Exchange Rate Forecasting Based on the Combination of GARCH Models and ANN Technologies
Chi Xie · Science Technology and Engineering · 2006
It is an important task, as well as a hard one, to give an accurate exchange rate forecasting. By now, all kinds of methods and models have been created, but those forecasting performances disappoint us. At present, GARCH type models have been employed to model these high frequency financial time series due to their ability to capture the dynamic characteristics. In addition, the artificial neural network (ANN) method has emerged as an alternative approach to statistical methodologies because it can theoretically approximate any mapping relationship to any desired degree of accuracy. The two methods are combined to forecast seven foreign exchange rates, and expected to have better performance.