Friday, January 4, 2013

High Frequency Trading



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text courtesy of Wikipedia creative commons licence
High-frequency trading (HFT) is the use of sophisticated technological tools and computer algorithms to trade securities on a rapid basis.[1][2][3]

HFT usually uses proprietary trading strategies that are carried out by computers. Unlike regular investing, an investment position in HFT may be held for only seconds, or fractions of a second (though sometimes it may extend to longer), with the computer trading in and out of positions thousands or tens of thousands of times a day.[4] At the end of a day of HFT, there is no open position in the market. Firms engaged in HFT rely heavily on the processing speed of their trades, and on their access to the market. Many high-frequency traders provide liquidity and price discovery to the markets through market-making and arbitrage trading; and high-frequency traders also take liquidity to manage risk or lock in profits.[5]

High-frequency traders compete on a basis of speed with other high-frequency traders, not long-term investors (who typically look for opportunities over a period of weeks, months, or years), and compete for very small, consistent profits.[6][7] As a result, high-frequency trading has been shown to have a potential Sharpe ratio (measure of reward per unit of risk) thousands of times higher than the traditional buy-and-hold strategies.[8]

Aiming to capture just a fraction of a penny per share or currency unit on every trade, high-frequency traders move in and out of such short-term positions several times each day. Fractions of a penny accumulate fast to produce significantly positive results at the end of every day.[2] High-frequency trading firms do not employ significant leverage, do not accumulate positions, and typically liquidate their entire portfolios on a daily basis.[7]

By 2010 high-frequency trading accounted for over 70% of equity trades in the US and was rapidly growing in popularity in Europe and Asia.[citation needed]

High-frequency trading may cause new types of serious risks to the financial system.[1][9] Algorithmic and high-frequency trading were both found to have contributed to volatility in the May 6, 2010 Flash Crash, when high-frequency liquidity providers were in fact found to have withdrawn from the market.[10][11][12][13][14][15][16][17] A July, 2011 report by the International Organization of Securities Commissions (IOSCO), an international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, 2010."[1][18] An October 2012 study by the Chicago Federal Reserve found that "every exchange interviewed had experienced one or more errant algorithms" and recommended "limits on the number of orders that can be sent to an exchange within a specified period of time."