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随着社会的发展,中小企业竞争越来越激烈,融资担保机构是借鉴企业融资问题的重要保障,因此也是越来越受到重视。就目前的情况来看,为了进一步促进中小企业的发展,融资担保行业需要进一步加强中小企业的融资的控制,在实际过程中不断进行产品结构的调整,同时进一步扩展担保的业务,从而在满足企业的需求下促进行业的发展。基于此,通过定量分析中小企业信用担保的融资风险指数,提高对市场的风险规避能力。传统方法采用主成分分析模型,需要大量的历时数据作为风险评估的参考,当经验知识缺乏的情况下对风险指数的预测和评估性能不好。提出一种基于零冗余度主成分分析的中小企业信用担保融资风险评估定量分析模型。对风险指数时间序列进行数据融合和特征提取分析,通过分析降低数据维数和冗余度,实现对融资过程中的汇率波动、利率上涨、通货膨胀、国际贸易政策等风险指数进行定量预测。仿真结果表明,该定量分析模型对中小企业信用担保融资风险的预测精度较高,评估准确。
With the development of society, the competition among SMEs is getting fiercer and fiercer. The financing guarantee agency is an important guarantee to draw lessons from the issue of corporate finance. Therefore, it is also paid more and more attention. In the current situation, in order to further promote the development of small and medium-sized enterprises, the finance guarantee industry needs to further control the financing of SMEs. In the actual process, the Company constantly adjusts the product mix and at the same time further expands its guarantee business so as to meet the needs of enterprises The demand of promoting the development of the industry. Based on this, by quantitative analysis of SME credit guarantee financing risk index, to improve the risk aversion to the market. The traditional method uses the principal component analysis model, which requires a large amount of time-lapse data as a reference for risk assessment. When the empirical knowledge is lacking, the prediction and evaluation of risk index are not good. This paper presents a quantitative analysis model of SME credit guarantee financing risk assessment based on zero-redundancy principal component analysis. Data fusion and feature extraction of time series of risk index are carried out. By analyzing the data dimension and redundancy, the risk index such as exchange rate fluctuation, interest rate rise, inflation and international trade policy are quantitatively predicted. The simulation results show that the quantitative analysis model has a high prediction accuracy and accurate evaluation for SME credit guarantee financing risk.