id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fbem-634	Wang, Jie	Research on the Volatility Characteristics of Shanghai Stock Market Based on ARCH Model Family	2022	5	.pdf	application/pdf	3862	173	55	GARCH models reduce the requirements for parameters. But traditional ARCH or GARCH models cannot capture the nonlinear characteristics of stock returns.[8] Danielson (1994) used the maximum likelihood method to study the daily data of the S&P500 index and concluded that the EGARCH(2,1) model was better than the ARCH(5) and GARCH(1,2) models in fitting the data.[9]	cache/fbem-634.pdf	txt/fbem-634.txt