节点文献
基于BP神经网络的农村金融经营风险预警模型研究
Study on the Rural Financial Operating Risk Early Warning Model Based on BP Neural Network
【作者】 徐新方;
【导师】 曾国平;
【作者基本信息】 重庆大学 , 产业经济学, 2010, 硕士
【摘要】 近年来,我国农村金融体制改革取得了长足进展,农村金融对推动国民经济健康发展特别是农村经济的发展发挥了重要作用。但是,农村金融整体风险特别是经营风险问题仍然十分突出,成为制约新农村建设顺利推进的一大障碍。在深入研究金融风险管理理论、风险评估预测防范理论的基础上,结合农村金融操作实务,本文综合采用了因果分析、系统分析、实证分析和模型分析等多种方法,探索农村金融风险实时预警的方法与技术,将BP神经网络应用于农村金融经营风险预警,构建了基于资本风险、信用风险、流动性风险、收益风险和利率风险五大类别、二十一个二级指标的农村金融经营风险实时预警指标体系和相应的预警模型,并进行了仿真模拟。本文的研究成果对于进一步完善金融机构特别是农村金融机构经营风险监测指标体系,丰富金融风险预警基本理论,提升农村金融机构的风险防范化解能力和管理效率,保证社会主义建设新时期农村金融机构的又好又快发展,具有重要的理论价值和现实指导意义。
【Abstract】 In recent years, China’s rural financial system reform has made considerable progress. Rural finance has played an important role in promoting National economy, especially the rural economy. However, the overall risk of rural finance in particular operating risk is still serious, and becomes a major obstacle to the new rural construction.The dissertation based on financial risk management theory and evaluation theory and practice of rural financial operations, integrated use of systems analysis, causal analysis, empirical analysis and model analysis method, based on China’s rural financial system in depth understanding of operating risks, in sum, summarize, compare and reference index system of monitoring domestic and foreign financial institutions based on research to detect the risk indicators of rural financial management system and early warning. BP neural network is applied to rural financial risks early warning system, and then, the dissertation designs the rural financial operating risk indicators in early warning system and the corresponding warning model. The index system contains five major categories and 21 secondary indicators such as capital risk, credit risk, liquidity risk, income risk and interest rate risk. The results of this dissertation is of great importance to further improve the financial institutions, especially of rural financial institutions operational risk monitoring index system, the basic theory of extensive early warning of financial risks, improve rural financial institutions in risk prevention and management to resolve the efficiency of the new period of socialist construction to ensure that rural financial institutions sound and rapid development, has important theoretical value and practical significance.
【Key words】 Rural Finance; Operating Risk; Early Warning Model; BP neural network;