Author(s)

Jieru Li

Corresponding Author

Jieru Li

ABSTRACT

According to the characteristics of the stock market's return rate sequence such as peaks and thick tails, skewness, volatility clustering, and leverage effect, this paper constructs two forecasting models, GARCH (1, 1) and EGRMA (1,1) to explore and analyze return rates The inherent laws of the sequence use R language to estimate and predict the parameters of the two models established. The results show that the unconditional standard deviation of the EGARCH(1,1) model is 0.03454091 closer to the sample standard deviation of 0.03470566; the AIC(-4.020409) of the EGARCH(1,1) model is compared to the AIC characteristics of the GARCH(1,1) model , Improve forecast accuracy. At the same time, based on the model results, it provides investors with suggestions and strategies for stock selection.

KEYWORDS

Topsis, inertia-reversal theory, EGRMA