This session is for those interested in the role of execution quality in portfolio performance attribution. Learn how conventional Transaction Cost Analysis (TCA) rewards behavioral trading practices in ways that may hurt rather than help portfolio performance. We’ll show you a new execution quality framework, as an extension of Brinson Fachler, that aligns the incentives of the trading desk with optimal portfolio performance. We’ll describe how to compute an unbiased baseline price by simulating the actions of a trading machine that considers the trading desk’s stream of instructions and its workflow requirements to merge orders into blocks and then allocate fills. Then we’ll demonstrate how replacing the execution results with our proposed baseline price in Brinson Fachler provides a measure of portfolio performance that is isolated from trader decisions. Learn about the application of this framework to AI-assisted trading and understand how execution optimization can significantly impact portfolio rankings.

Takeaways:

• Learn how conventional TCA may create biases and give incentive to behavioral trading that can hurt rather than help portfolio performance.
• See how our proposed benchmark can be tracked in real-time in an Execution Management System (EMS) to give traders the ability to track the progress of an algorithm.
• Understand why an accurate performance attribution methodology, that separates the impact of the trader’s decisions from portfolio management, enables successful implementation of predictive analytics to optimize trading schedules.
• Recognize that improving execution quality can have a significant positive impact on total performance when looked at over longer time periods.
• See how our approach can enable savings over historical performance metrics ranging from 0 to 20bps, depending on the specifics of each client implementation.