本文選題：房地產(chǎn)客戶信用風(fēng)險 + 信用風(fēng)險度量��； 參考：《浙江大學(xué)》2013年碩士論文

【摘要】：本文利用國內(nèi)上市房地產(chǎn)公司數(shù)據(jù)和國內(nèi)某大型機械設(shè)備制造商(房地產(chǎn)上游企業(yè))的內(nèi)部非上市房地產(chǎn)公司數(shù)據(jù),運用成熟的傳統(tǒng)非線性技術(shù)Logit二分類模型來研究反映我國房地產(chǎn)公司信用風(fēng)險的度量模型。在指標(biāo)選取上,本文基于對公司違約本質(zhì)的理論分析,企業(yè)守約充分必要條件是企業(yè)必須具有一定的還款意愿和相應(yīng)的還款能力,本文所采用的指標(biāo)分為財務(wù)類指標(biāo)(體現(xiàn)企業(yè)還款能力)和非財務(wù)指標(biāo)(影響企業(yè)還款意愿)。本文適用的違約標(biāo)志是“房地產(chǎn)公司因逾期不支付、無力支付到期債務(wù)而遭受債權(quán)方訴訟并敗訴”,即房地產(chǎn)公司實際發(fā)生違約。模型檢驗方面通過分類預(yù)測正確性檢驗對各模型的效力進行了比較分析。 通過實證研究發(fā)現(xiàn),Logit模型具有良好的違約預(yù)測能力,財務(wù)類指標(biāo)使用違約前一年數(shù)據(jù)建模更有效,進一步引入影響企業(yè)還款意愿的非財務(wù)類指標(biāo)后,能更好地反映公司信用風(fēng)險的情況。通過利用非上市房地產(chǎn)公司數(shù)據(jù)對模型進行檢驗,發(fā)現(xiàn)“以上市房地產(chǎn)公司作為建模樣本而獲得的信用風(fēng)險度量模型”基本適用于判別非上市房地產(chǎn)公司的違約風(fēng)險。 最后,由于本文所關(guān)注的信用風(fēng)險主要是以企業(yè)間賒銷為內(nèi)容的商業(yè)信用風(fēng)險,基于我國企業(yè)信用風(fēng)險管理現(xiàn)狀,尤其是房地產(chǎn)上游企業(yè)所面臨的嚴峻環(huán)境,本文就如何管理房地產(chǎn)客戶信用風(fēng)險提供實踐建議,結(jié)合筆者自身企業(yè)信用管理工作實踐經(jīng)驗,提出“信用風(fēng)險管理操作流程方案”及實施的細化建議,并就如何將房地產(chǎn)類客戶信用風(fēng)險度量模型運用到企業(yè)信用風(fēng)險管理操作流程的實踐中提供建議。
[Abstract]:This paper uses domestic listed real estate company data and internal non-listed real estate company data of a large domestic machinery and equipment manufacturer (real estate upstream enterprise). This paper studies the measurement model of the credit risk of real estate companies in China by using the Logit two-classification model, which is a mature nonlinear technique. In the selection of indicators, based on the theoretical analysis of the nature of corporate default, the sufficient and necessary conditions for the enterprise to keep the contract is that the enterprise must have a certain willingness to repay and the corresponding repayment ability. The indicators used in this paper are classified into financial indicators (reflecting the repayment ability of enterprises) and non-financial indicators (affecting the willingness of enterprises to repay). The sign of breach of contract applied in this paper is that the real estate company is in breach of contract because of overdue payment and inability to pay its debts due to the creditor's lawsuit. In the aspect of model test, the validity of each model is compared and analyzed by the correctness test of classification prediction. Through empirical research, it is found that the logit model has a good ability to predict default, and the financial indicators are more effective to use the data of one year before default, and further introduce the non-financial indicators that affect the willingness of enterprises to repay. Can better reflect the company's credit risk situation. By using the data of non-listed real estate companies to test the model, it is found that "the credit risk measurement model obtained by the real estate companies above the city as the modeling sample" is basically suitable for judging the default risk of the non-listed real estate companies. Finally, because the credit risk of this paper is mainly the commercial credit risk which is based on the content of credit sale between enterprises, based on the current situation of enterprise credit risk management in our country, especially the severe environment faced by the upstream enterprises of real estate. This paper provides practical advice on how to manage the credit risk of real estate customers, combining with the author's own practical experience of enterprise credit management, puts forward the "credit risk management operation flow plan" and the detailed suggestions for implementation. It also provides some suggestions on how to apply the real estate customer credit risk measurement model to the practice of enterprise credit risk management.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：F832.45;F299.23;F224

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