Assessing financial vulnerabilities: A case study of China’s banking and financial system

factor analysis

Factor analysis was first developed by the British psychologist Charles Spearman, who proposed in 1904 that the basic idea of ​​factor analysis is to group the original variables. These variables should be grouped according to their correlation size so that the correlations between variables in the same group are high and the correlations between variables in different groups are low. Each group of variables represents an underlying structure and an overarching unobservable variable called a common factor. For a particular problem to be studied, the original variable can be divided into two parts. some unmeasurable linear functions or common factors, and special factors that are unrelated to public factors (Qin and Lin, 2021; Kim et al., 2020a, 2020b).

Assume that there is n samples, each sample observes p There is a strong correlation between the indicators. p indicator.To facilitate research, the observed data of the sample are standardized, and the standardized variables are X_I (I= 1, 2,…, p) as the evaluation index, F_j (j= 1, 2,…, meter) as the common factor. ε_k (k= 1, 2,…, p) represents a special factor, and the specific model for factor analysis is as follows.

where is the common factor F_j (j= 1, 2,…, meter) are independent of each other and cannot be measured. An element that appears in the expression of the original variable. Special factors and common factors are also independent of each other. be_ij is the factor loading. The greater the absolute value, the greater the degree of dependence between them. X_I and F_j.

Indicators of banking system vulnerability

The selection of metrics is key to accurately and comprehensively assessing banking system vulnerabilities. A study by Gobert et al. (2002) focused on the liquidity ratio indicators of the banking system regarding the issue of financial fragility. It also argued that liquidity constraints were an important factor in causing the crisis and resulting in financial vulnerabilities in financial institutions. Karadima and Louri (2020) pointed out that high non-performing loan rates exacerbate banks’ vulnerability and have a strong negative impact on economic development. Capital adequacy ratio is an important indicator of a bank’s risk management and avoidance ability. Many countries, while opening their financial markets, face varying degrees of the threat of financial vulnerabilities. Therefore, capital adequacy has become an increasingly important issue for the banking industry from the perspective of safe business operations. As stated by Asteriou and Spanos (2018), a high performance of capital adequacy ratio maintains the stability of the financial system. Banks are improving security and liquidity, but profitability cannot be ignored. This can be expressed in terms of average return on assets. Therefore, this paper uses average return on assets, equity ratio, liquidity ratio, and non-performing loan ratio as indicators to measure the vulnerability of the banking system.

Indicators of financial system vulnerability

Discussions about the fragility of financial systems have always attracted significant attention from the theoretical community. Segmenting the financial system and monitoring financial risks from different subsystems is a central issue. Eichman et al. (2017) investigate financial vulnerabilities from the stock, real estate, and bond market subsystems and highlight that there are different views on the selection of specific evaluation indicators. Hamdaoui and Maktouf (2020) refer to the work of other scholars and measure financial fragility using indicators such as international capital flows, inflation, real exchange rate, money supply M2 ratio, and supervisory diffusion. . Kaminsky (2006) mainly selected key indicators such as the ratio of fiscal deficit to GDP, the real excess of M1, the ratio of M2 to foreign exchange reserves, and the ratio of external debt to imports. Additionally, Kaminsky subdivided two subsystems within his model: stock market and bank credit, making the model more comprehensive. In accordance with the theories of the above scholars, combined with the characteristics of China’s financial system, this paper establishes a financial system vulnerability assessment model from the four subsystems of economic environment, financial market early warning, financial surveillance, and financial exports. is focused on. Directional. Among these, we refer to common international standards and foreign experts to determine the boundaries of some evaluation indicators and the weight settings of subsystems (Graciela L Kaminsky, 2006). For other indicators, average values ​​are calculated based on past data, and the index range is determined according to the degree of deviation from the average value. Table 1 provides specific information.