基于神經(jīng)網(wǎng)絡(luò)模型的電力上市公司價(jià)值評(píng)估研究
[Abstract]:In recent years, the international community has carried out a lot of research on enterprise value evaluation, and actively promoted the development of asset evaluation. The electric power industry of our country has not only the characteristics of state-owned enterprises, but also the special technical and economic characteristics of the industry. With the deepening reform of social economy, electric power enterprises must change their management concept and development mode if they want to achieve long-term development. In order to meet the challenges and opportunities brought by the reform of electric power system and the downward economic situation, it is necessary for electric power enterprises to explore the driving factors of enterprise value, enhance the ability of value creation, and obtain more surplus value. Therefore, it is of great theoretical and practical significance to explore a method which is suitable for enterprise operation and can evaluate the value of enterprise objectively and accurately. Through literature review and data collection, this paper provides theoretical support for understanding the current research situation of power industry and enterprise value assessment model. This paper is divided into five parts. The first part is the background and significance of the research, as well as the domestic and foreign research on the evaluation of enterprise value and the application of neural network model. On this basis, the second part introduces the theory of enterprise value and valuation. The first task of value evaluation is to define the types of enterprise value, and through the brief description of each form of value, we can get the enterprise value performance studied in this paper. Secondly, it introduces the methods and theoretical models of enterprise value evaluation, and then explores the enterprise value evaluation model adopted in this paper. The third part is the analysis of the driving factors of power enterprise value based on SWOT and the construction of index system. The value driving factors of electric power enterprises are analyzed by SWOT, and the value evaluation index system suitable for electric power enterprises is established. The fourth part is the power enterprise value evaluation model construction and empirical analysis, the neural network model based on the construction of a detailed description of the evaluation of enterprise value and empirical analysis. The fifth part is the research results and conclusions, as well as the shortcomings of this study, hope to be improved in the future. This article mainly carries on the innovation research from two aspects. First, the paper uses SWOT analysis method to analyze the driving factors of enterprise value, and constructs the index system of power enterprise value evaluation, considering the factors such as cash flow, capital cost, etc. Secondly, the paper innovatively combines neural network and EVA. The establishment of enterprise value evaluation model provides a new idea for forecasting method in enterprise value evaluation model.
【學(xué)位授予單位】:華北電力大學(xué)(北京)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:F406.7;F426.61
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 李振平;桂預(yù)風(fēng);;基于灰關(guān)聯(lián)神經(jīng)網(wǎng)絡(luò)和馬爾可夫模型的股票價(jià)格預(yù)測(cè)[J];內(nèi)蒙古師范大學(xué)學(xué)報(bào)(自然科學(xué)漢文版);2016年03期
2 孫海波;王麗敏;韓旭明;;引入趨勢(shì)因子的BP模型在股市預(yù)測(cè)中應(yīng)用[J];統(tǒng)計(jì)與決策;2015年19期
3 李翔;歐陽森;黃瑞藝;蔣金良;;基于SWOT方法分析我國電力需求側(cè)管理發(fā)展[J];廣西電力;2015年04期
4 王偉晶;;基于BP神經(jīng)網(wǎng)絡(luò)預(yù)測(cè)股票的漲跌趨勢(shì)[J];現(xiàn)代經(jīng)濟(jì)信息;2015年16期
5 李秉坤;錢欣;;企業(yè)價(jià)值評(píng)估收益法應(yīng)用問題及其完善[J];哈爾濱商業(yè)大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2014年03期
6 陳嶷瑛;張澤星;李文斌;;基于神經(jīng)網(wǎng)絡(luò)的股票價(jià)格預(yù)測(cè)模型[J];計(jì)算機(jī)應(yīng)用與軟件;2014年05期
7 王含春;秦曦;鄭凱;;我國電力上市公司股權(quán)融資成本的測(cè)算與分析—基于三階段剩余收益貼現(xiàn)模型[J];管理現(xiàn)代化;2014年01期
8 劉玉平;池睿;;企業(yè)價(jià)值評(píng)估收益法中營運(yùn)資金預(yù)測(cè)的改進(jìn)[J];會(huì)計(jì)之友;2014年01期
9 劉家和;金秀;陳露艷;苑瑩;;基于IDNPSO-BP神經(jīng)網(wǎng)絡(luò)的股票市場(chǎng)指數(shù)預(yù)測(cè)[J];東北大學(xué)學(xué)報(bào)(自然科學(xué)版);2013年06期
10 劉任重;;基于企業(yè)價(jià)值評(píng)估的DCF與RIV定價(jià)模型的比較[J];統(tǒng)計(jì)與決策;2013年02期
相關(guān)博士學(xué)位論文 前1條
1 徐向;中國電力上市企業(yè)法人治理結(jié)構(gòu)研究[D];東北財(cái)經(jīng)大學(xué);2015年
相關(guān)碩士學(xué)位論文 前10條
1 趙安琦;基于EVA的企業(yè)價(jià)值評(píng)估研究[D];吉林財(cái)經(jīng)大學(xué);2016年
2 胡照躍;人工神經(jīng)網(wǎng)絡(luò)在股票預(yù)測(cè)中的應(yīng)用[D];中北大學(xué);2016年
3 趙紅梅;企業(yè)價(jià)值評(píng)估方法的選擇及影響因素研究[D];山東大學(xué);2015年
4 付靜麗;基于DCF的火力發(fā)電企業(yè)價(jià)值評(píng)估研究[D];遼寧大學(xué);2015年
5 郭智慧;我國電力行業(yè)上市公司資本結(jié)構(gòu)優(yōu)化研究[D];天津財(cái)經(jīng)大學(xué);2015年
6 張懿巍;引入EVA的發(fā)電類上市公司財(cái)務(wù)預(yù)警研究[D];華北電力大學(xué);2015年
7 孫明楊;基于剩余收益模型的皖能電力企業(yè)價(jià)值評(píng)估研究[D];湖南大學(xué);2014年
8 張希影;基于遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)股票價(jià)格預(yù)測(cè)[D];青島科技大學(xué);2014年
9 張明;基于改進(jìn)動(dòng)態(tài)神經(jīng)網(wǎng)絡(luò)的股票預(yù)測(cè)模型的研究[D];內(nèi)蒙古大學(xué);2014年
10 楊婷;企業(yè)價(jià)值評(píng)估指標(biāo)體系研究[D];長安大學(xué);2014年
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