本文關(guān)鍵詞：企業(yè)債券信用評(píng)級(jí)體系在礦山機(jī)械制造業(yè)的應(yīng)用分析　出處：《太原理工大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

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【摘要】：煤炭產(chǎn)業(yè)是國(guó)民經(jīng)濟(jì)發(fā)展的基礎(chǔ)產(chǎn)業(yè),礦山機(jī)械制造業(yè)是采礦業(yè)及煤炭開采和洗選業(yè)發(fā)展的基礎(chǔ)產(chǎn)業(yè),具有行業(yè)關(guān)聯(lián)度高、技術(shù)帶動(dòng)力度大等特點(diǎn),被稱為煤礦機(jī)械化建設(shè)的“發(fā)動(dòng)機(jī)”,作為國(guó)家重點(diǎn)培育和發(fā)展的七大戰(zhàn)略性新興產(chǎn)業(yè)之一,近年來(lái)呈現(xiàn)出快速發(fā)展的態(tài)勢(shì)。受當(dāng)前宏觀經(jīng)濟(jì)下行和煤炭企業(yè)固定資產(chǎn)投資增速下降的影響,自2013年以來(lái),礦山機(jī)械制造業(yè)銷售增速明顯回落,而同期行業(yè)投資擴(kuò)張的趨勢(shì)明顯,因此,要實(shí)現(xiàn)礦機(jī)企業(yè)的創(chuàng)新發(fā)展,資金支持必不可少,作為企業(yè)融資重要渠道之一的債券融資,一定程度上解決了礦機(jī)企業(yè)的資金困境。對(duì)礦山機(jī)械制造業(yè)企業(yè)進(jìn)行債券信用評(píng)級(jí)也因此顯得意義重大,而要對(duì)發(fā)債企業(yè)的信用狀況和債項(xiàng)具體保護(hù)措施做出全面、綜合的評(píng)價(jià),就必須依據(jù)一套適合該行業(yè)特征的,完整統(tǒng)一、而又能科學(xué)量化的評(píng)級(jí)指標(biāo)體系。 本文站在獨(dú)立第三方的角度,從債券信用評(píng)級(jí)體系中較為核心的評(píng)級(jí)指標(biāo)體系出發(fā),結(jié)合礦山機(jī)械制造行業(yè)的典型特征,完善了現(xiàn)有債券信用評(píng)級(jí)指標(biāo)體系,增加“行業(yè)狀況”和“外部風(fēng)險(xiǎn)與支持”兩項(xiàng)信用評(píng)價(jià)指標(biāo),從企業(yè)所處行業(yè)狀況、自身綜合實(shí)力、生產(chǎn)經(jīng)營(yíng)與管理質(zhì)量、財(cái)務(wù)狀況及外部風(fēng)險(xiǎn)與支持等五個(gè)方面,內(nèi)外因素相結(jié)合,更全面、客觀對(duì)礦山機(jī)械制造企業(yè)的信用風(fēng)險(xiǎn)狀況進(jìn)行評(píng)估。同時(shí),采用Logit模型作為信用風(fēng)險(xiǎn)評(píng)估的輔助驗(yàn)證模型,從評(píng)價(jià)指標(biāo)體系中選取35項(xiàng)主要財(cái)務(wù)指標(biāo),運(yùn)用SPSS軟件分別對(duì)所選指標(biāo)數(shù)據(jù)進(jìn)行多元共線性分析和Logit回歸分析,對(duì)發(fā)債企業(yè)違約概率做出預(yù)測(cè)。研究表明,該模型對(duì)企業(yè)的信用風(fēng)險(xiǎn)評(píng)估預(yù)測(cè)性較好,平均準(zhǔn)確率為91.6%,通過(guò)指標(biāo)體系和Logit模型評(píng)價(jià)結(jié)果比較,驗(yàn)證礦山機(jī)械制造業(yè)債券信用評(píng)級(jí)指標(biāo)體系的合理性。 結(jié)合實(shí)踐應(yīng)用,本文以A礦山機(jī)械制造企業(yè)為實(shí)例,進(jìn)行信用評(píng)級(jí)實(shí)際操作分析,使抽象的理論與實(shí)踐操作融合為一體,驗(yàn)證了指標(biāo)體系及所選方法的可靠性和實(shí)用性,豐富了企業(yè)債券信用評(píng)級(jí)體系,有一定的參考價(jià)值。
[Abstract]:The coal industry is the basic industry of national economic development, mining machinery manufacturing industry is the basic industry of the development of mining industry and coal mining and washing industry, with a high degree of correlation, the characteristics of technology with high power, known as mechanized coal mine construction "engine", as one of the seven strategic emerging industry's focus on fostering with the development in recent years, showing a trend of rapid development. Affected by the current economic downturn and the coal enterprise fixed asset investment growth decline, since 2013, mining machinery manufacturing industry sales growth rate dropped significantly, while the industry investment expansion trend is obvious, therefore, to realize the innovation and development of mining enterprises, financial support is essential as bond financing, corporate finance one of the important channels, to a certain extent to solve the financial difficulties of its enterprises. In mining machinery manufacturing enterprises bonds The credit rating and therefore is of great significance to, and specific measures for the protection of the credit and debt of corporate bonds to make a comprehensive, comprehensive evaluation, it must be based on a set of suitable for the characteristics of the industry, complete and unified, and scientific quantitative evaluation index system.
This paper stands in the perspective of an independent third party, starting from the bond credit rating system is the core of the evaluation index system, combined with the typical characteristics of mining machinery manufacturing industry, improve the existing bond credit rating index system, increase the "industry" and "external risk and support two credit evaluation index, from the status of the industry the enterprise, its comprehensive strength, production management and quality management, the five aspects of financial condition and external risk and support, the combination of internal and external factors, more comprehensive and objective of mining machinery manufacturing enterprise credit risk situation evaluation. At the same time, aided verification Logit model was used as a credit risk assessment, selection of 35 the main financial indicators from the evaluation index system, using SPSS software were selected index data by multi linear analysis and Logit regression analysis, the probability of default of corporate bonds do A prediction is made. The research shows that the prediction accuracy of the model is better than that of the Logit model, and the prediction accuracy is 91.6%. The rationality of the credit rating index system of mining machinery manufacturing industry is verified through the comparison between the index system and the evaluation result of the model.
Combining with the practical application, based on A mining machinery manufacturing enterprise as an example, the credit rating of actual operation analysis, make the abstract theory and practice integration, validated the reliability and practicability of the index system and the selected method, enrich the corporate bond credit rating system, there is a certain reference value.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F426.4;F406.7

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