Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty

TL;DR

This paper investigates how transaction costs influence portfolio optimization, demonstrating that turnover penalization improves portfolio performance and links to covariance shrinkage, supported by theoretical insights and extensive empirical analysis.

Contribution

It introduces a novel connection between transaction costs and covariance shrinkage, and shows how turnover penalization enhances portfolio performance in practice.

Findings

Turnover penalization outperforms traditional shrinkage methods.

Transaction costs induce regularization in optimal portfolios.

Empirical results confirm the effectiveness of turnover penalization.

Abstract

We theoretically and empirically study portfolio optimization under transaction costs and establish a link between turnover penalization and covariance shrinkage with the penalization governed by transaction costs. We show how the ex ante incorporation of transaction costs shifts optimal portfolios towards regularized versions of efficient allocations. The regulatory effect of transaction costs is studied in an econometric setting incorporating parameter uncertainty and optimally combining predictive distributions resulting from high-frequency and low-frequency data. In an extensive empirical study, we illustrate that turnover penalization is more effective than commonly employed shrinkage methods and is crucial in order to construct empirically well-performing portfolios.