The Research Of Chinese Gold Futures Market Volatility And Risk Measurement

On January 9, 2008, gold futures, as a Chinese financial futures pioneer, attracted many people’s eyes from the date of the initial public offering, but just a few months, the main gold futures contracts appeared many gaps, the market fluctuated intensely, many investors are losing money and walked out, the liquidity in the market is poor. With access to commercial banks and the promulgation of night trading system, the participants in Chinese gold futures market increased gradually, market liquidity was enhanced greatly. However, the volatility in the market was still very severe under the influence of dollar price and international events. In this context, we need to strengthen the analysis of the volatility and risk in this market. The purpose of this paper is to draw lessons from domestic and foreign scholars on the cutting-edge research methods of the financial market volatility and risk measurement, analyze and research Chinese gold futures market from different perspectives, build a relatively complete research system.First of all, this paper summarizes researches about financial market volatility and risk measurement, finds that the related research about gold futures in China has some shortages. Then, to analyze gold futures market in theory, this paper introduces a variety oftheoretical models of volatility characteristics in financial market and risk-quantification. What’s more, this paper selects main gold futures contracts as the research object, adopts GARCH(selects maximum likelihood to estimate parameters) and SV Model(selects MCMC Method to estimate parameters) based on normal distribution and t distribution, then adds "leverage effect", trading volumeand open interest gradually to depict the characteristics of Chinese gold futures market volatility. We can get three conclusions: first, Chinese gold futures market volatility has persistence and concentration, but its asymmetry is not obvious, this can be explained by participants’ construction and the basic characteristics of the futures market. Second, there is a positive relationship between trading volume and volatility. On the contrary, open interest is negatively related to the market volatility. Third, the SV Model is more suitable for depicting the fluctuation characteristics of the gold futures market. In the end, we introduces the conditional variances that calculated by volatility model to VaR Method, and choose the "optimum" risk measurement model for different types of investors by failure tests.