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Algo Trading Lures the Buy Side in a Fragmented Market

Buy-side traders find algorithmic trading helps them conceal their trades, boost productivity and measure their performance against benchmarks.

Another reason that algorithmic trading is handling more and more order flow is that it helps buy-side traders to be more productive. "It's made our trading desk much more efficient - traders can handle far more orders with these tools at their disposal than they ever could trading singly or on the electronic system or even juggling a lot of broker tickets," Wheeler asserts.

The strategies "can also be capacity-enhancing for the buy-side trading desk," says Brian Fagen, managing director, institutional equity division, at Morgan Stanley. "They can act almost like trading assistants - a trader can give instructions with limits that control the order and control the execution, so that the buy-side trader doesn't have to focus all their attention on that order," Fagen continues. "The trader knows the order is being handled in the manner they would expect, and the trader can move on and focus on the more difficult situations."

In order to allow the buy side to take more control over its executions, and to encourage buy-side traders to use the algorithims, brokers are beginning to offer direct access to their algorithmic strategies through their existing buy-side order-management systems, or directly through the Financial Information Exchange (FIX) protocol.

Brokers have been extremely prolific in forging interfaces to buy-side order-management systems and other types of front-office trading systems already on the desktop. For example, Credit Suisse First Boston offers access to CSFB Advanced Execution Services through 14 or 15 third-party vendors, including Charles River, Macgregor and Longview Trading, as well as Bloomberg, Reuters, FlexTrade and Portware.

In addition to masking order flow and allowing institutions to trade anonymously, algorithmic trading is a way to lower trading costs. "For the buy side," algorithmic trading is in demand because "it's reducing market impact and reducing trading cost," says Josh Galper, a senior consultant with The Tabb Group in New York City.

Firms can pay 1/2 a cent or a penny a share for a low-touch (algorithmic) trade, which goes straight to a direct-access liquidity point, whereas they could pay three, five or six cents a share for touch-assisted trading - which includes some research, Galper says. "If you strip out research and you're just talking about straight execution for an algorithmic trade, you're well under a penny," he adds.

Brokerage commissions alone, however, are not the only variable in the cost equation. There are two types of transaction costs that the buy-side trader is looking to reduce with algorithmic trading: explicit costs, which are the tangible brokerage commissions, and implicit costs, which are the intangible costs of market impact - when the price slips away from the trader while he or she is in the process of buying or selling a large block of stock. Goldman Sachs' Hale says traders will be judged on their ability to minimize these implicit costs.

To avoid market impact, buy-side firms are measuring their performance against benchmark trading strategies, a trend that is supported by algorithmic trading. Similar to the way that portfolio management is measured against a benchmark return, such as the S&P 500 or the Dow Jones Industrial Average or the Russell 2000, traders are being compared to benchmarks.

In fact, Morgan Stanley named its offering Benchmark Execution Strategies "because, at the end of the day, we think that's what everyone is trying to do," the firm's Fagen says. "They're trying to minimize their execution shortfall to a particular benchmark."

There's a whole slew of benchmarks for traders to measure themselves against, Fagen adds. For example, he cites the previous night's close; the start of the order, or the arrival price; the volume weighted average price of the day; and that day's closing price.

According to Robert Hegarty, vice president of TowerGroup's securities and investment practice, "Many firms are becoming much more reliant on picking a benchmark, whether it's the S&P 500 or the Russell 2000. One of the better ways to perform against that is to employ algorithmic trading." Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio

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