Liquidnet, the global institutional trading network, today announced the launch of its Algo Ranking Model technology, designed to enhance the way institutional traders make their execution decisions.
The Algo Ranking Model, built to complement Liquidnet’s recently launched suite of Next Gen Algos, uses innovative technology and a multi-factor model to holistically profile every order to rank execution strategies in real-time according to order characteristics, trading objectives, market conditions, and performance targets.
“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,” said Rob Laible, Global Head of Liquidnet’s Execution & Quantitative Services (EQS) Group.
Liquidnet’s Algo Ranking Model leverages Liquidnet’s institutional trading insight and quantitative expertise to translate complex market data into readily actionable information. The model ranks Liquidnet’s Next Gen Algos for three key execution objectives: performance, fill rate, and an optimal combination of the two. The trader is presented with a set of ranked algo strategies and then decides the course of action, gaining immediate insight into the market factors that influenced each strategy’s ranking and how we helped them achieve best execution on that trade.
“Technology is crucial to harnessing the ever-expanding volume of market information so that institutional traders can take their productivity, efficiency, and performance to new levels. In rapidly changing market conditions, traders often only have seconds to determine the right strategy to execute. Liquidnet’s Algo Ranking Model takes in relevant data before employing sophisticated logic and computing power to deliver meaningful and actionable conclusions to traders who are under pressure,” said Akis Georgiou, Liquidnet’s Head of Quant Analytics & Research.
Larry Tabb, CEO of the TABB Group further commented, “The next generation of trading tools will need to help them better navigate rapidly changing market conditions in real-time. As we’ve seen with the recent volatility, it is more important than ever for traders to not only have as much information as possible at their fingertips but the most meaningful conclusions about that information as well.”
Building the first “GPS for trading”
Seth Merrin, Liquidnet’s CEO and Founder, commented, “At Liquidnet, we use technology as an enabler for a more efficient financial market. 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. Liquidnet’s Algo Ranking Model plays the same role—analyzing your objectives before providing you with meaningful conclusions and insight so that you can make the best decision.”