高新技术企业投资价值评估研究
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摘要
二十一世纪是知识经济为主导的时代,而知识经济的支柱是高新技术产业,高新技术正逐步成为推动当代经济社会发展的决定力量,各国、各地区都在不断加强对高新技术企业的扶持力度,竞相通过制定和实施相关政策为新兴的高新技术企业提供良好的发展空间和条件。而高新技术企业与传统企业最大的区别就在于其研发(R&D)投入大、拥有潜在的高收益和知识的高度密集性,因此,这类企业需要有较多的研发经费投入和高学历人才的投入。从投资者的角度来看,高新技术企业是一类极具发展潜力的企业,但在期望收益的背后也可能存在较大的风险,而真正能实现将科研技术成果规模化、产业化的企业并不多,那么如何从中选择科技含量高、收益好、发展潜力大的高新技术企业,则成为投资者在进行投资决策时的一个难题。虽然国内外有关专家学者在理论和实证研究中都提出了不少企业价值评估的模型,但对评估高新技术企业尤其是成长性高新技术企业投资价值的模型并没有给予太多的关注和重视。因此,本文选择高新技术企业投资价值作为研究对象,在理论和实践上都具有重要的意义。
本文在国家大力推进自主创新能力提升和我省着力构建合芜蚌自主创新综合配套改革试验区的大背景下,通过理论研究、算例分析相结合的方法深入研究了高新技术企业的投资价值评估问题。在研究的过程中,一方面以实证研究为依托,运用“衰退系数法”对定量指标进行处理,进而结合定性指标采用基于证据理论的评估模型对成长性高新技术企业的投资价值进行比较排序,以便选取具有投资价值的高新技术企业;另一方面,在传统理论的基础上建立了基于资产组合法的高新技术企业投资价值评估模型,并通过算例分析验证了模型的实用性和可行性。本文的主要研究内容和创新成果如下:
(1)本文通过将高新技术企业和传统企业进行比较,分析了高新技术企业的主要特征,在大量调研的基础上,建立了较为全面的高新技术企业投资价值优劣排序指标体系。文章在对定量指标进行分析时,认为不同历史时期的数据对未来的预测能力是不一样的,即历史越长的数据预测能力越差,因此对定量指标引入“衰退系数法”进行预处理。在对D-S证据理论充分理解的基础上建立了基于期望报酬的高新技术企业投资价值优劣排序模型,并将该模型应用于安徽省信息技术企业中的成长性高新技术企业投资价值大小的排序,从而实现对具有较高投资价值企业的初选。
(2)本文在哈里·马克威茨(Markowitz)等人创立的“均值——方差组合模型”理论的基础上,引入资产组合概念对高新技术企业的价值评估问题进行建模。文章具体分析了资产组合模式对企业绩效及投资价值的作用及影响,将资产结构的合理性作为评估企业投资价值的重要依据,通过确定出最佳的资产组合模式来测算各个高新技术企业的投资价值。在这一研究过程中,本文构建了有效资产组合和非有效资产组合下的高新技术企业价值评估模型,并通过具体的算例分析,验证了基于资产组合法的高新技术企业价值评估模型在评估成长性高新技术企业中的可行性。
(3)充分考虑到高新技术企业研发投入高、知识高度密集的产业特点,将R&D费用计入收益率的计算中,同时在对高新技术企业资产进行分类的过程中,不仅仅从传统的流动资产和固定资产的组合角度进行考虑,并将无形资产和R&D费用之和计为知识资产,从知识资产、营运资产、固定资产、其他资产四个方面来计量高新技术企业的有效资产组合结构。
文章的研究成果在一定程度上解决了成长性高新技术企业投资的选取问题以及成长性高新技术企业投资价值的评估建模问题,为进行高新技术企业的投资决策实践提供了更加广阔的空间,也为企业价值评估理论研究开创了一个崭新的研究视角。
New high and technology industry,a pivotal industry of the knowledge economy, has gradually become the determinants to promote the contemporary economic and social development in the twenty-first century characterized by knowledge-dominated economy. Countries and regions all over the world are constantly strengthening the support for high-tech enterprises, providing much room for newly emerged high-tech enterprises by formulating related policies and putting them to practice. What distinguishes high-tech enterprises from traditional enterprises lies in its high degree of R&D inputting, potential investment income and knowledge intensity. So these enterprises require more funding for R&D and the input of highly educated talents. From the investors’perspective, high-tech enterprises have great potentials, but there exist great risks behind their expectations of proceeds. In practice, few enterprises are in a position to scale the results of research in science and technology and to industrialize them. Therefore, how to select new high-tech enterprises with good earnings and great potentials has become investors’top priority when they make decisions in investment. Although experts and scholars at home and abroad have constructed a number of models to assess enterprise value in their theoretical and empirical studies, they didn’t attach great importance to the assessment of new high-tech enterprises; especially the growing new high-tech enterprises. Therefore, it is of great significance to conduct research on the investment value of the high-tech enterprises both in theory and practice.
