Efficient long range prediction of exchange rates using Radial Basis Function Neural Network models

In this paper a novel prediction scheme is proposed to efficiently predict the long range exchange rates using Radial Basis Function Neural Network(RBFNN). These models have been employed to predict currency exchange rate between 1 US$ to Indian Rupees and Japanese Yen. The performance of the RBF models is evaluated through simulation study and the results have been compared with Multilayer Layer Neural Network (MLANN) and Functional Link Artificial Neural Network (FLANN) based forecasting model. It is noticed that the RBFNN forecasting model outperforms than the FLANN and MLANN models.