  Mining companies to properly manage their operations and be ready to make
business decisions, are required to analyze potential scenarios for main market
risk factors. The most important risk factors for KGHM, one of the biggest
companies active in the metals and mining industry, are the price of copper
(Cu), traded in US dollars, and the Polish zloty (PLN) exchange rate (USDPLN).
The main scope of the paper is to understand the mid- and long-term dynamics of
these two risk factors. For a mining company it might help to properly evaluate
potential downside market risk and optimise hedging instruments. From the
market risk management perspective, it is also important to analyze the
dynamics of these two factors combined with the price of copper in Polish zloty
(Cu in PLN), which jointly drive the revenues, cash flows, and financial
results of the company. Based on the relation between analyzed risk factors and
distribution analysis, we propose to use two-dimensional vector autoregressive
(VAR) model with the $\alpha-$stable distribution. The non-homogeneity of the
data is reflected in two identified regimes: first - corresponding to the 2008
crisis and second - to the stable market situation. As a natural implication of
the model fitted to market assets, we derive the dynamics of the copper price
in PLN, which is not a traded asset but is crucial for the KGHM company risk
exposure. A comparative study is performed to demonstrate the effect of
including dependencies of the assets and the implications of the regime change.
Since for various international companies, risk factors are given rather in the
national than the market currency, the approach is universal and can be used in
different market contexts, like mining or oil companies, but also other
commodities involved in the global trading system.
