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September 30, 2004

The Revenge of the Geeks

By Randy Abernethy

Automated market making, black box proprietary trading and algorithms are rapidly growing segments of the trading industry. The implied migration from people to machines will have a profound and long-term effect on our capital markets.

A few years ago, market making was a task doled out to tens, sometimes hundreds of people on boisterous trading desks. Today, the most profitable market makers are silicon, rather than carbon based. Technology has revolutionized the way the bulge-bracket firms trade their own money. Quantitative strategies operated by hedge funds and the proprietary arms of broker dealers have grown tremendously in sophistication.

Today's committed buyside trader is pitted against these systems. Sometimes it seems like a mismatch. The trader is often under-armed. In many cases, his own information is used against him. However, market forces are driving both the development and the adoption rate of complex agency-based trading servers in the buyside community. That gives traders the ability to fight fire with fire. Many trading technology developers and agency brokerages are offering algorithmic trading strategies that can rapidly analyze market conditions and make intelligent decisions. These decisions include when, where and how to execute trades. Today's algorithmic trading servers are reaching mature levels. Here are some of the common strategies available:

*Slicers - Slicers are the most basic, and easy to use, order handling engines. Slicers take large orders and break them into pieces, which are delivered to the market over time, concealing the total size of the master order. Some of the more advanced slicers allow traders to specify rules and constraints around the method of slicification.'

*VWAP - VWAP (Volume Weighted Average Price) servers are a mainstay in this evolving space but vary in sophistication. However, because many servers stick out like a sore thumb, some highly advanced VWAP servers use camouflage tactics and exceptionally rich real-time market information. That makes their trading patterns hardly recognizable as VWAP in the open market.

*Shortfall - Introduced by Jack Treynor and Andre Perold in the late 1980s, implementation shortfall has enjoyed an increase in popularity on the buyside. This approach measures risk over specified time intervals, as well as the opportunity cost of not executing the order. Automated trading servers, built upon this methodology, attempt to determine optimal execution opportunities to lower total transaction costs based on a set of factors.

*Participation - Strategy servers of this kind target a volume ratio for execution using historical and real-time volume data. Historical average daily volume statistics and the current day's market conditions provide a base for these algorithms. They project the total share volume in the selected stock necessary to achieve the targeted participation ratio. To be successful, this strategy requires both accurate volume projections, as well as the ability to maintain a passive limit order presence in various venues of a fragmented market.

*Pairs - Pairs trading servers allow market neutral trades, such as merger arbitrage and other types of statistical multi-instrument trades, to be managed electronically with risk controls. That ensures trading does not become excessively unbalanced. This type of server, in its more sophisticated implementations, can manage complex arbitrage operations involving program trades and instruments in various asset classes.

Leading edge firms have been using proprietary versions of many popular algorithms for several years. Controversies persist over whether they are superior to human trading. That said, the era of widely available technology-based trading servers has just begun. Banc of America, CSFB and many others offer compelling buyside solutions in the algorithmic trading space, helping traders minimize market impact, opportunity cost and execution timing costs. All report rapid growth. For now, there appears to be no limit to the level of sophistication that algorithmic trading systems can achieve.

Randy Abernethy is the CEO of UNX, Inc.