Algo Customization Addresses Complexity

Terry Flanagan

The need to navigate the maze of exchanges, dark pools, ATSs, and broker crossing networks that characterize the equities markets has given rise to the need to customize trading algorithms to achieve maximum execution performance.

Trading platform systems provided Portware has spent the past two years perfecting an intelligent algorithm system, AlphaVision, which uses predictive analytics to help traders ensure that they are in the right algorithm at the right time, regardless of market conditions. The software communicates directly with traders in real time, giving them unprecedented levels of control and information [color] on each order.

“Algo customization is being driven by the need for the trader to match the unique goal of his/her PMs with the right algorithm–all while navigating a complex market structure with endless order types and growing venue choices,” said Alfred Eskandar, CEO of Portware. “This is very much a real trend that we have witnessed; and, it’s driving demand for our portfolio manager profiling/algo management service, Alpha Vision.”

Portware has built on the momentum of its Alpha Vision product, which it had rolled out the year before, with the goal of putting the tools of machine-based intelligence to work for traders. The company added additional visualization tools to the product, which allow traders to ‘see’ the data rather than simply read the data.

Eskandar and Portware’s goal was to carve out a new category, namely, the thinking EMS powered by artificial intelligence. Portware has “democratized” the use of machine-based intelligence through AlphaVision, bringing machine-based intelligence to all traders, Eskandar said.

When customizing algorithms for their customers, broker-dealers need to focus on the objectives of the trader, and develop algorithms that meet those objectives. Customization for its own sake can lead to suboptimal results.

“Brokers that develop their own algorithmic suites have pushed the envelope to develop arrays of algorithms to handle special situations,” said Matt Samuelson, director of equities at Woodbine Associates, in a blog posting. “These algorithms, in theory, automate the process of hard-to-trade securities by becoming more or less aggressive, depending on market conditions.”

Buy-side traders need to be “mindful of a balance of human trading in conjunction with effective algorithm use,” he said. “To work complicated orders through specialty algorithms is often sub-optimal and can result in less-than-desired execution quality.”

Specialized algorithms designed to handle complex trading scenarios (e.g., automate less-liquid securities or perform more complex execution strategies) are of limited value, according to Samuelson.

“The discerning eye of an experienced trader can assess price action far better than an algorithm,” he said. “That assessment of price action need not be at the milli- or micro-second level but over a period of seconds or minutes. This is why most traders would never place an illiquid, hard-to-trade security in an algorithm.”

On the other hand, specialty algorithms that seek liquidity across the full spectrum of displayed and non-displayed venues do have value. “In such cases traders are principally concerned with capturing liquidity, potentially at the expense of obtaining truly optimal execution quality,” Samuelson said. “The tradeoff is reasonable given the difficulty of filling certain orders.”

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