Forecasting Chinese Foreign Exchange with Monetary Fundamentals using Artificial Neural Networks

We employ artificial neural networks (ANNs) and unconditional Vector Autoregressive model (VAR) to perform one-month-ahead out-of-sample predictions of both official and market Yuan/USD exchange rates using monetary fundamentals from 1992:M3 to 2010:M10. The optimal ANNs are attained systematically based on random validation sets. We empirically demonstrated that the generalized regression neural network is superior to the multilayer feedforward network in Chinese foreign exchange forecasting. ANNs generally outperformed in market rate forecasts in which suggest that market rates are supported by monetary fundamentals. On the contrary, official rates do not explained well by monetary fundamentals.