标的区间打分为收益,各指标打分的协方差为风险,建立了风险投资组合模糊决策模型,得到了风险投资组合收益与风险的区间数,讨论了不同风险偏好下的最优投资决策,应用实例表明该模型能起到较好的风险分散作用。更多还原

【Abstract】 High-tech enterprises developed rapidly since 2000 in china, especially it has become one of the major forces promoting China’s economic development. Venture capital is an important source of funds for high-tech enterprise, how to improve the efficiency of investing and optimize the allocation of resources becomes a heat issue of studies domestic and internationally. From the perspective of venture capital, this dissertation discussed the value of the venture business, investment risk and portfolio decisions, which of great significance.It could both improve the venture capital investment decision-making and guide the healthy development of China venture business.This dissertation reviewed the theories of corporate value, venture capital and sources of investment value, after that the investment value in the venture capital perspective was defined. Concerning investment amount, investment returns, investment risk, and times, which the venture capital institutions pay the most attention, this dissertation proposed the concept of investment value according to the financial strength of different investors, investment preferences, and gave the formula of high-tech business investment value, and discussed the basic characteristics of the four functions, provided ventrue investors with new ideals of determining investment value.To improve venture capital institutions’efficiency of investing, based on the formula of high-tech business investment value, this dissertation designed the venture investment decision support system, which includes basic databases, major functional blocks and algorithms library. Through the venture investment decision support system, investors could estimate the investment value of venture business, evaluate the investment risk of venture business and select the venture investment portfolio. By using fuzzy theory, the core of the three main modules were discussed.(1) The enterprise evaluation module was a collection of various methods of asset pricing. As venture investors was uncertain about the project value and the amount of investment when making decision, this dissertation used normal fuzzy sets to improve the real options, after derivate the operations of normal fuzzy sets, we proposed single growth fuzzy real option model, compound fuzzy real option and multi-stage compound fuzzy real option. Further more, we solved these models and gave an example, which illustrated that the venture investors can get a fuzzy investent value of the venture business by his understanding of the project.(2) In the decision support systems, the function of investment risk assessment module was the comprehensive evaluation of investment risk. This dissertation disscussed the risk of venture investment and the risk assessment process design. Constructed the evaluation index system which reflected the market risk, technical risk, financial exposure, management risk, credit risks, financial risk and risk of resignation. Grid and fuzzy borda number were used to get the weight of each index. To maximizing the use of the information in experts’score, this dissertation set the risk level, and constructed the whitening function, then the fuzzy gray relational method was used to get the risk score.(3) Venture capital institutions could reduce the investment risk by venture investment portfolio. This dissertation views the experts’interval socres on each index as the incomes, and views covariance as the risk, constructed the venture fuzzy investment portfolio model. At last, the interval incomes and risks could be determined from a certain risk appetite, and the best portfolio could also be determined. Example shows that this model could help risk diversification.更多还原