發(fā)布時(shí)間：2018-03-06 01:17

  本文選題：僵尸企業(yè)　切入點(diǎn)：財(cái)務(wù)預(yù)警　出處：《上海師范大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：僵尸企業(yè)的存在擾亂了正常的市場秩序,造成社會(huì)資源的無端耗費(fèi),且易觸發(fā)系統(tǒng)性的金融風(fēng)險(xiǎn)。因而,關(guān)于僵尸企業(yè)的預(yù)警研究對于新常態(tài)下推動(dòng)經(jīng)濟(jì)發(fā)展質(zhì)量的提升,有著極大的現(xiàn)實(shí)意義。本文以滬深兩市制造業(yè)與采礦業(yè)兩個(gè)產(chǎn)能過剩重災(zāi)區(qū)板塊的個(gè)股樣本作為研究對象,在廣泛文獻(xiàn)研究的基礎(chǔ)上,以“在t年度首次被FN-CHK識別為僵尸企業(yè),且至少持續(xù)至t+1年”作為識別方案,通過顯著性檢驗(yàn)、主成分分析、數(shù)據(jù)清洗、數(shù)據(jù)歸一化等多種預(yù)處理手段建立基于合并年報(bào)財(cái)務(wù)比率的預(yù)警體系,利用二分類Logistic回歸模型和BP神經(jīng)網(wǎng)絡(luò)模型進(jìn)行實(shí)證研究,對模型進(jìn)行了合理的解釋,并分別從企業(yè)自身與監(jiān)管層面給出了相關(guān)政策建議。研究結(jié)果發(fā)現(xiàn),采用所構(gòu)建模型均具備良好的預(yù)警能力。同時(shí),由于企業(yè)經(jīng)營效益的發(fā)展演化是一個(gè)漸進(jìn)累積的過程,相較于以Logistic回歸為代表傳統(tǒng)的線性、結(jié)構(gòu)化的預(yù)警方法,BP神經(jīng)網(wǎng)絡(luò)更能做出充分的反饋,對于僵尸企業(yè)的預(yù)警具有積極的意義和價(jià)值。盈利能力和創(chuàng)現(xiàn)能力在對僵尸企業(yè)的預(yù)警中起著關(guān)鍵的作用,具體地,每股收益和總資產(chǎn)報(bào)酬率、凈利潤(同比增長率)和經(jīng)營活動(dòng)產(chǎn)生的現(xiàn)金流量凈額(同比增長率)是影響企業(yè)是否被判定為僵尸企業(yè)的最重要因素。
[Abstract]:The existence of zombie enterprises disturbs the normal market order, causes unprovoked consumption of social resources, and easily triggers systemic financial risks. Therefore, the early warning research on zombie enterprises promotes the quality of economic development in the new normal. It is of great practical significance. This paper takes the individual stock samples of the manufacturing and mining industries in the heavy disaster areas of Shanghai and Shenzhen Stock Exchange as the research objects, and takes "FN-CHK as a zombie enterprise for the first time in t year," on the basis of extensive literature research. And at least one year "as the identification scheme, through the significance test, principal component analysis, data cleaning, data normalization and other pre-processing methods to establish an early warning system based on the combined annual financial ratio. Using the two-classification Logistic regression model and BP neural network model to carry on the empirical research, has carried on the reasonable explanation to the model, and separately has given the related policy suggestion from the enterprise itself and the supervision level. At the same time, since the development and evolution of enterprise operating benefits is a gradual cumulative process, compared with Logistic regression as the representative of the traditional linear, The structured early warning method, BP neural network, can make sufficient feedback and has positive significance and value for the early warning of zombie enterprises. Profitability and creation ability play a key role in the early warning of zombie enterprises. Earnings per share and total return on assets, net profit (year-on-year growth rate) and net cash flow generated by operating activities (year-on-year growth rate) are the most important factors affecting whether a company is judged to be a zombie.
【學(xué)位授予單位】：上海師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F424;F426.1;F832.51

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