Co-existence of stochastic and chaotic behaviour in the copper price time series

The possible scarcity of copper (and the likely resulting pressure on prices) is an issue of concern, especially in the light of its importance for the ever growing networking industry. Also for that reason, copper is the nonferrous metal most traded in the markets. Therefore, assessing the nature of its price fluctuations is an important task. Several papers have been devoted to analysing the characteristics of the time series of copper prices, especially for the purpose of predicting its future behaviour. The field of approaches can be divided roughly equally between those adopting a stochastic model and those opting for a deterministic nonlinear (chaotic) model. Nevertheless, while papers employing the stochastic paradigm have completely ignored the presence of chaotic features, at the same time papers recognizing the chaotic paradigm have neglected the presence of noise.The purpose of this paper is to investigate copper price behaviour in the CMX, considering a very long time series and adopting estimation methods that provide the coexistence of stochastic and chaotic features. We find that: a) the presence of noise is very significant (amounting to more than a quarter of the average signal value), as well as the presence of chaotic features; b) intermittency is present, which may be indicative of a bubble-related value that emerged without any fundamental cause.