發(fā)布時(shí)間：2018-02-20 06:21

  本文關(guān)鍵詞： 信貸風(fēng)險(xiǎn) 投入產(chǎn)出網(wǎng)絡(luò) 行業(yè)地位系數(shù) KMV模型　出處：《當(dāng)代經(jīng)濟(jì)科學(xué)》2017年03期 　論文類型：期刊論文

【摘要】：近年來,我國商業(yè)銀行不良貸款率升高,信貸投放面臨著行業(yè)和客戶的選擇困難。但是,現(xiàn)階段我國仍缺乏關(guān)于行業(yè)資金投放的理論和方法。本文利用復(fù)雜網(wǎng)絡(luò)的方法研究經(jīng)濟(jì)系統(tǒng)中行業(yè)的信貸風(fēng)險(xiǎn),提出地位系數(shù)這一指標(biāo)來衡量局部行業(yè)間投入產(chǎn)出網(wǎng)絡(luò)的對稱性。然后,考察地位系數(shù)與KMV模型中行業(yè)違約距離之間的負(fù)相關(guān)性,并根據(jù)宏觀經(jīng)濟(jì)以及國家政策對低風(fēng)險(xiǎn)和高風(fēng)險(xiǎn)行業(yè)的地位系數(shù)進(jìn)行對比說明。最終,提出了切實(shí)可行的政策建議。
[Abstract]:In recent years, the non-performing loan ratio of commercial banks in China has increased, and the credit supply is facing difficulties in the choice of industry and customers. At the present stage, our country still lacks the theory and method of industry capital investment. This paper uses the method of complex network to study the credit risk of the industry in the economic system. The status coefficient is proposed to measure the symmetry of the input-output network among local industries. Then, the negative correlation between the status coefficient and the default distance in the KMV model is investigated. According to the macroeconomic and national policies, the status coefficients of low risk and high risk industries are compared and explained. Finally, practical policy suggestions are put forward.
【作者單位】： 北京大學(xué)經(jīng)濟(jì)學(xué)院;浙江大學(xué)寧波理工學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目“基于數(shù)據(jù)挖掘-Copula理論的銀行信貸中觀組合管理研究”(71201143)
【分類號(hào)】：F832.4
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本文編號(hào)：1518972