The Role of Trading in Portfolio Performance Attribution

Abstract

We investigate the role of execution quality in portfolio performance attribution. We show how conventional Transaction Cost Analysis (TCA) rewards behavioral trading practices that in some cases hurt rather than help portfolio performance. To align the incentives of the trading desk with optimal portfolio performance, we propose a new execution quality framework as an extension of Brinson Fachler. We show how to compute a baseline price by simulating the actions of a trading machine that handles order size changes, limit price instructions and cancellations, merges overlapping orders into blocks and executes any open shares following strictly the benchmark plan. Replacing the execution results with the baseline price in Brinson Fachler provides a measure of portfolio performance that is isolated from trader decisions; the offsetting terms attribute the trading desk's role in portfolio performance and provide an unambiguous accounting of opportunity costs. We propose a quantitative framework to optimize trade execution. The proposed framework enables an AI-assisted workflow where the machine automatically attaches an optimal execution schedule to each order, then brings value-adding human intervention opportunities to the trader's attention. Over the long term, execution optimization can significantly improve portfolio rankings.