  We analyze structure of the world foreign currency exchange (FX) market
viewed as a network of interacting currencies. We analyze daily time series of
FX data for a set of 63 currencies, including gold, silver and platinum. We
group together all the exchange rates with a common base currency and study
each group separately. By applying the methods of filtered correlation matrix
we identify clusters of closely related currencies. The clusters are formed
typically according to the economical and geographical factors. We also study
topology of weighted minimal spanning trees for different network
representations (i.e., for different base currencies) and find that in a
majority of representations the network has a hierarchical scale-free
structure. In addition, we analyze the temporal evolution of the network and
detect that its structure is not stable over time. A medium-term trend can be
identified which affects the USD node by decreasing its centrality. Our
analysis shows also an increasing role of euro in the world's currency market.
