Recently many researchers have studied complex networks that express nodes as individuals or groups and links as connections among them. Most complex networks serve as a function to transfer constituents between nodes through various dynamical processes. Menezes et al and Eisler et al investigated the scaling law between the time averages of the constituents’ flow and their standard deviations measured at different nodes for various real systems. We regard the foreign exchange market as a network and measure them of quotation frequencies which represent the macroscopic dynamics of the foreign exchange market. We found that the power-law relation between a mean of quotation frequencies and their standard deviation for each currency pair. It is confirmed that the power law exponents take values from 0.8 to 1.0 depending on observation periods. Therefore it can be concluded that the arrivals of the quotations on the brokerage systems are not independently Poissonian since synchronous and desynchronous states of quotation arrival rates are related to the value of a scaling exponent.

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