企業(yè)碳信貸信用風(fēng)險(xiǎn)的預(yù)測模型與應(yīng)用研究
[Abstract]:In recent years, the concern of environmental protection has been increasing continuously. Since the first proposal of the two sessions in 2010 locked in the development of low-carbon economy, China has been exploring the practical development mode of economic low-carbon development and environmental sustainable development. However, after several years of practice, relying solely on administrative control or pure law enforcement means, our country can not continue to take the path of sustainable development, let alone achieve the goal of energy saving and emission reduction. On the basis of the successful experience of the developed countries in the development of low-carbon economy, our country urgently needs to establish a management system of low-carbon finance to support the low-carbon economy, and the banks are in the main position of the financial industry in our country. If can actively develop carbon credit business, this is undoubtedly one of the effective ways. Firstly, based on the review of the theories of social responsibility, sustainable development and international equatorial principle, this paper analyzes the reasons for the development of carbon credit in commercial banks. Secondly, from the point of view of enterprises, combining the characteristics of carbon credit risk, the paper establishes the enterprise carbon credit risk prediction index system, selects listed companies as the research sample, and collects and collates the relevant data widely. According to the measures for Environmental Credit Evaluation of Enterprises implemented since 2014, and supplemented by the detailed rules for the division of green credit customers' environmental information identification, issued by the Bank of Communications in August 2010, the "operational Manual for Classification of Environmental Protection labels of Bank of Communications", And ask expert's opinion, evaluate get sample company carbon credit risk grade. Furthermore, BP neural network is used to establish carbon credit risk prediction model from time series dimension and cross section data dimension respectively, after network training and simulation and other experimental operations. The reliability of the two models is analyzed and the prediction results of the two models are evaluated. Finally, the prediction model is applied to practical case analysis, and it is concluded that the prediction model of time series dimension has more practical application value than that of cross-section data dimension.
【學(xué)位授予單位】:南昌大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2015
【分類號】:F832.4;TP183
【參考文獻(xiàn)】
相關(guān)期刊論文 前9條
1 周黃斌;周永華;朱麗娟;;基于MATLAB的改進(jìn)BP神經(jīng)網(wǎng)絡(luò)的實(shí)現(xiàn)與比較[J];計(jì)算技術(shù)與自動化;2008年01期
2 蔣文燕;朱曉華;蔡運(yùn)龍;陳晨;;基于不同空間尺度的旅游客源預(yù)測模型對比研究[J];旅游學(xué)刊;2007年11期
3 楊明;常坤;;創(chuàng)新國內(nèi)商業(yè)銀行綠色信貸評級模型的研究[J];華北金融;2011年08期
4 何德旭;張雪蘭;;對我國商業(yè)銀行推行綠色信貸若干問題的思考[J];上海金融;2007年12期
5 李繼尊;;中國能源預(yù)警模型及其預(yù)警指數(shù)的創(chuàng)建[J];中國石油大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年06期
6 李兵;曾濤;張婧璇;蔣亞婷;蘇丹;;基于AHP的電信行業(yè)業(yè)務(wù)持續(xù)性風(fēng)險(xiǎn)預(yù)測模型研究[J];數(shù)學(xué)的實(shí)踐與認(rèn)識;2013年16期
7 張軍;黃子杰;;BP神經(jīng)網(wǎng)絡(luò)模型的原理及在心理學(xué)領(lǐng)域的應(yīng)用[J];現(xiàn)代預(yù)防醫(yī)學(xué);2006年10期
8 曾波;;基于核和灰度的區(qū)間灰數(shù)預(yù)測模型[J];系統(tǒng)工程與電子技術(shù);2011年04期
9 張晟;;商業(yè)銀行推行低碳信貸的實(shí)踐、困境與對策[J];時(shí)代金融;2011年36期
相關(guān)碩士學(xué)位論文 前2條
1 陳龍;我國商業(yè)銀行碳信貸風(fēng)險(xiǎn)管理研究[D];武漢理工大學(xué);2010年
2 楊燁萍;綠色信貸的機(jī)理及激勵(lì)機(jī)制研究[D];福建農(nóng)林大學(xué);2010年
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