本文選題：信用風(fēng)險(xiǎn)　切入點(diǎn)：KMV模型　出處：《哈爾濱商業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：信用風(fēng)險(xiǎn)是金融市場(chǎng)上存在的一種最古老最基本的風(fēng)險(xiǎn)類型,同時(shí)也是我國(guó)金融市場(chǎng)中最重要的風(fēng)險(xiǎn)類型之一,所以其管理水平的高低對(duì)我國(guó)整個(gè)金融業(yè),甚至整個(gè)社會(huì)經(jīng)濟(jì)生活都存在著重要的影響。隨著金融環(huán)境的日益復(fù)雜,傳統(tǒng)的、靜態(tài)的、歷史的財(cái)務(wù)比率度量信用風(fēng)險(xiǎn)的方法已經(jīng)無(wú)法滿足銀行等金融機(jī)構(gòu)和企業(yè)自身對(duì)信用風(fēng)險(xiǎn)進(jìn)行科學(xué)度量和管理的需求。信息技術(shù)業(yè)作為新興產(chǎn)業(yè)發(fā)展迅速,對(duì)國(guó)民經(jīng)濟(jì)的發(fā)展具有巨大的推動(dòng)作用,但是其信用風(fēng)險(xiǎn)相比傳統(tǒng)行業(yè)具有更大的不確定性和波動(dòng)性,信用風(fēng)險(xiǎn)更高,所以對(duì)其信用風(fēng)險(xiǎn)的準(zhǔn)確度量尤為重要。運(yùn)用在國(guó)際上得到廣泛認(rèn)可和使用的KMV模型,并根據(jù)我國(guó)的具體經(jīng)濟(jì)環(huán)境和數(shù)據(jù)的可獲得性對(duì)相關(guān)參數(shù)進(jìn)行計(jì)量方式的確定,最后將模型運(yùn)用到我國(guó)特定的信息技術(shù)業(yè)的信用風(fēng)險(xiǎn)度量之中,這對(duì)提高我國(guó)信息技術(shù)業(yè)的信用風(fēng)險(xiǎn)度量和管理水平有重要的現(xiàn)實(shí)意義。首先,運(yùn)用文獻(xiàn)分析法,在查閱大量相關(guān)文獻(xiàn)的基礎(chǔ)上對(duì)本文的研究背景及現(xiàn)狀進(jìn)行詳細(xì)的介紹,總結(jié)前人研究的優(yōu)點(diǎn)和不足,提出本文研究的主要內(nèi)容;介紹信用風(fēng)險(xiǎn)和信用風(fēng)險(xiǎn)度量的相關(guān)基本理論,運(yùn)用比較分析的方法對(duì)信用風(fēng)險(xiǎn)度量模型進(jìn)行比較,發(fā)現(xiàn)各主要度量模型的優(yōu)缺點(diǎn),選擇KMV信用風(fēng)險(xiǎn)度量模型作為研究模型。其次,對(duì)要用到的KMV信用風(fēng)險(xiǎn)度量模型進(jìn)行詳細(xì)的介紹,包括模型的來(lái)源、理論基礎(chǔ)和計(jì)算原理。再次,運(yùn)用實(shí)證研究的方法將KMV模型運(yùn)用于信息技術(shù)業(yè)上市公司的信用風(fēng)險(xiǎn)度量中,計(jì)算得出信息技術(shù)業(yè)上市公司的違約距離,并用統(tǒng)計(jì)檢驗(yàn)方法對(duì)結(jié)果進(jìn)行適應(yīng)性檢驗(yàn),得出KMV模型可以準(zhǔn)確的度量出我國(guó)信息技術(shù)業(yè)上市公司的信用風(fēng)險(xiǎn)的結(jié)論;最后在研究過(guò)程中發(fā)現(xiàn)模型在度量信息技術(shù)業(yè)上市公司信用風(fēng)險(xiǎn)方面還存在一些問(wèn)題,基于研究發(fā)現(xiàn)從宏觀國(guó)家政策層面、中級(jí)企業(yè)層面和微觀模型本身三個(gè)層面提出改進(jìn)和完善的建議,以期提高模型度量信用風(fēng)險(xiǎn)的適用性,提高信息技術(shù)業(yè)上市公司的信用風(fēng)險(xiǎn)管理水平,促進(jìn)行業(yè)的健康發(fā)展。
[Abstract]:Credit risk is one of the oldest and most basic risk types in the financial market, and it is also one of the most important risk types in our financial market. Even the entire social and economic life has an important impact. As the financial environment becomes increasingly complex, traditional and static, The method of measuring credit risk by historical financial ratio has been unable to meet the needs of banks and other financial institutions and enterprises to measure and manage credit risk scientifically. Information technology industry has developed rapidly as a new industry. It has great impetus to the development of national economy, but its credit risk is more uncertain and volatile than the traditional industry, and the credit risk is higher. Therefore, the accuracy of its credit risk is particularly important. Using the KMV model, which has been widely accepted and used in the world, and according to the specific economic environment and the availability of data in our country, the relevant parameters are determined. Finally, the model is applied to the credit risk measurement of the specific information technology industry in China, which has important practical significance for improving the credit risk measurement and management level of the information technology industry in China. On the basis of consulting a large number of related literature, this paper introduces the research background and current situation in detail, summarizes the advantages and disadvantages of previous studies, and puts forward the main contents of this paper. This paper introduces the basic theories of credit risk and credit risk measurement, compares the credit risk measurement models with the method of comparative analysis, and finds out the advantages and disadvantages of the main measurement models. KMV credit risk measurement model is selected as the research model. Secondly, the KMV credit risk measurement model is introduced in detail, including the source of the model, theoretical basis and calculation principle. The KMV model is applied to the measurement of credit risk of listed companies in information technology industry by using the method of empirical research. The distance of default of listed companies in information technology industry is calculated, and the adaptability of the results is tested by statistical test method. The conclusion is that KMV model can accurately measure the credit risk of listed companies in information technology industry in China. Finally, it is found that there are still some problems in measuring the credit risk of listed companies in information technology industry. Based on the findings of the study, the author puts forward suggestions for improvement and perfection from the macro national policy level, the intermediate enterprise level and the micro model itself, in order to improve the applicability of the model in measuring credit risk. Improve the credit risk management level of IT listed companies and promote the healthy development of the industry.
【學(xué)位授予單位】：哈爾濱商業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F224;F49;F832.51

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