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Evaluation of China’s Financial Risk Using Projection Pursuit Clustering Model and Its Positive Research

DOI: 10.7763/joebm.2014.v2.114

Keywords: Artificial bee colony (ABC) algorithm , China’s financial risk , evaluation index system , projection pursuit clustering (PPC) model.

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Abstract:

The evaluation index system for China’s financial risk (CFR) and its single-index assessment criteria were used to generate sufficient samples. The projection pursuit clustering (PPC) model with a new objective function is applied to evaluate the CFR during 1994 to 2012. Four rules for establishing valid PPC model are put forward in this paper, and the real optimal projection vector coefficients as well as others parameters are obtained by applying artificial bee colony (ABC) algorithm. Positive research shows that PPC model is suited to evaluate CFR, and a valid PPC model as well as six sub-system models for six aspects of CFR is established. The CFR level during 1994 to 2012 generally lies on Proper-safety level except that in 2008 belongs to Risk level. In terms of the six aspects of CFR, the bank risk is the greatest and the second is the risk of economic growth.

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