How exactly are buy side traders using algorithms? That was the question posed to a panel at the TradeTech West conference taking place in San Francisco this week.

The panel, moderated by Adam Honore, senior analyst at Aite Group, explored how algorithms fit into the buy side trading process, how traders evaluate offerings and what the trends are on the horizon.

David Margulies, head of algorithmic sales at Pragma@Weeden, an algorithmic trading platform from Pragma Financial Systems and Weeden & Co.,said that over the past couple of years the buy side skill set around algorithms has seen “an upside down shift.” With the proliferation of dark aggregation and the new benchmarks available, he sees the buy side actively changing and adapting their trading to leverage the latest and greatest algorithmic offerings.

Robert Maher, director, Advanced Execution Services at Credit Suisse, added that the buy side level of expertise in the area of custom algorithms and strategies has also seen a marked uptake. In fact, Maher said that Credit Suisse has built out its infrastructure and operations in order to fully support its customized offerings for buy side customers.

On the EMS/OMS front the panel seemed to agree that an OMS is still the center of a buy side trader’s universe and as such the algorithms they use must be delivered to the platforms efficiently.

Alan Marshall, head of equity trading at Luther King Capital Management explained that for his shop and his needs he is still trying to find a better application or integration that makes it easier to move toward an EMS for trading.

When evaluating trading partners, Marshall said he looks for robustness of platforms, why certain orders are routed where and how the systems perform. Although technically comparing algorithms trade for trade is virtually impossible as each trade is so different and market conditions vary as well.

Margulies said that traders have to try out various algorithms to determine what works best for them. In addition he said that more quantitative focused firms are likely to seek more information such as underlying risk models, covariance structures, etc when evaluating algorithmic offerings.

Next up for algos? The panel pointed to the usual hot areas—better dark liquidity seeking strategies and international algorithms. On the international front, Maher said that region to region, “benchmarks might be the same or similar but the different market microstructures mean algorithms have very different strategies.”

He added that liquidity can also be a challenge internationally as there are “less electronic trading pipes” for orders to flow through, as well as required spread sizes overseas.

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