Non-Gaussian Regime-Switching Model in Application to the Commodity Price Description

Regime-switching models have been recently becoming increasingly important as they allow structural changes to be taken into account in modelling financial data. Application of such models to describe prices behaviour is especially valuable in commodities markets, where China’s industrialisation in the past three decades, created a huge demand for metals and energy, changing fundamentals of the market and affecting commodity prices. Moreover, in the financial time series very often we observe the non-Gaussian behaviour, which is manifested by large observations related to the market conditions. Considering the mentioned features of the financial data (especially commodity prices) in this paper we propose a stochastic model which takes under consideration the possible regime changes, the non-Gaussian character of the data and finally, the non-constant in time characteristics (like the mean function). We describe the main properties of the considered model and introduce a novel estimation procedure for the estimation of its parameters. Finally, we apply the proposed model to the real data describing the copper prices, one of the main risk factor for the KGHM mining company.