High-frequency trading (HFT) is the use of sophisticated technological tools and computer algorithms to rapidly trade securities. HFT uses proprietary trading strategies carried out by computers to move in and out of positions in seconds or fractions of a second. Firms focused on HFT rely on advanced computer systems, the processing speed of their trades and 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. As of 2009, studies suggested HFT firms accounted for 60-73% of all US equity trading volume, with that number falling to approximately 50% in 2012. High-frequency traders move in and out of short-term positions aiming to capture sometimes just a fraction of a cent in profit on every trade. HFT firms do not employ significant leverage, accumulate positions or hold their portfolios overnight;[8] they typically compete against other HFTs, rather than long-term investors. As a result, HFT has a potential Sharpe ratio (a measure of risk and reward) thousands of times higher than traditional buy-and-hold strategies. HFT may cause new types of serious risks to the financial system. Algorithmic and HFT were both found to have contributed to volatility in the May 6, 2010 Flash Crash, when high-frequency liquidity providers rapidly withdrew from the market. Several European countries have proposed curtailing or banning HFT due to concerns about volatility. Other complaints against HFT include the argument that some HFT firms scrape profits from investors when index funds rebalance their portfolios. Most retirement savings, such as private pension funds or 401(k) and individual retirement accounts in the US, are invested in mutual funds, the most popular of which are index funds which must periodically "rebalance" or adjust their portfolio to match the new prices and market capitalization of the underlying securities in the stock or other index that they track.[26][27] This allows algorithmic traders (80% of the trades of whom involve the top 20% most popular securities[26]) to anticipate and trade ahead of stock price movements caused by mutual fund rebalancing, making a profit on advance knowledge of the large institutional block orders.[15][28] This results in profits transferred from investors to algorithmic traders, estimated to be at least 21 to 28 basis points annually for S&P; 500 index funds, and at least 38 to 77 basis points per year for Russell 2000 funds.[16] John Montgomery of Bridgeway Capital Management says that the resulting "poor investor returns" from trading ahead of mutual funds is "the elephant in the room" that "shockingly, people are not talking about." The largest high-frequency trading firms in the US include names like Getco LLC, Knight Capital Group, Jump Trading, and Citadel LLC. Advanced computerized trading platforms and market gateways are becoming standard tools of most types of traders, including high-frequency traders. Broker-dealers now compete on routing order flow directly, in the fastest and most efficient manner, to the line handler where it undergoes a strict set of Risk Filters before hitting the execution venue(s). Ultra Low Latency Direct Market Access (ULLDMA) is a hot topic amongst Brokers and Technology vendors such as Goldman Sachs, Credit Suisse, and UBS. Typically, ULLDMA systems can currently handle high amounts of volume and boast round-trip order execution speeds (from hitting "transmit order" to receiving an acknowledgement) of 10 milliseconds or less. Such performance is achieved with the use of hardware acceleration or even full-hardware processing of incoming market data, in association with high-speed communication protocols, such as 10 Gigabit Ethernet or PCI Express. More specifically, some companies provide full-hardware appliances based on FPGA technology to obtain sub-microsecond end-to-end market data processing. http://en.wikipedia.org/wiki/High-frequency_trading

• published: 21 Aug 2013
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