Abstract
A system containing known values and uncertain unknown values is called a Grey system. Grey system requires only a limited amount of data to estimate the behaviour of unknown systems with poor, incomplete or uncertain information. In this paper, the accuracies of different Grey system models such as GM(1,1), FRMGM(1,1), VGM and FRMVGM are investigated. In addition to this, Linear Regression model is also used for comparison. These Grey models solve complex and sophisticated problems like foreign currency exchange. Foreign currency exchange rates are affected by many highly correlated factors. These factors could be economic, political and even psychological factors, and each of them affect the rate of currency exchange in difference level from time to time. Foreign currency exchange rate from Commercial Bank of Ethiopia between November 2014 and October 2015 are used to compare the performance of different models. The simulation result shows that FRMGM(1,1) is the best in model fitting and forecasting foreign currency exchange.
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