News Column

Edge in a Niche

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Ramirez & Co., the nation's largest and oldest Hispanic-owned investment bank, has turned to algorithm trading technology via a joint venture with a young, Hispanic-owned proprietary algorithm trading services provider. Together, they aim to:

• Compete against larger brokerages,

• Maintain an edge over minority-owned competitors, and

• Increase the bank's more than $2 billion under management.

A Client Service Unit

New York-based Ramirez & Co. signed a joint venture with Algorithm Trading Solutions (ATS), a division and the primary business of Newark, New Jersey-based Tradetrek Sec-urities, a broker-dealer and algorithm developer/trading-services provider for institutional investors. The joint venture creates Ramirez Trading Solutions (RTS), offering the latest algorithm trading services to individual institutional investors, money managers, and pension funds.

Ramirez & Co. and ATS have a revenue sharing agreement in RTS. "We have certain clients we bring to the table, they have certain resources they bring to the table, and we look at an equitable split," says Sam Ramirez Jr., managing director of Ramirez & Co. The companies declined to discuss details.

Careful Match

Algorithms are software- and computer-driven mathematical models that run trading decisions and executions according to preset numerical strategies and goals. Use of algorithms helps Ramirez & Co. court clients that demand the most sophisticated trading technology, says Mr. Ramirez. "We compete with big brokerages as well as other minority-owned firms, and it comes down to showing the marketplace that we are unique," he says.

Under terms of the joint venture agreement, Ramirez & Co. is the only minority-owned brokerage that can use ATS algorithms. The deal gives the firm, which has about 90 employees and seven offices nationwide, an edge in the minority and small brokerage niches.

"Institutional investors are realizing that a good amount of their clients or constituents are Hispanic or other minorities, and they're trying to diversify the firms they do business with," says Mr. Ramirez. "We try to stay on the cutting edge of technology to put us ahead of our competition."

Sang Lee, managing partner at Aite Group, a Boston-based financial services research and consulting firm, agrees. "A lot of small brokers may not have a trading execution service, or have one that is heavily manual, which means it costs more to provide support services for clients," he explains. "One way around that is to introduce automated execution services."

ATS talked with other minority brokerages before signing the deal with Ramirez & Co. "We had been in contact with five or six other Hispanic brokers and another five or six minority brokers," recalls ATS managing partner George Rodriguez.

ATS struck the deal with Ramirez & Co. primarily because it is stable, with a strong capital base and a good reputa-tion. The firm's Hispanic-owned status was also a factor. "Both sides recognized there was a need to have small and mid-sized brokerage firms, that also happen to be Hispanic-owned, able to provide this type of sophisticated trading," says Mr. Rodriguez.

What Algorithms Do and Don't

Algorithms control the volume and timing of trade orders, and make it easier to buy and sell large quantities of equities by breaking them into smaller units to be sold electronically. Without algorithms, brokerages selling large blocks of stocks would have to seek the best prices on stock exchanges and through brokers.

Some algorithms are relatively simple, and target a stock's average daily price. Others are more complex, trading according to market volume and certain times of the day. "Most algorithms trade against a benchmark like market indices or certain rules created within the algorithm," Mr. Lee explains. "There are many benchmarks, and traders can theoretically accommodate any risk level."

Large Wall Street trading firms have used algorithms internally for years. But the concept has changed drastically over the past few years, for several reasons:

• In 2001, Wall Street changed from valuing stocks in sixteenths to pennies, increasing the number of price points for each dollar, reducing trading margins and profits for brokers.

• Growing government scrutiny of Wall Street and increasingly savvy individual investors made trading equities less profitable and more complicated than ever.

• Most importantly, electronic communications networks (ECNs) grew, allowing brokers to trade securities faster and more efficiently through exchanges worldwide. Large trading firms that had used algorithms internally began to use them for client trades.

Stocks with large capitalizations account for the bulk of algorithm-traded securities. But firms are starting to use algorithms for government securities, futures, and options. Mutual funds and pension fund managers are also beginning to make the move.

Algorithm-based trades will account for 40 percent of U.S. equities trading by 2008, compared with 25 percent currently, according to Aite Group.

Over the past few years, big financial institutions such as Credit Suisse First Boston, Goldman Sachs, Banc of America, and Lehman Brothers have built sizeable departments that develop algorithms and improve them. Meanwhile, smaller competitors also emerged. "We have seen a jump in the number of smaller firms that are pure algorithm providers run by people from large firms and hedge funds," says Mr. Lee.

Customized Vs. "White Label"

Most of the firms provide off-the-shelf "white label" algorithms that aren't tailored to individual institutional clients, says Mr. Lee. But ATS employs a team of engineers who create customized algorithms.

Customized algorithms are more expensive than the white label variety. "Large firms spend millions of dollars on customized algorithms. For a mid-sized firm like ours, the best choice was to outsource it and form the joint venture," says Mr. Ramirez. With the ATS-customized algorithms, Ramirez Trading Solutions can position itself to potential clients as a shop that offers its own unique services that can do the following:

• Assess the potential risks and costs of clients' trades and trading strategies,

• Analyze performance against specific preset benchmarks, and

• Keep trades and strategy confidential by trading in large blocks.

Still, algorithm-based trading poses some risks, Mr. Lee says. At many institutional brokers, he explains, client orders pass through the firm's proprietary trading desk before they are executed algorithmically. The process can raise trading costs, delay trades, and create a potential conflict of interest between a brokerage's prime trading desk and its algorithmic trading operations. For example, the prime desk could pass a huge sell order on to the algorithmic trading unit but use the information to benefit an order from a non-algorithm trading client ["trade against" the algorithmic order]. Also, firms that don't use algorithm trading expertly can unknowingly create patterns that other traders recognize.

None of that would happen with RTS, says Mr. Rodriguez. They deal in superior expertise, and "have structured it so that we will never trade against customer orders."

Service is Human

Algorithms can significantly reduce overhead costs for brokerages that use the technology expertly. "Algorithm trading requires sophistication that not all small and mid-sized firms possess, but Ramirez & Co. has that sophistication," says Mr. Rodriguez.

Algorithms can replace human traders, but Ramirez & Co. has no such plans, he adds. His reasoning? Algorithms are no better than the people who use and program them, and personal relationships with clients will always be important.

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