Our Country’s Precious Metals Market Risk Measurement Comparison And Empirical Analysis

In recent years, due to frequent wars and volatile political situation in the world, additionally the recession of the global economy and stock market collapse and inflation continued in our country, Precious metals such as gold and silver popular because of the safety function. However, our country’s precious metals market relatively late built, it is not perfect. Investing in our country’s precious metals market is easy to encounter the risk of price volatility. Therefore, the comprehensive analysis on the risk of our country’s precious metals market and the effective measure of risk for the healthy development of our country’s precious metals market and investors of precious metals investment operation and risk management have important practical significance.The traditional risk measurement method VaR does not meet the coherent rule, cannot measure tail risk. ES satisfy the coherent rule of risk measurement, but it used the single risk weighting when calculated the tail risk that is different with the reality which people have different attitudes of different risk levels. Then, Spectral Risk Measure (SRM) which satisfy coherent rule of risk measurement, and can be based on user’s degrees of risk aversion to construct the subjective risk weighting arises at the historic moment, and gradually get the attention of scholars. GARCH model and SV model as ideal model of financial market volatility widely used in the calculation of dynamic VaR and ES. It can also be used for the calculation of SRM.Based on the GARCH model and SV model of VaR, ES and SRM measure risk of our country’s precious metals market as the core of this paper, to find a better risk measurement model.Firstly this article theoretical analysis of the current situation of the development and the risk of our country’s precious metals market risk and the necessity of our country’s precious metals market risk measurement. Then through the theoretical proof that SRM has the VaR and ES incomparable advantages, it satisfies the coherent rule of risk measurement and introduced a weighting function embodies the subjective risk aversion of investors. Then introduces GARCH model and SV model, establish the yields is normal distribution, t distribution, GED distribution assumptions based on GARCH model and SV model of dynamic VaR, ES and SRM. The 5 varieties of precious metals trading in the Shanghai gold exchange and Tianjin precious metals exchange as the empirical object, get the time-varying variances of VaR, ES and SRM, through LE statistics comparison come to a conclusion, when the VaR fails, there is always the risk aversion coefficient k to take the appropriate value let SRM average more close to the mean of the actual loss than VaR and ES, the k value range according to the different kinds of the types of precious metals, yield distribution hypothesis, volatility model is different. After test, based on SV-GED model, k value between 32 and 33 of SRM is a relatively optimal model of our country’s precious metals market risk measurement. At the same time, by comparing the size of platinum which is the common varieties in Shanghai gold exchange and Tianjin precious metals exchange market VaR, ES and SRM, learned that the risk of Tianjin precious metals exchange market is more than the Shanghai gold exchange market. Finally, according to the results of theoretical and empirical studies provides some feasible suggestions to improve the precious metals market construction, varieties of precious metals trading margin level requirements, precious metals investment and risk management.