Wavelet Analysis of Commodity Price Behavior

We propose a form of semi-nonparametric regression based on wavelet analysis. Traditional time series methods usually involve either the time or the frequency domain, but wavelets can combine the information from both of these. While wavelet transforms are typically restricted to equally spaced observations an integer power of 2 in number, we show how to go beyond these constraints. We use our methods to construct ‘patios’ for 21 important international commodity price series. These graph the magnitude of the variations in the series at different time scales for various subperiods of the full sample