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Core-satellite investing with commodity futures momentum

Author

Listed:
  • Immo Stadtmüller

    (University of Leipzig)

  • Benjamin R. Auer

    (Friedrich Schiller University Jena, Chair of Finance
    University of Leipzig
    CESifo Munich, Research Network Area Macro, Money and International Finance)

  • Frank Schuhmacher

    (University of Leipzig)

Abstract

Core-satellite strategies are often implemented to combine the benefits of passive and active investing. Our study analyzes a particularly attractive and quasi-frictionless core-satellite approach: Adding active commodity futures momentum satellites to passive cores diversified across traditional asset classes. We show that momentum portfolios, enhanced by long-term reversal and skewness information, are highly valuable satellites. Considering them with low fixed weights, as suggested by popular strategic allocations, leads to significant improvements in investment performance and reduces portfolio sensitivities to shocks in investor fear. In contrast, using time-varying optimized weights based on satellite alphas or tail risk minimization turns out to be less advantageous. Interestingly and regardless of the considered weighting scheme, momentum satellites shine primarily by lowering portfolio risk (instead of increasing portfolio return) which supports modern interpretations of the role of active management.

Suggested Citation

  • Immo Stadtmüller & Benjamin R. Auer & Frank Schuhmacher, 2024. "Core-satellite investing with commodity futures momentum," Journal of Asset Management, Palgrave Macmillan, vol. 25(3), pages 261-287, May.
  • Handle: RePEc:pal:assmgt:v:25:y:2024:i:3:d:10.1057_s41260-024-00352-5
    DOI: 10.1057/s41260-024-00352-5
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    More about this item

    Keywords

    Core-satellite investing; Commodity momentum; Portfolio optimization; Strategic portfolio weighting;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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