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Algorithmic trading

Trading that relies on a computerized trading system, which automatically issue buy/sell orders once market conditions fall in line with a certain set of parameters, or algorithms.

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Expanded Definition

How much do you usually invest in a stock? A few hundred dollars? A few thousand? A few hundred thousand?

All of these are mere drops in the bucket to large institutions, which regularly dump huge sums into their investments -- so much that they have the power to noticeably change a stock’s price. One of the ways they can minimize this impact is through algorithmic trading, whereby a computerized system executes trades based on a certain set of parameters, or algorithms.

The firms determine which parameters they want to set, and once market conditions fall in line with these criteria, the systems work fast -- they can make several trades in literally a fraction of a second -- and they can break up large orders into smaller blocks and execute each of these smaller orders separately. This lowers the impact that the whole order would have otherwise had on the stock’s price.

Although algorithmic trading has grown in popularity over the years (according to some studies, one-third of all U.S. stock trades were driven by automatic algorithms in 2005), it hasn’t been without a few setbacks. One of the most notable occurred on Feb. 27, 2007, when a computing error made it look like the Dow had dropped 240 points in three minutes. This huge change spurred a flurry of automatic orders from algorithmic trading systems, which created an order backlog and eventually led to the suspension of electronic trading by the New York Stock Exchange later that day.

But despite the occasional snag, these systems are still widely used as an efficient means for executing large trades. Algorithmic trading is also known as computerized trading, black-box trading, or model-driven trading.

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