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Fast Methods For Large-Scale Non-Elliptical Portfolio Optimization

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  • MARC S. PAOLELLA

    () (Swiss Banking Institute, University of Zurich, Switzerland;
    Swiss Finance Institute, Switzerland)

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.

Suggested Citation

  • Marc S. Paolella, 2014. "Fast Methods For Large-Scale Non-Elliptical Portfolio Optimization," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-32.
  • Handle: RePEc:wsi:afexxx:v:09:y:2014:i:02:n:s2010495214400016
    DOI: 10.1142/S2010495214400016
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    References listed on IDEAS

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    1. repec:gam:jecnmx:v:5:y:2017:i:2:p:18-:d:97715 is not listed on IDEAS

    More about this item

    Keywords

    Expected shortfall; GARCH; mixture distributions; portfolio allocation; shrinkage estimation; simulation; weighted likelihood; C51; C53; G11; G17;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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