Research On Risk Measurement Of Open-ended Fund In China

Chinese fund industry started late,but is developing rapidly.By the end of 2018,the total fund scale in China has exceeded 50 trillion RMB.Although Chinese fund development speed is fast,the scale expansion is large,but because of the opening up of Chinese fund industry,foreign fund companies continue to enter the Chinese fund market,which has brought rare opportunities for the development of Chinese fund industry,but also brought severe challenges.The entry of foreign fund companies will help Chinese fund companies learn advanced fund management experience and improve their risk management ability.For the fund industry,it will help form a diversified competitive pattern and promote the stable development of the fund industry.Compared with foreign-funded fund companies,the risk awareness and risk control level of Chinese fund companies are relatively low.And Chinese fund companies has low emphasis on risk and compliance.Therefore,if Chinese fund companies do not learn advanced risk management concepts and form a sound risk management system,in the future,Chinese fund companies will not be able to compete with other countries' fund companies.Traditional risk measurement methods including nominal volume method,the sensitivity method and volatility,due to measure the risk of oneness and applicable scope of narrow,with the expansion and complexity of fund market,the more obvious its defects are exposed,and value at risk,which can reflect various market risks and is easy to calculate and understand,has gradually become the mainstream risk measurement method.VaR is a method that can comprehensively measure the market Risk of complex securities portfolio,and has a clear theoretical guiding significance in Risk measurement and management.Traditional VaR measurement methods include historical simulation method,monte carlo simulation method and variance-covariance simulation method,which all rely on a large number of historical data and assume that the data distribution is normal.However,in practical applications,the above two conditions are difficult to meet.GARCH-VaR model can well fit the characteristics of high-peak and thick-tail and volatility agglomeration of financial time series,and has been applied more widely due to its fewer parameters,high fitting degree and strong practicability.Extreme events often occur in the financial market,and the impact and harm of extreme events on the financial market is huge,so the measurement of extreme risks is of great significance.However,the risk error of financial market under extreme events of GARCH-VaR is likely to be larger,and the extreme value theory(EVT)provides a new method for measuring the risk under extreme market conditions.Extreme value theory is the study of the extreme value distribution,and focus on the tail of distribution,have nothing to do with the data distribution assumption,using only the data itself to show its distribution characteristics,so it is a good way to fitting of the end of the financial time series,in recent years,the application of extreme value theory in the financial markets are more and more widely.However,tail data selected by the extreme value theory need to be independent of each other,which will also be limited in practical applications.GARCH model can be used to filter the data first,and then extreme value theory can be used to fit the tail of the distribution.On the basis of previous studies,this paper,based on the characteristics of financial time series,such as high peak,thick tail and fluctuation agglomeration,aims to estimate fund market risks more accurately.In this paper,the garch-var model based on the overall data is established at first,and then the extreme value theory(EVT)is introduced for the fund market risk in extreme cases.It construct that garch-evt-var model based on the tail of data distribution,and compare the estimation effect of two models.In the empirical analysis,36 open-end funds were selected as samples,including 12 stocks,12 mixed funds and 12 bonds,respectively,and the GARCH-VaR model and GARCH-EVT-VaR model were used to estimate the VaR of different types of sample funds at the two confidence levels of 95%and 99%,and the accuracy of two models was compared using the Kupiec failure frequency test.Results show that the 95%confidence level,the GARCH-VaR performance better,GARCH-EVT-VaR model is easy to underestimate risk,in the 99%confidence level,the GARCH-EVT-VaR model performance better,GARCH-VaR easy to overestimate the risk.It's also clear that the GARCH-VaR has a better chance of capturing the volatility of the fund day,but that's just low levels of confidence,and when the confidence is high,the model underestimates the risk.And extreme value theory can really solve the model in high confidence level of risk estimation errors.