發(fā)布時間：2017-12-28 13:26

  本文關(guān)鍵詞：我國制造業(yè)上市公司財務(wù)預(yù)警模型的實證研究　出處：《中國海洋大學》2014年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 財務(wù)預(yù)警 Logistic回歸 模型 實證 運用

【摘要】：經(jīng)濟全球化使世界形勢產(chǎn)生了劇烈的變化,經(jīng)濟的迅猛發(fā)展在給企業(yè)帶來前所未有機遇的同時也帶來了巨大的挑戰(zhàn),然而與之相匹配的完善的全球經(jīng)濟管理體制尚未形成,企業(yè)經(jīng)營中所面臨的諸多不確定性日益增加。世界頂尖企業(yè)諸如安然、寶麗來、安達信等的轟然倒塌,美國次貸危機的全面爆發(fā)公司,遭遇財務(wù)危機甚至破產(chǎn)的案例層出不窮,面對競爭激烈的市場環(huán)境,各類公司都加強了對其自身財務(wù)狀況穩(wěn)定性的關(guān)注,越來越注重完善公司財務(wù)預(yù)警系統(tǒng)�；谖覈鴮嶋H情況,財政部企業(yè)司于2009年也曾提出“企業(yè)從自身實際出發(fā),探索建立企業(yè)財務(wù)預(yù)警機制”、“注重發(fā)揮企業(yè)財務(wù)信息的預(yù)警作用,加強企業(yè)財務(wù)風險監(jiān)測預(yù)警工作”等要求。一般而言,任何企業(yè)的財務(wù)危機惡化都會經(jīng)歷一個過程,因此,在我國建立一個完善的、敏感的制造業(yè)上市公司的財務(wù)預(yù)警模型,對財務(wù)危機盡早反映、將其消滅于萌芽之中,對一般投資者、政府和銀行等國家金融機構(gòu)、注冊會計師、債權(quán)人及潛在的債權(quán)人、經(jīng)營管理者等利益相關(guān)者來說,顯得尤為重要。論文以我國制造業(yè)上市公司作為研究對象,將公司因財務(wù)狀況異常而被特別處理(ST或*ST)作為企業(yè)陷入財務(wù)危機的標志,選取2011-2013年我國滬、深兩市首次被ST的27家財務(wù)危機公司作為樣本組,同時采用一一配對的方法逐年選擇27家財務(wù)健康公司作為配對組；初步選定反映企業(yè)償債能力(包括短期償債能力和長期償債能力)、盈利能力、股東獲利能力、發(fā)展能力、營運能力和現(xiàn)金流量能力等六大方面的62個變量指標,并通過柯爾莫哥洛夫-米諾夫正態(tài)分布檢驗(K-S檢驗)、顯著性檢驗(獨立樣本T檢驗和曼-惠特尼-威爾克森檢驗),篩選出顯著性的變量指標,再對顯著性的變量指標提取主成分以降低變量的個數(shù)和消除多重共線性；然后建立了ST前1-5年的Logistic回歸模型并對其擬合和預(yù)測效果進行檢驗,ST前1-5年的預(yù)測能力分別為80%、94.4%、75.0%、59.1%、63.6%；最后論文指出了財務(wù)預(yù)警模型的功能和適用范圍。利用中國海洋大學圖書館的資源,在論文寫作前期大量搜集、鑒別和整理國內(nèi)外文獻,反復推敲選定該論文題目以及寫作思路。接下來論文圍繞如何對我國制造業(yè)上市公司進行提前財務(wù)預(yù)警的問題,對財務(wù)預(yù)警的研究對象(即財務(wù)危機)、樣本選取、模型構(gòu)建和模型的運用等要素進行綜合系統(tǒng)地分析,從而找出解決的可行方案。對于國內(nèi)外財務(wù)預(yù)警研究的現(xiàn)狀綜述,界定財務(wù)危機的內(nèi)涵框架,財務(wù)預(yù)警的現(xiàn)有模型和財務(wù)預(yù)警模型在企業(yè)中的運用,論文采用了描述研究法。另外,通過實證研究方法,利用SPSS統(tǒng)計分析手段,建立了Logistic回歸的財務(wù)預(yù)警模型,并對其預(yù)測能力進行檢驗。論文在我國制造業(yè)上市公司中,連續(xù)選取三年的樣本數(shù)據(jù),并在ST前1-5年逐年配對選擇財務(wù)健康公司作為配對組；然后針對每個公司選取了62個財務(wù)指標,分別建立了ST前1-5年的Logistic回歸模型；數(shù)據(jù)容量較大、信息量豐富。初步選定的變量指標包括六大方面的62個財務(wù)指標,先后對其剔除了異常值、正態(tài)分布檢驗、顯著性檢驗(符合正態(tài)分布的用獨立樣本T檢驗、不符合正態(tài)分布的用曼-惠特尼-威爾柯克森檢驗)和主成分分析；變量指標全面、處理得當。論文分別建立了ST前1-5年的Logistic回歸模型,從而能夠提前、及時發(fā)現(xiàn)企業(yè)存在財務(wù)危機的可能性,起到一定預(yù)警的效果。
[Abstract]:The economic globalization makes the world situation changed, the rapid development of economy and the hitherto unknown opportunities in brings to the enterprise has brought great challenges, however perfect global economic management system matching has not yet formed, enterprise faces many uncertainties increasing. The world's top companies such as Enron, Arthur Andersen, polaroid, the collapse of the outbreak of the U.S. subprime mortgage crisis, suffered a financial crisis or even bankruptcy cases emerge in an endless stream, facing the fierce competition in the market environment, various companies have strengthened the status of its own financial stability concerns, more and more attention to improve the company's financial early warning system. Based on the actual situation of China, the Ministry of finance of the Ministry of finance also proposed in 2009 that "enterprises start from their own reality, explore the establishment of enterprise financial early warning mechanism", "pay attention to giving full play to the early warning function of enterprise financial information, and strengthen the monitoring and early warning of enterprise financial risks" and so on. In general, any company's financial crisis will go through a process, therefore, to establish a perfect financial early-warning model, sensitive Manufacturing Listed Companies in China, the financial crisis as soon as possible, will reflect the nipped in the bud, to ordinary investors, government and banks and other financial institutions of the state, registered accountants, creditors and potential creditors, managers and other stakeholders, it is particularly important. Based on the listed companies of China's manufacturing industry as the research object, the company because of the abnormal financial condition by special treatment (ST or *ST) as the enterprise into a financial crisis, selects 2011-2013 China's Shanghai and Shenzhen two city for the first time by the 27 financial crisis companies ST as samples, using the method of paired each year choose 27 financial health companies as the matched group; preliminary selected reflect the enterprise solvency (including short-term solvency and long-term solvency), 62 variables are indicators of profitability, shareholder profitability, development ability, operation ability and cash flow ability six aspects, and through the Karl Region - Minov normal distribution test (K-S test), t-test (independent samples T test and Mann Whitney test, Wilkerson) screened significant variables, and variables of significant extraction The main components in order to reduce the number of variables and eliminate multicollinearity; and then establish a Logistic regression model of ST before 1-5 years and to test the fitting and prediction, prediction ability of ST before 1-5 were 80%, 94.4%, 75%, 59.1%, 63.6%; finally, the paper points out that the financial early-warning model and function applicable scope. The Ocean University of China library resources, large collection, in writing papers early identification and sorting of literatures at home and abroad, the thesis selected batted and writing ideas. This paper focuses on how to advance the financial early-warning problem of manufacturing listed companies in China, the research object of financial early-warning (i.e. financial crisis), a comprehensive system of sample selection, construction model and use factor analysis, so as to find out the feasible solution. To summarize the current situation of financial early warning research at home and abroad, define the connotation framework of financial crisis, the existing models of financial early warning and the application of financial early-warning model in enterprises, the paper adopts descriptive research method. In addition, through the empirical research method, the SPSS statistical analysis method is used to establish the financial early warning model of Logistic regression, and its prediction ability is tested. The manufacturing industry listed companies in China, with continuous sample data for three years, and 1-5 years ago in the ST year by year selected financial health companies as the matched group; then selects 62 financial indicators for each company, respectively, the regression model was established Logistic ST 1-5 years ago; the rich amount of information, large data capacity. Variables selected 62 financial indicators including six aspects, has removed the abnormal value, normal distribution test and significance test (with normal using independent samples T test, the distribution does not meet the normal distribution by using the Mann Whitney Weill Kirk Sen test) and principal component analysis; the variable index comprehensive, proper treatment. The Logistic regression models in the first 1-5 years of ST were established respectively, so that we can find the possibility of financial crisis in advance and in time, and play a certain early warning effect.
【學位授予單位】：中國海洋大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F425;F406.7

