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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. 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.
    3. 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.
    4. 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.
    5. 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.

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