high-frequency trading

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high-frequency trading

Buying and selling large quantities of stocks in split seconds, and making pennies or fractions of a penny per share. High-frequency trading (HFT) is performed entirely by computer algorithms that look for and take advantage of small price discrepancies of the same stock on different exchanges. HFT computers are constantly bidding and offering 100-share lots of thousands of different stocks to determine moment-to-moment prices. In addition, traders can spoof the market by placing large sell orders, cancel them milliseconds later and immediately buy the stocks at a lower price, which they caused by injecting negativity into the market.

High-frequency traders are competing with other high-frequency traders all day long. In order to profit, the buys and sells must be executed immediately, and the shorter transmission pathways between orders and executions make the difference. To speed up the process, high-speed traders locate their computers within the same datacenter as the stock exchange computers or as close by as possible. In the most extreme example, a fiber optic line was laid from New Jersey to Chicago in the straightest line possible in order to shave nanoseconds from the travel time. The futures exchange is in Chicago, and New York-based stock exchanges have their datacenters in New Jersey.

Extremely Controversial
Proponents claim high-frequency trading is simply an advanced form of algorithmic trading like all the other widely used financial formulas. High-frequency traders also claim their systems make a more uniform market and have a stabilizing effect.

Opponents claim HFT is downright deceitful, turning money making into software that executes 99% of its trades with a profit. They claim high-frequency traders make billions per year without contributing any value to anyone but themselves. In the Flash Crash of May 6, 2010, when the Dow swung 1,000 points within minutes, regulators reported that high-frequency trading exacerbated market volatility after the sale of unusually large futures contracts. Had the event occurred at a different time of the day, the effects might have reached around the world. As a result, opponents assert that high-frequency trading could turn the market into greater bouts of chaos in the future.
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A US watchdog is now investigating if HFT had any role to play in the price decline of cattle futures last year.
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23) The crash of 1987 serves as more than a turning point in this analytical timeline: it reveals the interconnectedness of the events in Wall Street's insidious history that have contributed--and are strikingly analogous--to the current situation involving HFT and dark pools.
More specifically, on the one hand, HFT algorithms are designed to detect and respond to market rhythms, as per Lefebvre's definition (for a discussion of the rhythmic character of algorithms, see also Miyazaki, 2013):
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