本文選題：信用風險測度　切入點：判別分忻　出處：《東華大學》2013年碩士論文

【摘要】：自2008年國際金融危機爆發(fā)以來,世界經濟經歷了急劇地動蕩與衰退地考驗,現在又進入到艱難復蘇的后國際金融危機時期。受經濟周期下行和國家產業(yè)政策調整等因素的影響,國內制造業(yè)、地產、船舶、鋼鐵貿易等被列入了高風險行業(yè)。其中,制造業(yè)作為國民經濟的基礎,是經濟指數良好運行強有力地支撐。然而,由于我國近期宏觀經濟走勢趨緩、出口疲軟、用工成本上升、訂單外流等因素的影響,使得我國制造業(yè)發(fā)展形勢很不樂觀,日常運營面臨重大挑戰(zhàn),信用風險開始集中暴露。因此,如何有效測度制造業(yè)上市公司的信用風險亟待解決。基于此,文章采用定性和定量的方法對我國制造業(yè)上市公司信用風險的測度進行了理論分析和實證研究。 首先,文章對國內外信用風險文獻資料,按照信用風險測度的指標模型和非指標模型這一標準進行了梳理與學習,并從研究對象、研究視角、研究方法三個方面總結歸納了學者們的研究成果對作者所研究課題的啟發(fā)。 其次,文章對信用風險的理論知識進行了簡要說明,并對信用風險的測度模型按照指標模型和非指標模型這一標準進行了解析,以加深對模型的認知,為后續(xù)信用風險測度模型的選擇與運用奠定理論基礎。同時,文章也對我國制造業(yè)上市公司信用風險的成因及特點進行了分析。 通過上述信用風險文獻綜述、理論知識以及各種模型的解析,我們發(fā)現：現有的針對國內上市公司信用風險的測度分別從會計報表截面數據和資本市場時間序列數據兩個單方面因素展開研究。而公司信用風險發(fā)生與否是一個長期積累的過程,且會計報表截面數據是信用主體的歷史記載,具有“向后看”的特性；資本市場時間序列數據作為先行指標,具有“前瞻性”。為此,如果將兩者有效結合,使其較為全面地涵蓋公司未來違約的預測信息,那么其整體的預測效果是否比從單一方面考慮會更好是文章研究的口的所在。 因此,文章結合實際情況以及相關模型的適用性,先運用財務比率指標作為會計報表截面數據,基于主成分和判別分析對制造業(yè)上市公司的信用風險進行初步測度；接著運用股票價格時間序列數據作為資本市場數據,基于KMV模型計算違約距離DD,然后將財務比率指標主成分因子與違約距離DD共同納入到Logistic模型中,實現會計報表截面數據和資本市場時間序列數據的有效結合,以提高對我國制造業(yè)上市公司信用風險的測度能力。 實證研究結果表明,會計報表截面數據和資本市場時間序列數據有效結合后,使得Logistic模型整體預測準確率達到85%,相比僅有財務比率指標數據的分析模型,其整體預測準確率提高了5%,充分說明財務比率指標與違約距離DD的結合對模型的預測是有效的。至此,文章從會計報表截面數據以及資本市場時間序列數據兩個方面,通過運用不同模型和方法的優(yōu)勢互補性,試探性地提出我國制造業(yè)上市公司信用風險兩階段測度體系,從而更有效地對制造業(yè)的信用風險進行測度,并為其有效管理提供初步的理論依據。
[Abstract]:Since 2008 the international financial crisis, the world economy has experienced turbulence and recession test, and now into the difficult recovery after the international financial crisis. Affected by the downward economic cycle and the national industrial policy adjustments and other factors, the domestic real estate industry, shipbuilding, steel trade, etc. are included in the high risk industry the manufacturing industry is the foundation of the national economy, the economic index is good operation of the strong support. However, due to China's recent macroeconomic trends slowed, weak exports, rising labor costs, affect the outflow of orders and other factors, the development of China's manufacturing industry is very optimistic about the situation, the daily operation is facing major challenges, credit risk began to focus on the exposure. Therefore, how to effectively measure the credit risk of Listed Companies in the manufacturing industry to be solved. Based on this, the dissertation uses the method of qualitative and quantitative of China's manufacturing industry. The measure of the credit risk of the city company has been analyzed theoretically and empirically.
First of all, the article of domestic and international credit risk literature, according to the index model of credit risk measurement and non index model which is a standard of the carding and study, and from the research object, research perspective, research methods inspired three aspects summarizes the research achievements of scholars research on them.
Secondly, the credit risk of the theoretical knowledge of this paper are briefly described, and the measure model of credit risk in accordance with the index model and non index model of this standard are analyzed, in order to deepen the cognition model, lay the theoretical foundation for the follow-up and use of credit risk measurement models. At the same time, the article also on credit risk China's manufacturing industry listed companies causes and characteristics are analyzed.
The credit risk through literature review, theoretical knowledge and analytical models, we find that the existing credit risk of domestic listed companies to measure and carries out the research on accounting statements section data and time series data of capital market and two unilateral factors. The company credit risk occurs or not is a long-term process of accumulation, and accounting report section data is the main credit history, has the characteristic of "look back"; the capital market time series data as a leading indicator, are "forward-looking". Therefore, if the effective combination of the two, the forecast information comprehensively covers the company's future defaults, then whether the overall prediction results than considering one aspect of the paper is to be better in place.
Therefore, based on the actual situation and the applicability of the model, we use financial ratios as the accounting statements section data, principal component analysis and discriminant analysis for manufacturing the credit risk of listed companies based on the preliminary measure; then use the stock price time series data as the capital market data, the default distance calculation model based on KMV and DD. The financial ratio index of principal components and DD into the distance to default to the Logistic model, realize the effective combination of the accounting statements section data and time series data of the capital market, to improve the ability to measure the credit risk of China's Listed Companies in the manufacturing industry.
The empirical results show that the effective combination of the accounting statements section data and time series data of capital market, makes the Logistic model the overall prediction accuracy reached 85%, compared with the model only financial ratio index data, the overall prediction accuracy is increased by 5%, and shows the default ratios from DD to forecast model is combined with effective. Thus, this article from the two aspects of accounting statements and the section data of capital market time series data, through the complementary advantages of the use of different models and methods, we put forward some of China's manufacturing industry listed companies' credit risk measurement system of two stages, so as to more effectively to the manufacturing industry to measure credit risk, and to provide the theoretical basis for its effective management.

【學位授予單位】：東華大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：F425;F832.51;F224

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本文編號：1715148