An Index System for Financial Safety of China

Abstract: This paper combines a synthetic index system by the variables and evaluates China’s financial safety through the change of indexes in a comprehensive way. First of all, it builds the financial industry evaluation index system composed of 25indicators in terms of the operation of the financial industry and external economic environment and particularly takes into consideration factors which might trigger liquidity risks such as off-balance-sheet business, interbank business and shadow banking; then it selects 10 indicators to conduct empirical analysis and identifies the indicator weight through principal component analysis; finally it combines the financial safety indexes through the linear weighted comprehensive evaluation model.
Design/methodology/approach: Synthesis of indexes is made by constructing a proper comprehensive evaluation mathematical model, integrating a number of evaluation indexes into one comprehensive evaluation index and then obtaining corresponding comprehensive evaluation results. In this paper, it selects 10 indexes to conduct empirical analysis and identifies the index weight through principal component analysis; finally it combines the financial safety indexes through the linear weighted comprehensive evaluation model. Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. PCA was invented in 1901 and was later independently developed (and named) by Harold Hotelling in the 1930s.
Findings: From 2003 to 2013 China’s financial safety indexes fluctuated. From 2003 to 2007 indexes rose, which indicates China’s financial safety status gradually improved; from 2007 to 2009 indexes declined, which indicates due to the impact of subprime crisis, China’s financial safety status took a turn for the worse; from 2009 to 2012 indexes rose, which indicates the external environment improved so did China’s financial safety status; from 2012 to 2013 indexes declined because due to the rapid development of banks’ financial products and trust products, banks’ off-balance-sheet assets and liquidity risks increased. The changes of financial safety indexes are generally identical with those of China’s financial safety status.
Research limitations/implications: In the empirical analysis part, this article tries to selective 24 indicators synthetic index of China's financial security, but due to some of the indicators data acquisition is relatively difficult, can only Selective 10 of 25 indicators and gather the annual data of 10 indicators from 2003 to 2013 to synthetic index. The information of eliminated indicators cannot be reflected in the index. Index change also does not reflect of the risk from these indicators. In order to make up for the above limitations, this paper is mainly to introduce and analysis our latest financial institutions business trends associated with these eliminated indicators to get the conclusions more reliable.
Originality/value: The aim of this research is to estimate financial safety of China with the application of the index of financial safety of a country using the annual data of 2003-2013. Through synthetic index of financial security measure the risks of China's financial system, provide the basis for the government macro financial policy. The Originality of the paper is mainly manifested in incorporating factors which have made important impacts on China’s financial safety in recent years, but have not been taken into consideration in the existing studies into the newly constructed financial safety index system. For example, some factors that cannot be controlled easily might have huge hidden risk hazards. To be more specific, factors such as off-balance-sheet business, interbank business and shadow banking might trigger liquidity risks. In this way, the research results will be more practical.
Keywords: financial safety indexes, financial safety evaluation, principal component analysis
Author: Xiaojun Jia, Menggang Li
Journal Code: jptindustrigg150066

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