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Fast methods for large-scale non-elliptical portfolio optimization


Paolella, Marc (2014). Fast methods for large-scale non-elliptical portfolio optimization. Annals of Financial Economics, 9(2):1-32.

Abstract

Simple, fast methods for modeling the portfolio distribution corresponding to a non-elliptical, leptokurtic, asymmetric, and conditionally heteroskedastic set of asset returns are entertained. Portfolio optimization via simulation is demonstrated, and its benefits are discussed. An augmented mixture of normals model is shown to be superior to both standard (no short selling) Markowitz and the equally weighted portfolio in terms of out of sample returns and Sharpe ratio performance.

Simple, fast methods for modeling the portfolio distribution corresponding to a non-elliptical, leptokurtic, asymmetric, and conditionally heteroskedastic set of asset returns are entertained. Portfolio optimization via simulation is demonstrated, and its benefits are discussed. An augmented mixture of normals model is shown to be superior to both standard (no short selling) Markowitz and the equally weighted portfolio in terms of out of sample returns and Sharpe ratio performance.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Banking and Finance
Dewey Decimal Classification:330 Economics
Language:English
Date:September 2014
Deposited On:18 Jan 2016 14:12
Last Modified:05 Apr 2016 19:55
Publisher:World Scientific Publishing Co. Pte. Ltd.
ISSN:2010-4952
Publisher DOI:https://doi.org/10.1142/S2010495214400016
Related URLs:http://www.worldscientific.com/doi/abs/10.1142/S2010495214400016?journalCode=afe (Publisher)
Other Identification Number:merlin-id:12540
Permanent URL: https://doi.org/10.5167/uzh-119591

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