模糊支持向量机在金融风险预警中的应用

发布时间：2018-06-07 02:24

本文选题：金融风险预警 + 统计学习理论　；参考：《成都理工大学》2012年硕士论文

【摘要】：随着世界各地金融危机不断爆发，使得金融危机联动性和破坏性越来越明显因为金融风险与金融危机之间现实关系，，所以金融风险具有引发金融危机的前奏和开端;金融危机又是金融风险动态积累的极限后果因此，金融风险预警研究倍受各国政府和公众的普遍关注而且研究结果将直接关系到对金融市场状况的正确认识和判断，从而提出防范金融风险措施，抵御国际金融风险的冲击，将金融风险控制在经济可以承受的范围之内，对促进我国经济和金融健康稳定的发展，有着重要的现实意义本文以金融风险预警理论和模糊支持向量机理论为基础，首先根据国内外学者在金融风险预警指标体系领域内的研究成果，在比较充分的了解该领域的现状和研究成果的基础上，选择了适合中国实际情况的金融风险预警指标，又由于传统预警方法往往囿于专家经验和简单的数学模型，难于处理高度非线性模型，无法满足宏观金融预警的客观要求本文选择了模糊支持向量机算法及其变形算法模型，对选取的预警指标体系的现实性与合理性进行了实证检验，对我国的未来年度金融风险进行了成功的预警预测，并得出该方法的有效性
[Abstract]:With the continuous outbreak of financial crisis in various parts of the world, it is more and more obvious that the linkage and destruction of financial crisis is more and more obvious because of the realistic relationship between financial risk and financial crisis, so financial risk has the prelude and beginning of triggering financial crisis. The financial crisis is the ultimate consequence of the dynamic accumulation of financial risk. Therefore, the early warning of financial risk has attracted the widespread attention of the governments and the public of all countries, and the research results will be directly related to the correct understanding and judgment of the financial market situation. Therefore, it is of great practical significance to put forward measures to prevent financial risks, to resist the impact of international financial risks, and to control financial risks within the range of economic tolerance, which will promote the healthy and stable development of China's economy and finance. Based on financial risk early warning theory and fuzzy support vector machine theory, this paper firstly bases on the research results of domestic and foreign scholars in the field of financial risk early warning index system. On the basis of fully understanding the present situation and research results in this field, the paper chooses the financial risk warning index suitable for the actual situation in China, and because the traditional early warning method is often limited to expert experience and simple mathematical model, It is difficult to deal with the highly nonlinear model and can not meet the objective requirements of macro financial early warning. This paper selects the fuzzy support vector machine algorithm and its deformation algorithm model, and makes an empirical test on the feasibility and rationality of the selected early warning index system. In this paper, the financial risks in the future in China are forecasted successfully and the effectiveness of this method is obtained.
【学位授予单位】：成都理工大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TP18;F832

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