【參考文獻】

相關(guān)期刊論文 前10條

1 龍松;向麗蘋;;因子分析在上市公司財務(wù)預(yù)警中的應(yīng)用[J];黃岡師范學院學報;2010年03期

2 郭德仁;王培輝;;基于模糊聚類和模糊模式識別的企業(yè)財務(wù)預(yù)警[J];管理學報;2009年09期

3 胡鄭利;;金融危機對我國企業(yè)財務(wù)運行的影響及啟示[J];會計之友(下旬刊);2009年07期

4 王利新;;基于模糊層次分析法的石油企業(yè)財務(wù)預(yù)警模型的構(gòu)建[J];石油天然氣學報;2008年03期

5 劉彥文;戴紅軍;;基于粗糙集—神經(jīng)網(wǎng)絡(luò)的財務(wù)危機預(yù)警模型實證研究[J];科研管理;2007年06期

6 王克敏;姬美光;;基于財務(wù)與非財務(wù)指標的虧損公司財務(wù)預(yù)警研究——以公司ST為例[J];財經(jīng)研究;2006年07期

7 李秉祥;基于模糊神經(jīng)網(wǎng)絡(luò)的企業(yè)財務(wù)危機非線性組合預(yù)測方法研究[J];管理工程學報;2005年01期

8 馬喜德;上市公司財務(wù)困境預(yù)測模型比較研究[J];經(jīng)濟師;2005年03期

9 馬喜德;基于神經(jīng)網(wǎng)絡(luò)模型的財務(wù)困境預(yù)測實證分析[J];山西財經(jīng)大學學報;2005年01期

10 巢劍雄;企業(yè)財務(wù)困境預(yù)警模型[J];湖南大學學報(自然科學版);2005年01期

，

本文編號：1346177