基于神经网络的金融风险评估研究.doc

毕业论文中文摘要 基于神经网络的金融风险评估研究 摘 要： 20世纪80年代末以来，随着经济全球化趋势的不断蔓延，世界金融市场无疑面临各种各样的挑战，对于金融风险的评估和管理的重要性日益加强。 我国的市场经济处于由计划经济向市场经济转轨的关键时刻，作为经济总枢纽的商业银行在运营过程当中无时无刻不面临着各种各样的金融风险，并随着经营业务领域和面向的群众普及率大幅开阔与提高，可谓步步如履薄冰。世界银行对全球银行业危机的研究指出,信用风险的管理不善是导致商业银行的风险防范和控制出现危机的主要原因 毕业论文外文摘要 Title Financial risk assessment studies based on neural network Abstract Since the late 1980s, with the trend of economic globalization continues to spread, the worlds financial markets will undoubtedly face a variety of challenges, increasingly the importance of financial risk assessment and management. Chinas market economy is in a critical moment of transition from a planned economy to a market economy, which as the economic hub of commercial banks operating in the process all the time facing a variety of financial risks, and with the popularity of the area of operations and for the masses rate significantly broaden and improve, can be described step by step in perpetuity. The World Bank study pointed out that the global banking crisis, mismanagement of credit risk leading commercial banks risk prevention and control of the main reasons of the crisis. Abroad in the use of data mining technology for credit risk assessment, widely used prediction model based on statistical discrimination method, the common model: multiple discriminant analysis model (MDA), Logit analysis model, the nearest neighbor method, the classification tree method. The above-mentioned methods are linear model analysis method is simple, low computational complexity, but overly stringent restrictions, and does not apply to the current economic situation in our country. Thus, I chose to use a neural network model, Chinas commercial banks credit risk assessment analysis. Neural network model for any function approximation ability, learning ability, the mapping between the self-organizing and adaptive capacity can be more precise description of factors. And the advantage of the neural network model in the applic