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Sparse Mean-Variance Portfolios: A Penalized Utility Approach (1512.02310v4)
Published 8 Dec 2015 in q-fin.ST
Abstract: This paper considers mean-variance optimization under uncertainty, specifically when one desires a sparsified set of optimal portfolio weights. From the standpoint of a Bayesian investor, our approach produces a small portfolio from many potential assets while acknowledging uncertainty in asset returns and parameter estimates. We demonstrate the procedure using static and dynamic models for asset returns.