Winter 2006

A Supplement to

Securities IndustrySecurities Industry

SELL-SIDEELECTRONICTRADING

Algorithms, multi-market access and the battle for

global superiority

Banc of America Securities’

Robert Almgren

SELL-SIDEELECTRONICTRADING

Algorithms, multi-market access and the battle for

global superiority

Banc of America Securities’

Robert Almgren

Algorithms Multiply to MatchTrading StrategiesSell-side firms have been unveiling new algorithms at an almost dizzying pace, making it clear

that electronic trading continues to grow in complexity as its usage increases. These strategies

include liquidity-seeking models that swiftly access the growing number of dark pools and

crossing networks, and algorithms for small-cap stocks, foreign exchange and large portfolios.

There are also adaptive algorithms, which are designed to respond to shifts in the market as a

live trader might.

By Katherine Heires

Abig reason for the increased number of products is that usage of, and demand for,algorithms on the buy side shows no sign ofletting up. According to Aite Group, aBoston-based research firm, 33 percent of

total equities trading volume flows through algorithms, upfrom 15 percent a year ago. Aite forecasts that the propor-tion will rise to 53 percent by the end of 2010. “Algorithmsare being used by an incredibly expanded base of clients,”noted Brad Bailey, a senior analyst at Aite. “It’s not justhedge funds anymore.”

Similarly, Westborough, Mass.-based research firm TabbGroup projects that the number of shares traded via algo-rithms could more than double after the Securities andExchange Commission’s Regulation National MarketSystem goes into effect in February. While many buy-sidetraders will still execute trades manually, when they do havean order that they want to execute with an algorithm, theywill only use something that they deem to be state of the art,wrote senior analyst and consultant Adam Sussman in aTabb Group report earlier this year. This puts pressure onbrokers to continue to innovate.

Sussman also noted that in the current electronic tradingenvironment, there is a lack of differentiation among offer-ings, and this could pose a threat to customer loyalty. As a

result, more sell-side firms are feeling pressure to set them-selves apart. “It’s extremely competitive,” said Tom Bok, SVPat Lehman Brothers Holdings in New York, which said it islaunching this month a liquidity-seeking algorithm over itsLehman Model Execution platform. The bank also offers anadvanced-strategy tool kit to make it easier for buy-sidetraders to customize Lehman’s algorithms, and it is toutingimproved integration of algorithms with analytics via a newdashboard feature.

Timothy Reilly, managing director of North Americanelectronic execution sales at Citigroup Global Markets,views liquidity-seeking algorithms as “the third generation ofalgorithmic offerings and the most challenging to producefrom a data management, infrastructure and financial engi-neering point of view.” The first generation of algorithms wasbased on common benchmarks such as volume-weightedaverage price. The second included strategies such as imple-mentation shortfall, which Reilly described as being morecomplex and largely focused on price goals.

Liquidity SeekersIn August, after a three-month development effort involving14 people, Citi released Dagger, which is designed to aggressively capture liquidity on electronic communicationsnetworks and exchanges without revealing signals to other

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market participants. Reilly said this algorithm competes withCredit Suisse’s Sniper and Guerrilla algorithms as well asAmbush from Banc of America Securities. At the same time,Citi also released Scouter, which searches for hidden liquid-ity across alternative trading systems and major exchanges.Scouter, like Guerilla, is engineered for traders seeking consolidated liquidity.

Other liquidity-seeking offerings include Goldman Sachs& Co.’s Sonar, which was released this past summer, and JPMorgan Chase & Co.’s Aqua and Arid, unveiled inSeptember. Aqua is designed to trade large orders in liquidmarkets, and Arid is intended to be used for illiquid securi-ties such as small-cap stocks. Both find liquidity by sweepinga total of eight dark books.

