A Wavelet Neural Network Model for Forecasting Exchange Rate Integrated with Genetic Algorithm

Floating rate system has come into force in china, which will make exchange rate more fluctuant. As a result, participants within the insurance industry have frequently found themselves facing increased variable exchange rate negatively and dangerously affected the insurance industry and need to be pro-active instead of reactive to exchange risk. In this paper, a hybrid model is described, which integrates the Wavelet Neural Network with Genetic Algorithm and can predict Exchange Rate. Then the theory framework and algorithms are discussed. An empirical example is described. It shows that the proposed model can predict Exchange Rate with the scale of one day, one week and other intervals and the precision of prediction is not the decline trend when the forecasting scale is extended.