| 基于稀疏主成分和熵值法的中国上市银行风险评价 |
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| 引用本文：喻胜华，阳林芝.基于稀疏主成分和熵值法的中国上市银行风险评价[J].湖南大学学报社会科学版,2019,(2):77-81 |
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| 中文摘要:利用稀疏主成分分析方法和熵值法对中国25家上市银行风险进行多指标的量化分析和综合评价。在选择惩罚系数λ1时，同时兼顾了主成分的稀疏度和主成分对于原解释变量的解释程度。结果显示，我国上市银行中，国有商业银行风险系数最低，其次是城市商业银行，股份制银行风险系数最高。最后，根据不同风险类型给出了防范建议。 |
| 中文关键词:稀疏主成分 熵值法 上市银行 风险评价 |
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| Risk Assessment for Listed Banks in China Based on Sparse Principal Analysis and Entropy Method |
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| Abstract:In this paper, sparse principal component analysis and entropy method are used to quantify and evaluate the risk of 25 listed banks in China. When choosing penalty coefficient λ1, the sparsity of principal component and the percentage of explained variance of principal component to the original explanatory variables are both taken into account. The results show that among the listed banks in China, the risk coefficient of state-owned commercial banks is the lowest, followed by urban commercial banks, and the risk coefficient of joint-stock banks is the highest.Finally, we give some suggestions according to different types of risks. |
| keywords:sparse principal analysis entropy method listed bank risk assessment |
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