Liquidnet has developed a new way to support execution decisions with its Algo Ranking Model.
The model is intended to enable buy-side traders to rank their execution strategies in real-time based on various criteria, including order characteristics, trading objectives, market conditions and performance targets.
Liquidnet said the Algo Ranking Model will utilise its institutional trading insights and quantitative expertise to turn complex data into information that an be actioned by traders.
It ranks algorithms from Liquidnet’s new suite based on three execution objectives; fill rate, performance and how the two are combined. Traders will receive a set of ranked algo strategies and can then pick the most appropriate for their trading strategy.
Rob Laible, global head of Liquidnet’s Execution & Quantitative Services Group, said: Today’s markets have become increasingly complex and our Members have said that many of the basic algo offerings have become commoditized. The only way to truly capture a performance advantage is by choosing the right strategy based on the conditions of the stock and market at the time of execution.”
Liquidnet said that the model will help traders who are under pressure to make decisions in seconds to choose the algorithm that is best for their order.
Seth Merrin, CEO and founder of Liquidnet, added: “With markets evolving quickly and the volume of data increasing even more rapidly, technology is key to enhancing decision making and productivity.
“We like to think of our Algo Ranking Model as the equivalent of a GPS for trading. When traveling from point A to B, you always have the option of simply jumping in a car and driving the route you assume would be best. But by using a GPS system, you can make a more informed decision based on speed, convenience, cost, or even a combination of all three.”