Volatility Forecast Of Shanghai Stock Index Based On NPCARR Model

In recent years,China’s securities market is in an era of coexistence of opportunities and risks.The securities market has been characterized by price fluctuations since its emergence.How to express the price of the securities market accurately and confirm the parameters of the subsequent rate of return are the key factors considered by the industry.Therefore,the analysis around volatility has great theoretical and practical value.As a fixed feature of the financial system,volatility is generally manifested as the fluctuation of corresponding asset prices.This volatility represents uncertainty and risk in the market system.Relevant documents at home and abroad point out that range is better than volatility to describe the volatility of financial markets.Therefore,in the analysis of this paper,the thoughts and research methods of the two models will be integrated,and the calculation methods such as model and convergence under relatively weak conditions will be discussed through the connection between interval and volatility.Then,because the Shanghai Stock Index Extreme Range series has better statistical characteristics than pure price series,it is more conducive to financial risk measurement and modeling.Moreover,the Shanghai Stock Index is highly liquid,highly correlated with the existing market index,and the sample stocks are concentrated in a large number of high-quality stocks in the market,which has a strong market representativeness.Therefore,the Shanghai Stock Index Extreme Range is selected as the research sample.From the simulation and empirical perspectives,the two models are simulated and empirically analyzed to study which model can be more A good description of the volatility of financial markets.In the end,it is concluded that the Shanghai Stock Index Extreme Range has obvious fluctuation aggregation and high-order ARCH effects,and there are phenomena of forward bias,distribution diffusion and tailing.There are some autocorrelation,short and long memory and sustainability.Characteristics of attenuation.Compared with the predictive accuracy of the parametric CARR(1,1)model for the volatility of the Shanghai Stock Index,the non-parametric CARR(1,1)model has a higher prediction accuracy.