Optimizing Broker Performance Evaluation through Intraday Modeling of Execution Cost

TL;DR

This paper introduces a new intraday modeling approach to evaluate and improve broker execution performance by accurately estimating execution costs, including linear and impact costs, using trading data.

Contribution

The paper develops a novel methodology with analytical formulas and weighting techniques for more precise broker performance evaluation based on transient price impact models.

Findings

Enhanced accuracy in estimating execution costs

Robust framework for broker selection

Significant improvement over previous estimation methods

Abstract

Minimizing execution costs for large orders is a fundamental challenge in finance. Firms often depend on brokers to manage their trades due to limited internal resources for optimizing trading strategies. This paper presents a methodology for evaluating the effectiveness of broker execution algorithms using trading data. We focus on two primary cost components: a linear cost that quantifies short-term execution quality and a quadratic cost associated with the price impact of trades. Using a model with transient price impact, we derive analytical formulas for estimating these costs. Furthermore, we enhance estimation accuracy by introducing novel methods such as weighting price changes based on their expected impact content. Our results demonstrate substantial improvements in estimating both linear and impact costs, providing a robust and efficient framework for selecting the most cost-effective brokers.