  There is intense interest in understanding the stochastic and dynamical
properties of the global Foreign Exchange (FX) market, whose daily transactions
exceed one trillion US dollars. This is a formidable task since the FX market
is characterized by a web of fluctuating exchange rates, with subtle
inter-dependencies which may change in time. In practice, traders talk of
particular currencies being 'in play' during a particular period of time -- yet
there is no established machinery for detecting such important information.
Here we apply the construction of Minimum Spanning Trees (MSTs) to the FX
market, and show that the MST can capture important features of the global FX
dynamics. Moreover, we show that the MST can help identify momentarily dominant
and dependent currencies.
