Abel Noser and Liquidnet launch Portfolio Manager Profiling Pilot

Latest predictive analytic model available through LIQUIDNET LABS product innovation hub

Liquidnet and Abel Noser Solutions announced the pilot of Portfolio Manager Profiling. The model, when incorporated into Liquidnet’s Virtual High Touch™ Next Gen algo suite, links historical trade and TCA data with the portfolio manager’s decisions to create a distinct profile for each participating portfolio manager. These profiles are then factored into determining a suggested algo trading strategy via Liquidnet’s Algo Ranking Model (ARM).

“A portfolio manager’s tendencies have always influenced a trader’s execution strategy but being able to consistently replicate a profile pattern used to be a challenge,” said Peter Weiler, President of Abel Noser Solutions. “But by analyzing a client’s TCA data, we can now discover any persistent patterns that are statistically significant. With Portfolio Manager Profiling, Liquidnet pulls that analysis into its Algo Ranking Model to rank suggested execution strategies that are aligned to that PM’s preferences.”

“Buy-side traders are increasingly turning to smart execution tools like Liquidnet’s Algo Ranking Model to help support their trading decisions,” said Rob Laible, Liquidnet’s Global Head of Equity Strategy. “A PM’s tendencies are often nuanced, but could have a significant impact on the execution approach a trader takes. Being able to use technology to more accurately pinpoint those tendencies is a powerful addition to a trader’s toolkit.”

Portfolio Manager Profiling is currently being piloted via Liquidnet Labs, Liquidnet’s virtual innovation hub that showcases the company’s latest products and technology. Buy-side firms who are interested in being part of the pilot should contact their Abel Noser or Liquidnet representative directly.

Launched in 2016, Liquidnet’s Algo Ranking Model (ARM) generates an extensive profile of an order before ranking Liquidnet’s Next Gen Algos according to the trader’s execution objectives. Once the trader has made a selection, the model quantifies the factors that drive the ranking and adjusts its calculations in real time according to changing market and stock conditions. If the top-ranking algo changes, the trader is notified automatically. ARM is currently available in both the U.S. and European markets.