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Dynamic portfolio management with views at multiple horizons

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  • Meucci, A.
  • Nicolosi, M.

Abstract

We introduce Dynamic Entropy Pooling, a quantitative technique to perform dynamic portfolio construction with discretionary, non-synchronous views. With Dynamic Entropy Pooling, the portfolio manager can embed in the allocation process subjective views with life spans ranging from minutes to years, calendar views, autocorrelation stress-testing, and the traditional views on expectations, correlations and volatilities.

Suggested Citation

  • Meucci, A. & Nicolosi, M., 2016. "Dynamic portfolio management with views at multiple horizons," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 495-518.
    • Handle: RePEc:eee:apmaco:v:274:y:2016:i:c:p:495-518
    DOI: 10.1016/j.amc.2015.11.009
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    References listed on IDEAS

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    Cited by:

    1. Muhinyuza, Stanislas & Bodnar, Taras & Lindholm, Mathias, 2020. "A test on the location of the tangency portfolio on the set of feasible portfolios," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    2. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    3. Martin Schans, 2019. "Entropy Pooling with Discrete Weights in a Time-Dependent Setting," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1633-1647, April.
    4. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    5. Xiangyu Cui & Jianjun Gao & Yun Shi, 2021. "Multi-period mean–variance portfolio optimization with management fees," Operational Research, Springer, vol. 21(2), pages 1333-1354, June.

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