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27.07.2014 admin
In their obsessive pursuit of high-value market advantage, stock traders are pushing IT to its limits - and the lawmakers don't like it.
In August 2012, the company's computers started making bizarre trading decisions, quadrupling the price of one company - Wizzard Software - as well as bidding-up the price of much larger entities, such as General Electric. Languages such as OpenCL that provide a way to write highly parallel code that can be mapped onto graphics processors or field-programmable gate arrays (FPGAs), which have the ability to change logic circuits on the fly, are providing a way to move away from conventional compute servers. In the autumn, the US Securities and Exchange Commission (SEC) launched an investigation to decide whether Knight tested its computer systems properly before loading code designed to talk to a new trading platform used by the New York Stock Exchange (NYSE). A couple of years earlier, algorithmic trading came under the spotlight when US stock prices suddenly plunged for no apparent reason. The quantitative-analysis people are being educated by the Intel people to be hardware aware. The quicker trading algorithms see the trades, the faster they can react to them.The result has been something akin to an arms race built on computer and network hardware.

From the morning until just after lunch, while quotations hovered around 1,000 to 2,000 per second, trading continued more or less normally.
Across the Atlantic, MEPs in the European Parliament voted for a bill that could curb the more abusive activities of algorithmic trading. The measure restricts the speed with which orders can be withdrawn from the market - they would have to remain on the system for more than 100ms. Mao Ye, Chen Yao, and Jiading Gai, researchers from the University of Illinois at Urbana Champaign, published a paper last August in which they claimed even orders with a life of just 50ms would be a reasonable limit without affecting the cost of trading.
To try to extend the reach of HFT, computers increasingly use trading signals from exchanges thousands of miles apart and with an increasingly diverse range of data to eke out a trading advantage using statistical arbitrage.
The 825-mile trench contains fibre-optic cable that lets trading houses, unsatisfied with the latency that the existing telecom infrastructure could give them, link their computers together. Researchers at the Massachusetts Institute of Technology (MIT) came up with a number of ideal computing locations around the world based on their relative proximity to trading venues, some lay in the North Atlantic and Indian Ocean.

Oil rigs that have emptied their wells could find new uses as homes for trading supercomputers.Even then, at some point, the latency advantage runs out. There will be differentiation [between trading strategies], but speed is becoming less of a differentiator. High-frequency trading strategies have to examine massive amounts of data to generate predictive signals". As financial trading systems incorporate more data from the web, they become more vulnerable to the attacks that plague the Internet.

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