Bayesian Regularized Neural Network for Forecasting Naira-USD Exchange Rate

Abstract

The Artificial Neural Network Autoregressive model (ANN-AR) is a recently adopted approach for forecasting Naira to the USD exchange rate. The Bayesian Regularized Neural Network (BRNN) is an alternative to ANN-AR based on the probabilistic interpretation of network weights. It is useful for solving overfitting problems inherent in ANN when large historical data are not available. In this paper, we developed a BRNN for modelling the monthly time series data of Naira to USD for four years. Performance analysis was observed using actual exchange rate values for the Year 2017 against the model predicted outcomes based on four evaluation metrics. Results from the analysis established the appropriateness of a BRNN for modelling short-term exchange rates in Nigeria.