Abstract
This research aims to resolve the heteroscedasticity problem in time series data by modeling and analyzing volatility the gold return using GARCH models. Heteroscedasticity means not the constant variance of residuals. The sample data is a return data from January 1, 2014 to September 23, 2016. The data analysis technique used is a stationary test, model identification, model estimation, diagnostic check, heteroscedasticity test, GARCH model estimation, and evaluation. The results showed that ARIMA (3,0,3)-GARCH (1.1) is the best model.
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