Empirical Analysis of Fund Index Volatility Based on Conditional Heteroscedasticity Model

Abstract

: In order to study the changes of China's fund market, this paper carries out time series modeling and fitting prediction on the series based on the monthly series data of Shanghai Securities Fund Index from January 2010 to December 2019. EGARCH (1,1) model has a good fitting effect on Shanghai Securities Fund Index series, all parameters are not 0, and the residual series of the model is tested to obey the standard normal distribution. Finally, the fitted model is used to predict the Shanghai Securities Fund Index from January to May 2020, and compare it with the real value to test the accuracy of the model. The results show that the actual values are within the prediction interval of 95% confidence coefficient, and the fitting effect of the model is superior.