A model of generalized autoregressive conditional heteroscedastic was best to study the variance of inflation rates in Egypt from January 2006 to December 2017. This study aimed firstly to investigate suitability of the GARCH models to fit such data by examining the effect of heteroskedasticity. By using AIC, SIC, and BIC criteria of accuracy to check and choose the best model from selected models, GARCH (1,2) was the best model.
Aly, E. E. (2019). Measure the variation in inflation rates in Egypt using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models.. The Egyptian Statistical Journal, 63(2), 1-19. doi: 10.21608/esju.2019.188536
MLA
Emad Eldin I. Aly. "Measure the variation in inflation rates in Egypt using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models.", The Egyptian Statistical Journal, 63, 2, 2019, 1-19. doi: 10.21608/esju.2019.188536
HARVARD
Aly, E. E. (2019). 'Measure the variation in inflation rates in Egypt using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models.', The Egyptian Statistical Journal, 63(2), pp. 1-19. doi: 10.21608/esju.2019.188536
VANCOUVER
Aly, E. E. Measure the variation in inflation rates in Egypt using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models.. The Egyptian Statistical Journal, 2019; 63(2): 1-19. doi: 10.21608/esju.2019.188536
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