Measuring and Modeling Execution Cost and Risk

Abstract

Financial markets are considered to be liquid if a large quantity can be traded quickly and with minimal price impact. Although the idea of a liquid market involves both a cost as well as a time component, most measures of execution costs tend to focus on only a single number that reflects average costs and do not explicitly account for the temporal dimension of liquidity. In practice, trading takes time because larger orders are often broken up into smaller transactions or because of price limits. Recent work shows that the time taken to transact introduces a risk component in execution costs. In this setting, the decision can be viewed as a risk–reward trade-off faced by the investor who can solve for a mean-variance utility-maximizing trading strategy. Engle, Ferstenberg, and Russell introduce an econometric method to jointly model the expected cost and risk of the trade, thereby characterizing the mean-variance tradeoffs associated with different trading approaches, given market and order characteristics. They apply their methodology to a novel dataset and show that the risk component is a nontrivial part of the transaction decision.