本文關(guān)鍵詞：電力上市公司財(cái)務(wù)風(fēng)險(xiǎn)評(píng)價(jià)及預(yù)警研究　出處：《華北電力大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

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【摘要】：電力工業(yè)是國(guó)民經(jīng)濟(jì)的重要基礎(chǔ)能源產(chǎn)業(yè),在國(guó)家經(jīng)濟(jì)發(fā)展戰(zhàn)略中占有舉足輕重的地位。電力上市公司作為電力工業(yè)中最具活力和發(fā)展?jié)摿Φ钠髽I(yè),其財(cái)務(wù)狀況受到投資者、債權(quán)人的廣泛關(guān)注。隨著全球經(jīng)濟(jì)一體化的發(fā)展,我國(guó)上市公司擁有優(yōu)越發(fā)展機(jī)遇的同時(shí)面臨巨大的挑戰(zhàn),電力上市公司作為上市公司中的一員同樣面臨著激烈的競(jìng)爭(zhēng)和多元化的風(fēng)險(xiǎn),其中財(cái)務(wù)風(fēng)險(xiǎn)是企業(yè)發(fā)展過(guò)程中面臨的最重要的風(fēng)險(xiǎn)之一。近年來(lái),電力上市公司資產(chǎn)負(fù)債率高居不下,償債壓力較大,企業(yè)財(cái)務(wù)風(fēng)險(xiǎn)較高。因此,評(píng)價(jià)企業(yè)當(dāng)前財(cái)務(wù)風(fēng)險(xiǎn)水平并對(duì)其進(jìn)行有效預(yù)警對(duì)于電力上市公司提升財(cái)務(wù)抗風(fēng)險(xiǎn)能力具有重大意義。 本文首先梳理財(cái)務(wù)風(fēng)險(xiǎn)預(yù)警的相關(guān)概念,介紹所使用模型和方法的基本理論。其次,本文對(duì)電力行業(yè)的特征及其面臨的風(fēng)險(xiǎn)進(jìn)行分析。在借鑒前人的研究成果并結(jié)合電力上市公司的實(shí)際,從盈利能力、償債能力、營(yíng)運(yùn)能力、成長(zhǎng)能力、現(xiàn)金流量等五個(gè)方面構(gòu)建了電力上市公司風(fēng)險(xiǎn)評(píng)價(jià)的指標(biāo)體系�？紤]到評(píng)價(jià)指標(biāo)可能存在共線性的問(wèn)題,本文采用主成分TOPSIS法進(jìn)行綜合評(píng)價(jià)分析,即對(duì)評(píng)價(jià)指標(biāo)進(jìn)行主成分選取,利用TOPSIS法對(duì)上市公司財(cái)務(wù)風(fēng)險(xiǎn)進(jìn)行綜合評(píng)價(jià)并劃分等級(jí),隨后使用遺傳算法優(yōu)化的支持向量機(jī)(GA-SVM)模型并借助Java編程實(shí)現(xiàn)了電力上市公司財(cái)務(wù)風(fēng)險(xiǎn)預(yù)警分析。實(shí)證結(jié)果表明GA-SVM預(yù)警模型有較好的判別精度。最后,根據(jù)前文的理論分析以及實(shí)證研究結(jié)果,提出了針對(duì)電力上市公司的財(cái)務(wù)風(fēng)險(xiǎn)控制策略。
[Abstract]:Electric power industry is an important basic energy industry of national economy, which plays an important role in the national economic development strategy. The listed power companies are the most dynamic and potential enterprises in the power industry. With the development of global economic integration, the listed companies of our country have the superior development opportunity and face the huge challenge at the same time. As a member of listed companies, electric power listed companies also face fierce competition and diversified risks, among which financial risk is one of the most important risks in the process of enterprise development. Power listed companies have a high ratio of assets and liabilities, higher debt service pressure and higher financial risk. It is of great significance to evaluate the current financial risk level of enterprises and carry out effective early warning for the power listed companies to enhance the ability of financial risk resistance. This article first combs the financial risk early warning related concept, introduces the basic theory of the model and the method used. Secondly. This paper analyzes the characteristics of the power industry and the risks it faces. In the light of the previous research results and the actual situation of the listed power companies, the paper analyzes the profitability, solvency, operating capacity and growth ability of the listed companies. This paper constructs the index system of power listed companies' risk evaluation from five aspects, such as cash flow. Considering that the evaluation index may have the problem of collinearity, this paper adopts the principal component TOPSIS method to carry on the comprehensive evaluation analysis. That is to say, the main components of the evaluation index are selected, and the financial risk of listed companies is comprehensively evaluated and classified by using TOPSIS method. Subsequently, the genetic algorithm is used to optimize the support vector machine (GA-SVM). The model also realizes the financial risk early warning analysis of listed power companies with Java programming. The empirical results show that the GA-SVM early warning model has good discriminant accuracy. Finally. Based on the theoretical analysis and empirical results, the paper puts forward the financial risk control strategy for the listed companies.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F406.7;F426.61

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