Computational currency swapping

In the world's financial market today, there are many exchange rates. Banks have their own exchange rates posted and these rates are dynamic in nature. There are arbitrage opportunities when there exist price differences among different currencies in the international exchange market. The major process of the arbitrage strategy is to convert one currency to another, then convert it again to a third currency.etc., and then eventually convert it back to the original currency within a short time span. The simplest form of this process is the triangular arbitrage which involves only three currencies. It is possible to process more than three currencies in order to apply the arbitrage process. Although it may seem as if arbitrage is a risk-free process, in reality, there are risks involved. One of the risk factors is time; i.e., how fast one can process and how much capital one has in order to take advantage of these price discrepancies. It is worth noting that the arbitrage opportunities only exist when a bank's quoted exchange rate is not equal to the market's implicit cross exchange rate; these all happen in the range of seconds. The high frequency market fluctuation makes this process a challenge and calls for the utilization of high-performance computation. In this paper, we investigate the arbitrage problem by utilizing GPU to identify the opportunities and speed up the process.