本文選題：汽車制造業(yè)　切入點：因子分析　出處：《陜西科技大學(xué)》2013年碩士論文

【摘要】：隨著經(jīng)濟(jì)的發(fā)展、科技的進(jìn)步，我國汽車制造業(yè)也在不斷的發(fā)展壯大，但受國家相關(guān)政策、油價及材料物價、市場因素等方面的影響，汽車制造業(yè)正處于波動性的發(fā)展?fàn)顟B(tài)。由于汽車制造業(yè)的財務(wù)風(fēng)險不僅關(guān)系到整個汽車行業(yè)的經(jīng)濟(jì)利益，而且也與股東利益、證券市場及國民經(jīng)濟(jì)等密切相關(guān)，，所以汽車制造業(yè)上市公司必須進(jìn)行財務(wù)預(yù)警系統(tǒng)的研究與開發(fā)，加強(qiáng)風(fēng)險管理，提高預(yù)警意識，做好風(fēng)險防范措施，以促進(jìn)我國汽車制造業(yè)健康而快速的發(fā)展。 本文首先介紹了研究的背景、目的及意義，通過借鑒國內(nèi)外學(xué)者在財務(wù)預(yù)警方面的研究成果，確立本文的研究方法、思路及創(chuàng)新之處。然后介紹了企業(yè)財務(wù)預(yù)警的相關(guān)概念及理論基礎(chǔ)，并分析了我國汽車制造企業(yè)的發(fā)展環(huán)境、財務(wù)現(xiàn)狀、風(fēng)險特征及影響因素。財務(wù)標(biāo)體系是預(yù)警模型構(gòu)建的基礎(chǔ)，也是直接影響預(yù)警效果的重要因素之一，為了更客觀、真實反映汽車制造業(yè)的財務(wù)狀況，本文選取了償債能力、現(xiàn)金流量能力、盈利能力、成長能力及運營能力等方面的26個財務(wù)指標(biāo)，另外從公司治理、股權(quán)結(jié)構(gòu)、審計意見等角度選取8個非財務(wù)指標(biāo)來構(gòu)建財務(wù)預(yù)警指標(biāo)體系。 在實證研究中，按照規(guī)模、經(jīng)營范圍、時間等樣本選取原則，選取深滬A股市場中的54家汽車制造業(yè)上市公司為研究樣本，樣本數(shù)據(jù)包括在2003—2011年被特別處理的18家汽車制造業(yè)上市公司和與之配對的36家財務(wù)正常公司。然后利用SPSS軟件中的顯著性檢驗、因子分析等方法進(jìn)行財務(wù)指標(biāo)的篩選，最終確立了5個綜合財務(wù)指標(biāo)因子和4個非財務(wù)指標(biāo)因子。結(jié)合汽車制造業(yè)上市公司的特點及財務(wù)狀況，用Logistic回歸分析方法構(gòu)建汽車制造企業(yè)的預(yù)警模型，通過模型的檢驗、比較分析可以得出以下結(jié)論：引入非財務(wù)指標(biāo)后，財務(wù)危機(jī)發(fā)生前兩年、前三年的預(yù)測精度達(dá)到92.6%、79.6%，說明模型的預(yù)警效果較為顯著，也說明了財務(wù)危機(jī)的發(fā)生是一個漸變的過程，隨著時間的推移，財務(wù)狀況逐漸惡化；與僅考慮財務(wù)因素相比，引用非財務(wù)指標(biāo)后，財務(wù)危機(jī)發(fā)生前兩年、前三年的預(yù)測準(zhǔn)確度都有所提高，分別提高了5.6%、12.9%，從另一個角度也可以看出非財務(wù)指標(biāo)對遠(yuǎn)期預(yù)警來說效果更為明顯，而財務(wù)指標(biāo)對近期的預(yù)警效果較好。 最后，本文針對汽車制造業(yè)上市公司的行業(yè)特征及財務(wù)風(fēng)險狀況提出了一些建議，企業(yè)應(yīng)該提高危機(jī)意識、創(chuàng)新意識，建立財務(wù)風(fēng)險預(yù)警體系，提高債務(wù)償還能力及盈利能力等。建立汽車制造業(yè)上市公司的財務(wù)預(yù)警模型，有助于企業(yè)及時進(jìn)行風(fēng)險預(yù)測，積極采取風(fēng)險防范措施，這對汽車制造業(yè)上市公司財務(wù)風(fēng)險的前期控制和中期改善都有一定的實際意義和指導(dǎo)價值。
[Abstract]:With the development of economy and the progress of science and technology, the automobile manufacturing industry of our country has been developing and expanding constantly, but it is influenced by the related policies of the country, the price of oil and materials, the market factors, etc. Because the financial risk of automobile manufacturing industry is not only related to the economic interests of the whole automobile industry, but also closely related to the interests of shareholders, the securities market and the national economy, etc. Therefore, the listed companies of automobile manufacturing industry must carry on the research and development of the financial early warning system, strengthen the risk management, improve the early warning consciousness, and do well the risk prevention measures in order to promote the healthy and rapid development of the automobile manufacturing industry in our country. Firstly, this paper introduces the background, purpose and significance of the research, and establishes the research method of this paper by referring to the research results of domestic and foreign scholars in financial early warning. Then it introduces the related concepts and theoretical basis of enterprise financial early warning, and analyzes the development environment and financial status of automobile manufacturing enterprises in China. The financial standard system is the foundation of the early warning model and one of the important factors that directly affect the early warning effect. In order to reflect the financial situation of the automobile manufacturing industry more objectively and truly, this paper selects the solvency. There are 26 financial indexes in cash flow ability, profit ability, growth ability and operation ability. In addition, 8 non-financial indexes are selected from the aspects of corporate governance, equity structure and audit opinion to construct financial early warning index system. In the empirical study, according to the principles of sample selection, such as scale, business scope, time and so on, 54 auto manufacturing listed companies in Shenzhen and Shanghai A-share markets are selected as the study samples. The sample data include 18 auto manufacturing listed companies that were specially processed in 2003-2011 and 36 normal financial companies matched with them. Then the financial indicators are screened by using the significance test and factor analysis methods in SPSS software. Finally, five comprehensive financial index factors and four non-financial index factors are established. Combined with the characteristics and financial situation of listed companies in automobile manufacturing industry, the early warning model of automobile manufacturing enterprises is constructed by Logistic regression analysis, and the model is tested. The comparative analysis can draw the following conclusions: two years before the introduction of non-financial indicators, the prediction accuracy of the first three years has reached 92.66.79.6. it shows that the early warning effect of the model is more remarkable, and that the occurrence of financial crisis is a gradual process. Over time, the financial situation has deteriorated; the accuracy of forecasts for the first three years of the financial crisis has improved in the two years preceding the financial crisis, when non-financial indicators were quoted as compared to only financial factors. From another angle, we can also see that non-financial indicators have more obvious effect on forward warning, while financial indicators have better effect in the near future. Finally, this paper puts forward some suggestions on the industry characteristics and financial risk situation of the listed companies in automobile manufacturing industry. Enterprises should raise the awareness of crisis and innovation, and establish a financial risk warning system. To improve the ability of debt repayment and profitability, to establish a financial early warning model of listed companies in automobile manufacturing industry, which will help enterprises to make timely risk prediction and take active risk prevention measures. This is of practical significance and guiding value to the early control and medium-term improvement of financial risk of listed companies in automobile manufacturing industry.
【學(xué)位授予單位】：陜西科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F275;F426.471

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