作者: Taha Abdelshafy , Abdelhakim Khalaf
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摘要: In this paper, we introduce a time series model that is capable of characterizing the exchange rate Euro to Egyptian Pound (EUR/EGP). Since considered as financial series, traditional autoregressive integrated moving average (ARIMA) would not be sufficient data series. Financial often exhibit volatility clustering or persistence. Therefore, which captures changes in variance required. adopt general conditional heteroskedastic (GARCH) fit data. The analysis show GARCH(1,2) heteroskedasticity I. INTRODUCTION