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Predicting currency exchange rate and handling enormous data with traditional time series analysis has proven to be difficult. An artificial neural network may be more suitable for the task because no assumption about a suitable mathematical model has to be made prior to forecasting and being a stochastic method it can reach the near optimum solution in relatively lesser time. Furthermore, a neural network has the ability to extract useful information from large sets of data, which is required for a satisfying description of a financial time series. This paper discusses the various conventional analysis methods and neural network methodology to forecast the currency exchange rate. The paper also provides the effects of various topological parameters on the accuracy and training time of neural networks. A topology of neural network is proposed for the prediction of Indian currency exchange rate.