本文選題：新能源　切入點(diǎn)：上市公司　出處：《燕山大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著經(jīng)濟(jì)的快速發(fā)展，傳統(tǒng)能源日益短缺，開(kāi)發(fā)和利用新能源作為國(guó)家實(shí)現(xiàn)可持續(xù)發(fā)展的一項(xiàng)戰(zhàn)略舉措，越來(lái)越受到國(guó)家的重視。新能源上市公司是開(kāi)發(fā)、生產(chǎn)和銷(xiāo)售新能源產(chǎn)品并在證券市場(chǎng)公開(kāi)交易的上市企業(yè)，如何準(zhǔn)確合理的評(píng)估其企業(yè)價(jià)值，已經(jīng)成為政府、投資者和社會(huì)公眾關(guān)注的焦點(diǎn)。 新能源企業(yè)經(jīng)營(yíng)面臨的高度不確定性，使得企業(yè)管理者的決策具有靈活性，這種柔性管理價(jià)值就是實(shí)物期權(quán)的價(jià)值。傳統(tǒng)的價(jià)值評(píng)估方法不能評(píng)價(jià)企業(yè)擁有的未來(lái)投資機(jī)會(huì)的價(jià)值，即忽略了企業(yè)的實(shí)物期權(quán)價(jià)值。本文運(yùn)用遺傳算法優(yōu)化的人工神經(jīng)網(wǎng)絡(luò)，，對(duì)實(shí)物期權(quán)中的B-S模型進(jìn)行改進(jìn)，旨在建立一種能更加全面準(zhǔn)確的評(píng)估新能源上市公司企業(yè)價(jià)值的方法。 首先，在對(duì)國(guó)內(nèi)外研究現(xiàn)狀進(jìn)行綜述的基礎(chǔ)上，介紹了傳統(tǒng)企業(yè)價(jià)值評(píng)估的方法，并對(duì)實(shí)物期權(quán)理論進(jìn)行了詳細(xì)的闡述。 其次，分析了新能源上市公司的特點(diǎn)和價(jià)值評(píng)估環(huán)境以及其擁有的實(shí)物期權(quán)的類(lèi)型，并分析了傳統(tǒng)企業(yè)價(jià)值評(píng)估方法在評(píng)估新能源上市企業(yè)價(jià)值時(shí)存在的不足以及運(yùn)用實(shí)物期權(quán)評(píng)估其企業(yè)價(jià)值存在的優(yōu)勢(shì)。 再次，B-S模型雖具有一定的缺陷，但是它提供了影響企業(yè)價(jià)值的五個(gè)參數(shù)，將這五個(gè)參數(shù)作為BP神經(jīng)網(wǎng)絡(luò)的輸入變量，通過(guò)遺傳算法確定網(wǎng)絡(luò)最優(yōu)權(quán)值，建立評(píng)估新能源上市公司企業(yè)價(jià)值的改進(jìn)的實(shí)物期權(quán)模型。 最后，選取新能源板塊典型的上市公司進(jìn)行實(shí)證研究，將運(yùn)用改進(jìn)實(shí)物期權(quán)模型計(jì)算的股權(quán)價(jià)值與運(yùn)用B-S模型計(jì)算的結(jié)果分別與實(shí)際值進(jìn)行比較，驗(yàn)證了改進(jìn)模型的準(zhǔn)確性。進(jìn)一步利用改進(jìn)模型得到的股權(quán)價(jià)值計(jì)算股價(jià)，將其與實(shí)際的平均收盤(pán)價(jià)進(jìn)行比較，有助于判斷股價(jià)的未來(lái)變動(dòng)趨勢(shì)，幫助投資者做出正確的投資決策。另外，通過(guò)對(duì)樣本公司的五個(gè)參數(shù)進(jìn)行敏感性分析，找出影響企業(yè)價(jià)值的關(guān)鍵因素，從而對(duì)管理者如何提升企業(yè)價(jià)值提出合理建議。
[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.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F426.2;F832.51;F224

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