Bank trade gune EA

[wira2597]

mesti bank pkai ea gempak gler...:-?

 

[robotfx2]

nak tanya ada sesapa yg join HGI main forex kat sila comment

 

[emag1881]

NEW YORK - Louis Morgan, managing director of hedge-fund firm HG Trading, has never talked to his best trader. That's because his best trader is a machine.

Morgan's top earner is a computer with software than can monitor thousands of stocks simultaneously and respond in less than a blink of an eye when opportunities arise.

"Doing what we do by hand would be impossible," said Morgan, who focuses on statistical arbitrage - taking advantage of sudden and potentially profitable price anomalies between securities that usually trade in correlation.

Morgan uses a computer trading system based on algorithms, complex mathematical formulas that quickly weigh a huge number of possible trades and execute orders in milliseconds (a millisecond is one thousandth of a second).

He is part of a rapid and relentless trading revolution that has transformed financial markets.

The increasing adoption of algorithmic trading - "black box trading systems" - is changing the way Wall St works and is creating new royalty with billion-dollar-plus incomes.

Former mathematics professor James Simons, who was one of the best paid hedge fund managers in the world last year, made US$1.7 billion ($2.3 billion), says Alpha magazine.

But there are predictions that the number of traders will sink by as much as 90 per cent by 2015 and that most of those left won't need traditional Wall St skills but will be whizzes in math, statistics, computer science, astrophysics and linguistics.

The presence of so much computer power has reduced short-term market volatility, but it also is giving regulators sleepless nights.

Many wonder what would happen if a rogue trader with rocket-scientist skills had control of a Wall St firm's black boxes, or if the machines turned a market slide into a meltdown before anyone could trigger a halt.

The change is even affecting where big banks and funds do business as they seek to get closer to exchanges and news services, so they don't lose precious seconds through delays in transmission of information.

And financial news organisations are increasingly focusing on machine-readable, as well as human-readable news.

About a third of US equities trading is being done using algorithmic trading, and Brad Bailey, a senior analyst at the Boston researcher Aite Group expects that figure to soar to more than 50 per cent by 2010.

"I'm even afraid I'm underestimating that number," Bailey said.

The London Stock Exchange says about 40 per cent of its trading is algorithmic.

"It's becoming much more mainstream," said Guy Cirillo, manager of global sales channels for Credit Suisse's Advanced Execution Services unit, an algorithmic trading platform that serves major hedge funds and other buy-side clients.

"The traditional firms that took longer to adopt have come in strong in the past year to two years," he said. "If you are not using this type of technology, you are at a serious disadvantage."

Algorithmics can be used to execute almost any strategy.

Some aim to capture fleeting price anomalies that generate thousands of buy and sell orders every second.

Others slice up a large trade into smaller trades to mask intentions and prevent rivals squeezing the trader on price.

That ability to trade quietly and anonymously solves one of a large firms' biggest headaches about using brokers - information leakage.

"You don't want anybody to know that you are trying to buy, say, 10 million shares of some small-cap stock," said Adam Sussman, senior analyst at hedge fund research firm the Tabb Group. "Otherwise, the price is going to shoot up."

Algorithmic trading has reduced volatility in equities and foreign exchange markets, as many of the programs are based on mean reversion, so that as things go astray, the programs pull the market back to the norm.

But algorithmic trading has had the opposite effect on financial and corporate news.

The appetite for information on everything and anything on Wall St has never been greater as data-hungry computer programs can absorb and respond to new and old input.

Software tools can analyse years worth of news stories to see how certain headlines affect certain stocks and asset classes and use those patterns to programme computers to trade on the latest news developments.

News and financial organisations such as Reuters, Dow Jones and Thomson Financial, which is acquiring Reuters, have jumped into the fray, making sure they present stories in ways computers can understand.

Louis Morgan said that five years ago, creating an algorithmic trading system was expensive as everything had to be done in-house. Today, he works with two people and a software program to build his algorithms.

The effort has paid off. "We are profitable on a little more than 60 per cent of our trades," he said.

While such a win rate may not look great on a traditional trading desk, it is very profitable when computers are trading much greater volumes.

Such success in what is being called "the algo wars" may mean that it is not only the exchange floor traders whose jobs are threatened but many of those sitting in front of screens, too.

Last year, an IBM Institute for Business Value study found that of every 40 traders active today, only four will be left by 2015 because of electronification of markets.

"The four traders will be the stars that assume risk, achieve true client insight and, of course, consistently beat the market," says the study.

And those survivors are set to do very well.

Simons, the 69-year-old founder of Renaissance Technologies in Long Island, New York, is not alone in the new billionaire class.

Ken Griffin, the 38-year-old founder of Citadel Investment Group in Chicago , took home US$1.4 billion last year, up from US$240 million in 2004, according to Alpha.

Both employ rapid-fire quantitative techniques designed to exploit minute price differences through algorithms.

wuihh bestnya ea dia tuh, profitable