本文選題：基金評級 + 質(zhì)量檢驗(yàn)��； 參考：《浙江工業(yè)大學(xué)》2013年碩士論文

【摘要】：伴隨著經(jīng)濟(jì)全球化的深入,證券投資基金,銀行次級貸款,股票等資本市場的繁榮,信用評級在我國金融市場中的功能和作用日趨顯現(xiàn)。投資者,監(jiān)管部門對評級機(jī)構(gòu)的依賴程度也逐步提高,因此對理論研究工作者也有了更高的要求。如何檢驗(yàn)信用評級的信息含量；如何提高評級的公信力及投資者的信息質(zhì)量,如何借鑒國外先進(jìn)經(jīng)驗(yàn)并結(jié)合我國國情,建立科學(xué)合理的指標(biāo)體系來提高評級的準(zhǔn)確性等等都成為未來我國信用評級研究的基本問題。 信用評級的功能在于減少信息不對稱,揭示風(fēng)險,而要實(shí)現(xiàn)這一功能,評級質(zhì)量的保證至關(guān)重要�；谀壳按朔N現(xiàn)狀,本文企圖建立一種檢驗(yàn)評級質(zhì)量的方法。評級質(zhì)量的優(yōu)劣可以從兩個方面進(jìn)行衡量：一是評級觀點(diǎn)準(zhǔn)確性,即驗(yàn)證評級機(jī)構(gòu)“高級別低違約”的基本假設(shè)。二是評級觀點(diǎn)的穩(wěn)定性,只有在基本的信用風(fēng)險發(fā)生改變后才會發(fā)生級別變更,由于級別所依賴的基本信用風(fēng)險變化緩慢,因此級別的變動也不應(yīng)劇烈。因此,本文也從這兩個角度切入來對評級機(jī)構(gòu)的評級結(jié)果進(jìn)行質(zhì)量檢驗(yàn)。本文首先采用自組織神經(jīng)網(wǎng)絡(luò)的方法結(jié)合描述基金質(zhì)量特征的指標(biāo)數(shù)據(jù)對基金進(jìn)行等級劃分,將劃分結(jié)果與評級機(jī)構(gòu)的評級結(jié)果進(jìn)行對比,以檢驗(yàn)其準(zhǔn)確性；其次,基于模糊評價法和熵權(quán)法,結(jié)合遷移矩陣對評級機(jī)構(gòu)的評級結(jié)果的穩(wěn)定性進(jìn)行檢驗(yàn),并運(yùn)用隨后兩個月的基金業(yè)績表現(xiàn)來對本文檢驗(yàn)方法進(jìn)行檢測,得出該檢驗(yàn)方法具有良好的預(yù)測性和適用性。 至此,本文從準(zhǔn)確性和穩(wěn)定性兩個角度對評級機(jī)構(gòu)的評級結(jié)果進(jìn)行質(zhì)量檢驗(yàn),這是本文的切入視角創(chuàng)新;本文采用神經(jīng)網(wǎng)絡(luò)的方法進(jìn)行準(zhǔn)確性檢驗(yàn),采用遷移矩陣的方法進(jìn)行穩(wěn)定性檢驗(yàn)這是技術(shù)創(chuàng)新。希望通過本研究方法可以完善我國基金評級質(zhì)量檢驗(yàn)體系,促使評級機(jī)構(gòu)真正發(fā)揮評級機(jī)構(gòu)的風(fēng)險揭示和衡量作用。
[Abstract]:With the deepening of economic globalization and the prosperity of the capital market such as securities investment fund, bank subprime loan and stock market, the function and function of credit rating in our country's financial market is becoming more and more obvious. Investors and regulators are increasingly dependent on rating agencies, so they have higher demands on theoretical researchers. How to test the information content of credit rating, how to improve the credibility of credit rating, how to improve the information quality of investors, how to learn from the advanced experience of foreign countries and how to combine the situation of our country, Establishing a scientific and reasonable index system to improve the accuracy of credit rating has become a basic problem in the future study of credit rating in China. The function of credit rating is to reduce information asymmetry and reveal risk. To realize this function, the guarantee of rating quality is very important. Based on the present situation, this paper attempts to establish a method to test the quality of rating. The quality of ratings can be measured from two aspects: first, the accuracy of rating views, that is, to verify the rating agencies "high-level low default" basic assumptions. Second, the stability of the rating view, only after the change of the basic credit risk will occur level change, because the level of the basic credit risk changes slowly, so the level of change should not be violent. Therefore, this paper also analyzes the quality of rating agencies from these two angles. This paper first uses the self-organizing neural network method to combine the index data describing the fund quality characteristic to carry on the grade division to the fund, carries on the comparison between the division result and the rating agency's rating result, in order to test its accuracy, secondly, Based on fuzzy evaluation method and entropy weight method, combined with migration matrix, the stability of rating agencies' rating results is tested, and the performance of funds in the following two months is used to test the test method of this paper. It is concluded that the test method has good predictability and applicability. So far, this paper carries on the quality test to the rating agency's rating result from two angles of accuracy and stability, which is the innovation of the angle of view of this paper, this article uses the neural network method to carry on the accuracy test, The method of migration matrix is used to test the stability. This is a technological innovation. It is hoped that this research method can perfect the quality inspection system of fund rating in our country, and promote the rating agencies to give full play to the role of risk disclosure and measurement of rating agencies.
【學(xué)位授予單位】：浙江工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP183;F832.51

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本文編號：1978128