基于ARMA模型的商业银行信贷风险预测分析

发布时间：2018-07-10 14:53

本文选题：商业银行 + 银行信贷　；参考：《兰州大学》2014年硕士论文

【摘要】：随着我国商业银行信贷业务的不断壮大,信贷风险问题接踵而至,一些贷款难以回收,信任机制被严重威胁。因此,基于ARMA预测方法的商业银行信贷风险的研究,能更好的预测商业银行未来信贷风险的趋势,以便于及时采取措施,对商业银行的健康发展具有长期的指导意义和作用。本文分析商业银行信贷风险的现状,认为不良贷款率偏高是造成商业银行信贷风险的主要原因。我国银监会也将不良贷款率作为监管商业银行信贷风险的一个极为重要的指标,因此本文通过分析不良贷款率未来趋势来预测商业银行信贷风险。选取了招商银行和浦发银行作代表,通过Matlab编程,以银行的每个季度的不良贷款率的数据作为一个时间序列进行分析、建模、检验和预测,最后针对此问题提出政策和建议。
[Abstract]:With the development of the credit business of commercial banks in China, the problem of credit risk comes one after another, some loans are difficult to recover, and the trust mechanism is seriously threatened. Therefore, the research of commercial bank credit risk based on ARMA forecasting method can better predict the future trend of commercial bank credit risk, in order to take measures in time and have long-term guiding significance and function for the healthy development of commercial bank. This paper analyzes the present situation of commercial bank credit risk, and thinks that the high non-performing loan ratio is the main reason of commercial bank credit risk. The CBRC also regards the non-performing loan ratio as an extremely important indicator to supervise the credit risk of commercial banks, so this paper predicts the credit risk of commercial banks by analyzing the future trend of non-performing loan rate. This paper selects China Merchants Bank and Pudong Development Bank as representatives, and takes the data of non-performing loan ratio in each quarter of the bank as a time series to analyze, model, test and forecast by Matlab programming. Finally, the paper puts forward some policies and suggestions to solve this problem.
【学位授予单位】：兰州大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F224;F832.4

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