London software testing news UK


Traders test the limits of information technology

Posted in Acceptance testing by testing in London on September 22, 2007

From Financial News Online

Algorithmic trading, (aka program or black-box trading) is a well-established technique on the buy-side and accounts for about half of electronic trades in the mature stock markets.

It involves the routing of orders from fund managers’ trading blotter to specific computer-based algorithms that automatically manage the execution of these trades based on criteria such as timing, price or size of the order.

The first generation of trading algorithms, including volume-weighted average price and implementation shortfall algorithms, have been around for about three years but have come in for criticism this year for contributing to market volatility in periods of frenzied trading activity.

Algorithmic trading was blamed for escalating volatility spikes last month as the world’s leading equity markets reacted to sub-prime mortgage losses in the US.

Event-driven algorithms are marketed as the next generation of smart algorithms, differing from the established tools in that they adapt in real time to market changes. They emulate sellside traders by reacting immediately to the market and trading opportunistically to minimize execution costs and maximize returns, their vendors claim.

Customers can define the actions of the algorithms by setting parameters that optimize their performance while ensuring the underlying funds are not exposed to undue risk in times of extreme volatility.

Ary Khatchikian, chief technology officer of Portware, a supplier of automated portfolio trading software, said: “Some quants say they can handle it all electronically but you never know. That’s like saying there are no bugs in software.”One benefit of a sophisticated algorithmic trading platform is the ability to back-test market data to see what went wrong and try different strategies that might work better in similar conditions.

Martins said: “Back testing is key. Funds can capture the volatile market data of early August and back test it in new strategies to see how they would react.”

But Rosen said predicting the future based on the past is not reliable. He said: “Algorithms are not prophets. This is not a critique of algorithms, it is a critique of the naivete of the market. They are ascribing powers of prophecy to algorithms, giving them an aura of power they were not built to have.”

Algorithmic trading is here to stay, despite the recent scares. The ability of vendors to tweak and improve their products should make quant traders feel better about using them.

Testing financial services systems 

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