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A further encouragement for the adoption of algorithmic trading in the financial markets came in 2001 when a team of IBM researchers published a paper[22] at the International Joint Conference on Artificial Intelligence where they showed that in experimental laboratory versions of the electronic auctions used in the financial markets, two algorithmic strategies (IBM's own MGD, and Hewlett-Packard's ZIP) could consistently out-perform human traders. MGD was a modified version of the "GD" algorithm invented by Steven Gjerstad & John Dickhaut in 1996/7;[23] the ZIP algorithm had been invented at HP by Dave Cliff (professor) in 1996.[24] In their paper, the IBM team wrote that the financial impact of their results showing MGD and ZIP outperforming human traders "...might be measured in billions of dollars annually"; the IBM paper generated international media coverage.
As more electronic markets opened, other algorithmic trading strategies were introduced. These strategies are more easily implemented by computers, because machines can react more rapidly to temporary mispricing and examine prices from several markets simultaneously. For example Stealth (developed by the Deutsche Bank), Sniper and Guerilla (developed by Credit Suisse[25]), arbitrage, statistical arbitrage, trend following, and mean reversion.
This type of trading is what is driving the new demand for Low Latency Proximity Hosting and Global Exchange Connectivity. It is imperative to understand what is latency when putting together a strategy for electronic trading. Latency refers to the delay between the transmission of information from a source and the reception of the information at a destination. Latency has as a lower bound the speed of light; this corresponds to about 3.3 milliseconds per 1,000 kilometers of optical fibre. Any signal regenerating or routing equipment introduces greater latency than this speed-of-light baseline.
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