Some say it’s difficult for equity traders to add value in today’s electronic marketplace of penny spreads. But Tereck Fares, CFA, director of equity trading at Chicago Equity Partners, isn’t one of them. “There’s a lot of money riding on trading,” Fares says. “There’s plenty of money to be made and plenty to be lost.”
The key to adding value, Fares says, is knowing when to be aggressive and when to be passive, while limiting one’s footprint in the marketplace. “You don’t want to give up information, because information is money,” he says.
About 60 percent of Chicago Equity Partners’ $11 billion in equity assets is in large-cap stocks, with the balance split between mid and small caps. The firm was an early adopter of electronic trading because, in its view, it lessened leakage into the marketplace. Today, Fares estimates that electronic trading represents more than two-thirds of its total volume.
The desk uses algorithms from about 10 suppliers. Fares declined to name his favorites, other than to say certain algos work best for specific strategies. The firm isn’t a big consumer of Wall Street research and rarely uses capital. “You’re offered capital when you least need it,” he says.
Fares has had success using algorithms to trade mid- and small-cap stocks. “They’re clearly more difficult to trade, because there is less liquidity,” he says. “Being anonymous takes on more importance, as does speed of execution. People can pick up your footprints more easily in small caps, so we try to avoid that as much as possible.”
That’s why it’s important to recognize that algorithms aren’t just black boxes, Fares says. An autopilot strategy without constant oversight could potentially create impact in the market. So, with adverse-momentum stocks, for example, the desk tries to act fast with the least possible impact, he says.
Another important aspect of algorithmic trading is to alter the pattern of any given algo strategy, he adds. Fares believes that computer programs exist that read the tape and attempt to get out ahead of institutional orders-commonly known as “reverse engineering.” That’s why it is important to introduce randomness into an execution strategy.
The crossing networks on the firm’s roster include Liquidnet, Pipeline and ITG’s systems. “Right now, we’re in the beginning stages of dark pools. Everybody’s starting one-it’s like a gold rush,” Fares says. “There is market share to be won.”
And also lost. Like many, Fares expects consolidation in the crossing network arena, and that the systems that survive will be those that can differentiate themselves and find a niche. Fares says he tries to avoid interacting with proprietary flow in networks. He adds that the most efficient algos “are dynamically linked to dark pools and also allow you to choose which ones you want to interact with and scrape.” Those algos can often grab liquidity quickly and silently, minimizing trading costs.
Chicago Equity Partners Equity AUM: $11 billion Desk: 3 traders Broker List: 20 firms Avg. Comm.: 2.5 cents OMS: Macgregor Trade-Cost Analysis: ITG’s TCA