Recent research from Greenwich Associates has revealed shifts in financial markets as traders optimize execution strategies by more closely analyzing the performance of venues and brokers. Last week the research company hosted a webinar – Execution Quality: How the Buy Side Measures it; How the Sell Side Produces it – that explored the increasing sophistication of trading tools and execution analytics. Corvil CEO Donal Byrne was on the panel along with representation from the buy-side and sell-side.
Ken Monahan, Senior Analyst at Greenwich, opened the discussion by summarizing the results of his recent research and how brokers found themselves in a more intense horse race as they compete for buy-side order flow.
“As the tools of buy side users to analyze the quality of execution have increased in sophistication, it’s also driving an increase in the speed with which they reallocate flow,” Monahan said. “The capacity for the buy side to measure the performance of the sell side is making the competition among the sell side firms more intense.”
He framed the rest of the discussion, by exploring how buy-side firms were creating broker routing scorecards with precise metrics aligned to specific portfolio manager (PM) strategies. He then asked what brokers were doing to provide these requested metrics and optimize their execution plants to deliver against these heightened client expectations.
Providing the buy-side/trading desk perspective was Craig Hurl, Director at Ontario Teachers’ Pension Plan, one of the world’s largest institutional investors. He offered up some useful examples of the information being collected from and about their brokers and described how the company is using a mix of internal and third-party tools to analyze these against portfolio managers’ intentions, which informs how aggressive or passive its trading should be. For him the key value of having that data in using it to start changing behavior of either the trading desk or the broker to obtain a better outcome for a particular strategy.
Vlad Khandros, Global Head of Market Structure & Liquidity Strategy at UBS, explained how clients have become more data driven and systematic in their approach. He spoke of how investment in infrastructure, data sets and algo customization continues to increase, and how a basis point can translate to hundreds of million dollars for clients in their annual turnover.
“When you think about those kinds of metrics, the difference of being ranked as the number one broker for some clients or being cut off entirely can be literally the fraction of a basis point,” he said. Vlad warned of the risk of not having the resources to fully process all the data that is available, and talked about working with third-party analytics vendors to improve execution quality and validate data sources.
Donal Byrne said that in the last 12 months Corvil has seen a significant demand for more sophisticated analytics in organizations responsible for electronic trading execution, including brokers, exchanges and non-bank liquidity providers. In addition to seeking more high quality execution metrics, they also want more context into exactly why specific outcomes occurred.
People are trying to gain an understanding of the relationship between execution plant performance and execution outcomes for specific trading strategies. This understanding enables firms to make better use of the types of metrics that Ken Monahan described as the “canary in the coalmine” for fill rates -- e.g., reject rates, cancel rates, algo response times, or venue response times. Insights born from that understanding can drive changes needed to deliver against clients expectations more efficiently.
“This is evolving into another arms race around ‘execution alpha’,” he said. “It is the idea that with superior execution analytics, intelligence and superior technology, firms can achieve superior execution and attain alpha.”
Donal also opined that an abundance of high-quality metrics and real-time execution data will drive an increasing use of machine learning and AI, describing them as a “good fit” for analyzing causal effects and what specifically needs changing. “For example, is the algo responding correctly or appropriately to give me the desired fill rates? People are trying to crack that code using these types of technologies,” he said.
Watch the On-Demand Webinar
Download the Greenwich Associates Report: Customer Retention in the Age of Electronic Trading