The WES Method And Its Application In Risk Measurement

As one of the three pillars of modern financial theory, financial risk management has an extremely important significance. Considering financial globalization, the diverse and complex financial derivatives and the high leverage of institutions, financial risk management is more important. Since2011, people concern about credit risk of the real estate industry which triggered by the policy of restrictive purchase and the falling stock market. This article introduces Zhiping Chen, Li Yang (2011)’s WES risk measure and the measure meets the monotonicity and convexity. Compared to the coherent risk measure it takes into account the liquidity risk and in line with the real laws of the market. The empirical results show that this method can effectively measure the risk of the two field and also in line with investors’ habits.This article briefly introduce the background of the risk measurement and its development, including the mean-variance method, VaR method, coherent risk measure, the concept of convex risk measurement and analysis their advantages and disadvantages. Then, describe the basics WES method’s definition, nature and the methods for calculating in detail. WES then be applied to the credit risk measurement of real estate. listed companies achieved good results, the model have a reliable results to the different scale of companies’ credit risk. Compare to another popular KMV model, WES model forecast results are consistent with KMV. Due to the lack of a complete database of default, KMV method in our country cannot get a more accurate expected default (EDF) at this stage, but by the distance to default, which is difficult to visually determine the company’s risk. WES method can explicitly calculate the future extreme cases losses, and also the company’s ability to pay its debt in the case of a default. So, the WES method is a strong intuitive and practical method. At last WES model combined with GARCH (1,1) forecast the Shanghai index risk, which considering the risk aversion of investors. This model has better problem-solving and stock volatility than the VaR and ES models. Through empirical test, the fine nature of the WES model has been reflected and it also achieved good application effects.