Perhaps the best-known liquidity-seeking algorithm,Credit Suisse’s Guerrilla was introduced in summer 2004and has been regularly updated and tweaked, according toDan Mathisson, managing director and global head ofCredit Suisse Advanced Execution Services in New York.Market participants often cite it for its stealth-like qualitiesand ability to reduce “signaling risk,” and it is one of theofferings that has helped Credit Suisse become the market-share leader among sell-side and independent agency firmsactive in algorithmic trading, according to Tabb Group.

Mathisson expects innovations in liquidity-seeking algo-rithms to continue through 2007. “Forward-looking firms areincreasingly opening up their private pools of liquidity inreciprocal arrangements, which will ultimately benefit thebuy-side clients and reduce fragmentation,” he said. CreditSuisse showed how that can work in October, announcingthat its CrossFinder internal crossing engine and Instinet’sContinuous Block Crossing network would open their liquidity pools to each other’s customers.

Trading PortfoliosPortfolio algorithms take on the challenge of managing atrade and have more goals and constraints than single-stockstrategies. A portfolio algorithm has to take into account themany correlations across various holdings so that it can minimize aggregate transaction costs.

“It takes a little leap of faith to trade an entire portfolio inthis manner,” acknowledged Jana Hale, managing directorand head of global algorithmic trading at Goldman Sachs.The average trader wants to have a complete understandingof the trading process before starting to push buttons andallow an entire portfolio of stocks to be traded by software.Nevertheless, Hale said the initial clients seem quite pleasedwith the results.

“We now have 20 regular users of this algorithm, andmore and more clients are now asking to use it,” she said.Goldman’s Portfolio X algorithm trades an entire list ofstocks rather than a single name, and it required a full yearof production, with two to four months for testing before itwas ready to go live.

Small caps comprise another active algo category.According to Robert Almgren, head of quantitative strategiesat Banc of America and a principal with the firm’s electron-ic trading services unit, small-cap algorithms are “the newfrontier in algo trading” and need to be upgraded to addressthe fact that small caps trade unpredictability, with liquidityoften appearing and disappearing in unexpected fashion.“When you are dealing with small caps, it’s insane to try toplan in advance how many shares of a stock might be traded,” Almgren said.

His solution was to build a so-called “adaptive” algo thatmimics human actions and responses. Such algorithms aresaid to be adaptive, Almgren said, because they do not usepre-computed trading lists. Instead, they are designed toadjust their execution moment by moment in response towhat they see happening in the market—as a human traderwould.

According to Almgren, the algorithm, which rolled out inOctober but has yet to be named, was inspired by JesseLivermore, a famous trader of the 1920s whose tradingexploits are recounted in “Reminiscences of a StockOperator,” a book by Edwin Lefevre. Livermore’s key adviceto traders was to “watch the tape” to gauge market trends.Adaptive algorithms, Almgren said, follow the same principle.

The new algo utilizes what Almgren calls a proprietary“liquidity estimator” based on the observed sequence oftrades and quotes, allowing it to adjust the rate of trading. Inaddition, it monitors its effect on the market, slowing downwhen it’s having cost impact and speeding up when the market easily takes the shares. “The most important featurehere is the algorithm’s sensitivity to its own impact and itsability to get out of the market before it leaves an impact,”Almgren said.

ForexAlgorithms in foreign exchange are at an earlier stage ofdevelopment, but rapid-fire releases in September byCitigroup’s Lava Trading subsidiary, Barclays Capital andBofA indicated that momentum is picking up.

Lava’s Timeslice allows traders to break their orders intosmall lots to minimize market impact. Barclays’ PowerFill,available on its Barclays Automated Real-Time Execution, orBarx, platform, provides transparency into the market. BofAlaunched a pilot of FX algorithmic trading along withenhancements to its Electronic Trading Services platform.

Analysts point out that many sell-side firms are currentlyworking closely with buy-side clients to make it easier forthem to create more tailored and customized algorithms.

“We have barely touched upon what automated tradingcan truly do,” said Tabb Group’s Sussman. “Get ready,because algorithms are going to get smarter and faster, andover the next two years they are going to quickly spill overinto options as well as the foreign exchange trading arena.” ■