A Study On The Risk Assessment Of The Money Market Funds Like Yuebao

Monetary Fund has an explosive growth of size in 2013. There’s a large number of subscription of traditional money market funds, Innovation funds, and short-term financial debt funds. Benefited from lack of money, the annualized rate of return since the third quarter has remained at around 5% in the second half of 2013, and their mobility and security seems to be better than the bond funds. Therefore, a large number of investors put their money in the money market funds like Yuebao instead of bond funds.The money market funds like Yuebao meet the people’s investment needs and the requirements of regulatory agencies in encouraging of innovation and promote the development of the financial market. However, due to the late start of China’s financial market and the short time of internet financial development, the money market funds like Yuebao are facing risk diversification and many other problems. At this time, we must strengthen risk management and control of risk prediction and resolution. VaR in the world have been using for more than ten years, and it plays a significant effect for the management and control of risk. Its deficiency leads to more expansion of models that can compensate for the defect to keep up with the pace of market development. At this time, the use of VaR in risk assessment of the money market funds like Yuebao promotes the healthy development of Internet-based financial products, financial innovation, financial reform and improves the market structure.Firstly, we talk about risk. Secondly, we analyze the current situation of the money market funds like Yuebao about the growth and current problems. Therefore, to calculate VaR for risk management is a priority. Then, we talk about VaR and ARCH modles.Finally, we select Yuebao, Weixinlicai, Baidubaizuan, Wangyixianjinbao, Suninglingqianbao to calculate VaR. But the results of using parameter method are not good for risk assessment and control. Then we create the ARCH model of normality, t, GED distribution to predict the next day’s VaR value to compare the calculating results with the actual results. The final conclusion is that, ARCH models are better than parameter method is superior for different Internet monetary funds. And the result of three distributions is different. In general, the GED distribution is best. At last, we find that Baidubaizuan has a high rate of return with high risk, and Weixinlicai is the worst while the remaining three are in the middle.