Commentary

Robert Schuessler
Traders Magazine Online News

A Smarter Monkey

In this contributed piece, TIM noted that some traders do better than others when using data that has been run through certain analysis - that is, have used some form of machine learning to assist them.

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June 4, 2007

Algos Get Serious

Increased Sophistication and Greater Customization for Traders

By Nina Mehta

Trading in New York Stock Exchange-listed securities is going electronic. Liquidity in Nasdaq and Big Board names is splintering. Message rates for market data are accelerating. All this has created fertile ground for developers and promoters of algorithms. Now, as these products become smarter and better at grabbing liquidity, traders are customizing and adapting algos to trade more like themselves.

"Customers are using new algorithms and custom algorithms more readily than they used to, and they're changing algos and suggesting new features more quickly now," says Mike Stewart, head of global cash equity trading at Merrill Lynch. "They're also using algorithms over much shorter time periods to aggregate liquidity."

The Securities and Exchange Commission's Regulation NMS fueled electronic trading and ratcheted up the speed of trading. By protecting the top-of-book quotes at exchanges, Reg NMS also encourages brokers to manage the way they route to various markets and access liquidity.

This has fragmented liquidity. The NYSE and Nasdaq now compete with the reinvigorated regionals and aggressive ECNs like BATS and Direct Edge ECN. And in the run-up to Reg NMS's implementation, a new electronic world of non-displayed, or dark, liquidity was unleashed, claiming a growing share of equities volume.

16 Tentacles

Traders are turning to algos to pull together liquidity in a market where orders shift around between venues. "Accessing liquidity manually through direct market access will be a difficult task at best," says Michael Rosen, product manager at agency broker UNX Inc. "People will want to keep manual control on tough trades, but they can't do that for all trades. If they're in the wrong marketplace, they could miss liquidity."

Smart order routing, which analyzes the distribution of liquidity and dictates how algorithms place and take orders from the markets at every moment, has become increasingly critical.

Dan Mathisson, head of Credit Suisse's advanced execution services group, the firm's suite of algorithmic products, notes that smart routing enables algos to do more than mimic traders. "Algos trade in a way people can't," he says. "They have 16 tentacles out in the market as feelers. They keep track of where executions are occurring, the [execution] quality of venues, and what the supply and demand curves look like for individual stocks."

Jim Leman, a managing director at Westwater Corp., a management and technology consulting firm focusing on financial services, points out that algos can absorb and adeptly deal with the waves of market data coming at them faster-and better-than people can. Algos can also "send out requests for indications [of interest] or consume message data emanating from dark pools," he says. "That's like a vacancy sign going on and off that only algos can read. Otherwise, someone must go to those pools individually."

More Optimization

Unlike their predecessors, the current spate of sophisticated algorithms are not predetermined recipes for breaking block orders into pieces and executing those pieces, or "child orders," over the course of a few hours or a day based on historical trading patterns. In algo-speak, they are increasingly dynamic and "optimize" their trading strategies in real-time.