This dissertation studied the investment valuation of new high-tech enterprises in-depth by combining theoretical research, empirical research with case study in the situation that China enhanced the capability of independent innovation vigorously and ANHUI focused on the construction of a comprehensive reform pilot area in the following three cities of Hefei, Wuhu and Bengbu characterized by independent innovation.
In the study, the dissertation handled quantitative indicators by resorting to Decaying Coefficient Method, and ranked the investment value of growing high-tech enterprises in order to select new high-tech enterprises of the higher investment value by using the valuation model based on the evidence theory for the qualitative indicators. On the other hand, this dissertation constructed a valuation model of new high-tech enterprises based on the traditional portfolio method together with the improved relative value method. On these bases, the applicability and feasibility of the above two methods and models was authenticated by a case study. The main research and innovations are as follows.
(1) This dissertation analyzed the main features of new high-tech enterprises by comparing high-tech enterprises with traditional ones. Based on a large number of field research, a relatively comprehensive evaluation index system suitable to the high-tech enterprises was established, and the model to rank the investment value of new high-tech enterprises based on expected benefits was constructed on the full understanding of DS evidence theory. Then the mentioned model was applied to rank the growing new high-tech enterprises of Anhui information technology enterprises in order to complete preliminary selection of the enterprises with good investment value.
(2) The model to assess the value of new high-tech enterprises was constructed by introducing the concept of portfolio on the basis of the modern portfolio theory proposed by Hariri Markowitz——“Mean-Variance Model”. The dissertation analyzed the function and impact of asset structure on corporate performance and investment value in detail, and the reasonableness of asset structure was considered an important criterion for assessing the corporate investment value. The investment value of various new high-tech enterprises was estimated by determining the optimal portfolio mode. In the study, this dissertation built an evaluation model to assess the value of new high-tech enterprises based on effective portfolio and non-effective portfolio. The model used to assess growing new high-tech enterprises whose valuation earnings are positive was verified through a specific case study.
(3) The traditional enterprise valuation model based on the relative value method was discussed and analyzed and the limitations of valuating the investment value of new high-tech enterprises by using the traditional method were also identified. On these bases, the improved model was proposed, including the improved earnings model, the improved net earnings model, and the improved income multiplier model. The three improved model, a supplement and perfection of the traditional enterprise valuation model based on portfolio, considered the heavy investment in R & D for new high-tech enterprises, providing a good method to assess investment value of new high-tech enterprises whose yields are negative. In addition, the above improved model was verified by a specific case and the validity of the model used to valuate growing new high-tech enterprises whose yields are negative from a practical point of view.
The research in this dissertation helps to solve the investment problem of selecting growing new high-tech enterprises to a certain extent, as well as the valuation modeling of growing new high-tech enterprises, providing much more room for the investment decision-making of new high-tech enterprises and creating a new perspective for the theoretical research of enterprise valuation.
本文在国家大力推进自主创新能力提升和我省着力构建合芜蚌自主创新综合配套改革试验区的大背景下,通过理论研究、算例分析相结合的方法深入研究了高新技术企业的投资价值评估问题。在研究的过程中,一方面以实证研究为依托,运用“衰退系数法”对定量指标进行处理,进而结合定性指标采用基于证据理论的评估模型对成长性高新技术企业的投资价值进行比较排序,以便选取具有投资价值的高新技术企业;另一方面,在传统理论的基础上建立了基于资产组合法的高新技术企业投资价值评估模型,并通过算例分析验证了模型的实用性和可行性。本文的主要研究内容和创新成果如下:
(1)本文通过将高新技术企业和传统企业进行比较,分析了高新技术企业的主要特征,在大量调研的基础上,建立了较为全面的高新技术企业投资价值优劣排序指标体系。文章在对定量指标进行分析时,认为不同历史时期的数据对未来的预测能力是不一样的,即历史越长的数据预测能力越差,因此对定量指标引入“衰退系数法”进行预处理。在对D-S证据理论充分理解的基础上建立了基于期望报酬的高新技术企业投资价值优劣排序模型,并将该模型应用于安徽省信息技术企业中的成长性高新技术企业投资价值大小的排序,从而实现对具有较高投资价值企业的初选。
(2)本文在哈里·马克威茨(Markowitz)等人创立的“均值——方差组合模型”理论的基础上,引入资产组合概念对高新技术企业的价值评估问题进行建模。文章具体分析了资产组合模式对企业绩效及投资价值的作用及影响,将资产结构的合理性作为评估企业投资价值的重要依据,通过确定出最佳的资产组合模式来测算各个高新技术企业的投资价值。在这一研究过程中,本文构建了有效资产组合和非有效资产组合下的高新技术企业价值评估模型,并通过具体的算例分析,验证了基于资产组合法的高新技术企业价值评估模型在评估成长性高新技术企业中的可行性。
(3)充分考虑到高新技术企业研发投入高、知识高度密集的产业特点,将R&D费用计入收益率的计算中,同时在对高新技术企业资产进行分类的过程中,不仅仅从传统的流动资产和固定资产的组合角度进行考虑,并将无形资产和R&D费用之和计为知识资产,从知识资产、营运资产、固定资产、其他资产四个方面来计量高新技术企业的有效资产组合结构。
文章的研究成果在一定程度上解决了成长性高新技术企业投资的选取问题以及成长性高新技术企业投资价值的评估建模问题,为进行高新技术企业的投资决策实践提供了更加广阔的空间,也为企业价值评估理论研究开创了一个崭新的研究视角。
