基于改进实物期权模型的新能源上市企业价值评估研究

发布时间：2018-03-17 08:01

本文选题：新能源　切入点：上市公司　出处：《燕山大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着经济的快速发展，传统能源日益短缺，开发和利用新能源作为国家实现可持续发展的一项战略举措，越来越受到国家的重视。新能源上市公司是开发、生产和销售新能源产品并在证券市场公开交易的上市企业，如何准确合理的评估其企业价值，已经成为政府、投资者和社会公众关注的焦点。新能源企业经营面临的高度不确定性，使得企业管理者的决策具有灵活性，这种柔性管理价值就是实物期权的价值。传统的价值评估方法不能评价企业拥有的未来投资机会的价值，即忽略了企业的实物期权价值。本文运用遗传算法优化的人工神经网络，，对实物期权中的B-S模型进行改进，旨在建立一种能更加全面准确的评估新能源上市公司企业价值的方法。首先，在对国内外研究现状进行综述的基础上，介绍了传统企业价值评估的方法，并对实物期权理论进行了详细的阐述。其次，分析了新能源上市公司的特点和价值评估环境以及其拥有的实物期权的类型，并分析了传统企业价值评估方法在评估新能源上市企业价值时存在的不足以及运用实物期权评估其企业价值存在的优势。再次，B-S模型虽具有一定的缺陷，但是它提供了影响企业价值的五个参数，将这五个参数作为BP神经网络的输入变量，通过遗传算法确定网络最优权值，建立评估新能源上市公司企业价值的改进的实物期权模型。最后，选取新能源板块典型的上市公司进行实证研究，将运用改进实物期权模型计算的股权价值与运用B-S模型计算的结果分别与实际值进行比较，验证了改进模型的准确性。进一步利用改进模型得到的股权价值计算股价，将其与实际的平均收盘价进行比较，有助于判断股价的未来变动趋势，帮助投资者做出正确的投资决策。另外，通过对样本公司的五个参数进行敏感性分析，找出影响企业价值的关键因素，从而对管理者如何提升企业价值提出合理建议。
[Abstract]:With the rapid development of economy and the shortage of traditional energy, the development and utilization of new energy, as a strategic measure to realize the sustainable development of our country, has been paid more and more attention by the country. How to accurately and reasonably evaluate the value of listed enterprises that produce and sell new energy products and trade them publicly in the stock market has become the focus of attention of the government, investors and the public. The high degree of uncertainty in the operation of new energy enterprises makes the decision-making of enterprise managers flexible. This flexible management value is the value of real options. Traditional valuation methods cannot evaluate the value of future investment opportunities owned by an enterprise. In this paper, the B-S model of real options is improved by using artificial neural network optimized by genetic algorithm. Aim to establish a more comprehensive and accurate evaluation of the value of listed companies of new energy. First of all, on the basis of summarizing the current research situation at home and abroad, this paper introduces the traditional methods of enterprise value evaluation, and expounds the theory of real options in detail. Secondly, it analyzes the characteristics and valuation environment of new energy listed companies and the types of real options they have. This paper also analyzes the shortcomings of traditional valuation methods in evaluating the value of listed enterprises in new energy sources and the advantages of using real options to evaluate the value of listed enterprises. Again, the B-S model has some defects, but it provides five parameters that affect the enterprise value. The five parameters are taken as the input variables of BP neural network, and the optimal weights of the network are determined by genetic algorithm. To establish an improved real option model to evaluate the value of new energy listed companies. Finally, we select the typical listed companies in the new energy sector for empirical research, compare the equity value calculated with the improved real option model and the results calculated by the B-S model with the actual value, respectively. The accuracy of the improved model is verified. Further using the improved model to calculate the stock price and compare it with the actual average closing price is helpful to judge the future trend of the stock price. In addition, by analyzing the sensitivity of the five parameters of the sample company, the key factors affecting the enterprise value are found out, and the reasonable suggestions on how to enhance the enterprise value are put forward.
【学位授予单位】：燕山大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.2;F832.51;F224

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