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Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty

CFS WP No. 582

62 Pages Posted: 28 Sep 2017  

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research; Center for Financial Studies (CFS)

Stefan Voigt

WU Wien

Date Written: September 26, 2017

Abstract

We theoretically and empirically study large-scale portfolio allocation problems when transaction costs are taken into account in the optimization problem. We show that transaction costs act on the one hand as a turnover penalization and on the other hand as a regularization, which shrinks the covariance matrix. As an empirical framework, we propose a flexible econometric setting for portfolio optimization under transaction costs, which incorporates parameter uncertainty and combines predictive distributions of individual models using optimal prediction pooling. We consider predictive distributions resulting from highfrequency based covariance matrix estimates, daily stochastic volatility factor models and regularized rolling window covariance estimates, among others. Using data capturing several hundred Nasdaq stocks over more than 10 years, we illustrate that transaction cost regularization (even to small extent) is crucial in order to produce allocations with positive Sharpe ratios. We moreover show that performance differences between individual models decline when transaction costs are considered. Nevertheless, it turns out that adaptive mixtures based on high-frequency and low-frequency information yield the highest performance. Portfolio bootstrap reveals that naive 1=N-allocations and global minimum variance allocations (with and without short sales constraints) are significantly outperformed in terms of Sharpe ratios and utility gains.

Keywords: portfolio choice, transaction costs, model uncertainty, regularization, high frequency data

JEL Classification: C58, C52, C11, G11

Suggested Citation

Hautsch, Nikolaus and Voigt, Stefan, Large-Scale Portfolio Allocation Under Transaction Costs and Model Uncertainty (September 26, 2017). CFS WP No. 582. Available at SSRN: https://ssrn.com/abstract=3043216

Nikolaus Hautsch (Contact Author)

University of Vienna - Department of Statistics and Operations Research ( email )

Oskar-Morgenstern-Platz 1
Vienna, A-1090
Austria

Center for Financial Studies (CFS) ( email )

Grüneburgplatz 1
Frankfurt am Main, 60323
Germany

Stefan Voigt

WU Wien ( email )

Welthandelsplatz 1
Building D4.4.171
Vienna, 1020
Austria

HOME PAGE: http://www.vgsf.ac.at/voigt

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