New high and technology industry,a pivotal industry of the knowledge economy, has gradually become the determinants to promote the contemporary economic and social development in the twenty-first century characterized by knowledge-dominated economy. Countries and regions all over the world are constantly strengthening the support for high-tech enterprises, providing much room for newly emerged high-tech enterprises by formulating related policies and putting them to practice. What distinguishes high-tech enterprises from traditional enterprises lies in its high degree of R&D inputting, potential investment income and knowledge intensity. So these enterprises require more funding for R&D and the input of highly educated talents. From the investors’perspective, high-tech enterprises have great potentials, but there exist great risks behind their expectations of proceeds. In practice, few enterprises are in a position to scale the results of research in science and technology and to industrialize them. Therefore, how to select new high-tech enterprises with good earnings and great potentials has become investors’top priority when they make decisions in investment. Although experts and scholars at home and abroad have constructed a number of models to assess enterprise value in their theoretical and empirical studies, they didn’t attach great importance to the assessment of new high-tech enterprises; especially the growing new high-tech enterprises. Therefore, it is of great significance to conduct research on the investment value of the high-tech enterprises both in theory and practice.
This dissertation studied the investment valuation of new high-tech enterprises in-depth by combining theoretical research, empirical research with case study in the situation that China enhanced the capability of independent innovation vigorously and ANHUI focused on the construction of a comprehensive reform pilot area in the following three cities of Hefei, Wuhu and Bengbu characterized by independent innovation.
In the study, the dissertation handled quantitative indicators by resorting to Decaying Coefficient Method, and ranked the investment value of growing high-tech enterprises in order to select new high-tech enterprises of the higher investment value by using the valuation model based on the evidence theory for the qualitative indicators. On the other hand, this dissertation constructed a valuation model of new high-tech enterprises based on the traditional portfolio method together with the improved relative value method. On these bases, the applicability and feasibility of the above two methods and models was authenticated by a case study. The main research and innovations are as follows.
(1) This dissertation analyzed the main features of new high-tech enterprises by comparing high-tech enterprises with traditional ones. Based on a large number of field research, a relatively comprehensive evaluation index system suitable to the high-tech enterprises was established, and the model to rank the investment value of new high-tech enterprises based on expected benefits was constructed on the full understanding of DS evidence theory. Then the mentioned model was applied to rank the growing new high-tech enterprises of Anhui information technology enterprises in order to complete preliminary selection of the enterprises with good investment value.
(2) The model to assess the value of new high-tech enterprises was constructed by introducing the concept of portfolio on the basis of the modern portfolio theory proposed by Hariri Markowitz——“Mean-Variance Model”. The dissertation analyzed the function and impact of asset structure on corporate performance and investment value in detail, and the reasonableness of asset structure was considered an important criterion for assessing the corporate investment value. The investment value of various new high-tech enterprises was estimated by determining the optimal portfolio mode. In the study, this dissertation built an evaluation model to assess the value of new high-tech enterprises based on effective portfolio and non-effective portfolio. The model used to assess growing new high-tech enterprises whose valuation earnings are positive was verified through a specific case study.
(3) The traditional enterprise valuation model based on the relative value method was discussed and analyzed and the limitations of valuating the investment value of new high-tech enterprises by using the traditional method were also identified. On these bases, the improved model was proposed, including the improved earnings model, the improved net earnings model, and the improved income multiplier model. The three improved model, a supplement and perfection of the traditional enterprise valuation model based on portfolio, considered the heavy investment in R & D for new high-tech enterprises, providing a good method to assess investment value of new high-tech enterprises whose yields are negative. In addition, the above improved model was verified by a specific case and the validity of the model used to valuate growing new high-tech enterprises whose yields are negative from a practical point of view.
The research in this dissertation helps to solve the investment problem of selecting growing new high-tech enterprises to a certain extent, as well as the valuation modeling of growing new high-tech enterprises, providing much more room for the investment decision-making of new high-tech enterprises and creating a new perspective for the theoretical research of enterprise valuation.
引文
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