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Forecasting Exchange Rate Between the Ghana Cedi and the US Dollar using Time Series Analysis

Keywords: ARIMA , autocorrelation , Bayesian Information Criterion (BIC) , box jenkins method , forecasting , Mean Absolute Percentage Error (MAPE) , time series analysis

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Abstract:

This study modeled the monthly exchange rate between the Ghana Cedi and the US Dollar and forecast future rates using time series analysis. ARIMA model was developed using Box and Jenkins method of Time Series Analysis on the monthly data collected from January, 1994 to December 2010 and validated. The result showed that the predicted rates were consistent with the depreciating trend of the observed series. ARIMA (1,1,1) model was found as the most suitable model with least Normalised Bayesian Information Criterion (BIC) of 9.111, Mean Absolute Percentage Error (MAPE) of 0.915, Root Mean Square Error of 93.873 and high value of R- Square of 1.000. Estimation was done by Ljung-Box test, with (Q 18) = 15.146, 16 DF and p-value of 0.514 with no autocorrelation between residuals at different lag times. Finally, a forecast for two-year period from January, 2011 to December, 2012 was calculated which showed a depreciating of the Ghana Cedi against the US Dollar.

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