Principal Components As A Measure Of Systemic Risk

Financial crisis that brings a terrible beating to the global economy, caused by the United States subprime mortgage crisis in the 2007, and global financial markets remain severely strained, it is highly likely that some of these large banks will be insolvent, this illustrate that the potential systemic risk is huge, which we should pay our close attention to. Thus, the complicated relation makes risk be contagious between banks has become a hot issue for scholars and supervision department. For a bank-based country like China, banking industry plays a strategic role in the national economic activates. Therefore, the study on the systematic risk of banks has an important meaning.As a result of the high dimensional of data on the open market in listed banks, this paper uses PCA (principal component analysis) to study the systemic risk in banking. The main idea of principal component analysis is dimensionality reduction and maintains the variance contribution rate of the principal component is the largest, which made the most important information of data is preserved. The CAR value is by analyze the return on assets of the listed bank used principal component analysis; it is about the cumulative variance proportion of the first principal components. The bigger of variance of the first principal component, the higher of interpretation of the original variables, which retention of information of the original variables, that is, the listed banks asset returns is explained by first principal components. If the banks become closer, the systemic risk in banks will be higher. Due to the difficult of obtaining return on assets of the listed bank over the open market, as a result, this dissertation utilizes KMV model to give us a more authentic and accurate of the return on asset. In the meantime, this study also found that PC load is to measure the sensitivity of the systematic risk in specific bank.Therefore, a representative sample of 14 listed bank was selected from Oct 2007 to Mar 2014, and utilizing the principal component analysis to carry on research.The empirical research finds:U.S. financial crisis led to the CAR value at high levels among the banking industry. As a result of effective actions about the easy-money policy and positive finance policy in China, the CAR value went slowly in 2009. However, because of the excessive credit and shadow banking system since 2012, the CAR value is slowly sinking in waves, this is in accordance with the actual circumstance, which shows that CAR value had good identifiably ability of the banking systemic risk.