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The dynamic Black–Litterman approach to asset allocation

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  • Harris, Richard D.F.
  • Stoja, Evarist
  • Tan, Linzhi

Abstract

We generalize the Black–Litterman (BL) portfolio management framework to incorporate time-variation in the conditional distribution of returns in the asset allocation process. We evaluate the performance of the dynamic BL model using both standard performance ratios as well as other measures that are designed to capture tail risk in the presence of non-normally distributed asset returns. We find that the dynamic BL model outperforms a range of different benchmarks. Moreover, we show that the choice of volatility model has a considerable impact on the performance of the dynamic BL model.

Suggested Citation

  • Harris, Richard D.F. & Stoja, Evarist & Tan, Linzhi, 2017. "The dynamic Black–Litterman approach to asset allocation," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1085-1096.
    • Handle: RePEc:eee:ejores:v:259:y:2017:i:3:p:1085-1096
    DOI: 10.1016/j.ejor.2016.11.045
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    2. Palczewski, Andrzej & Palczewski, Jan, 2019. "Black–Litterman model for continuous distributions," European Journal of Operational Research, Elsevier, vol. 273(2), pages 708-720.
    3. Fernandes, Betina & Street, Alexandre & Fernandes, Cristiano & Valladão, Davi, 2018. "On an adaptive Black–Litterman investment strategy using conditional fundamentalist information: A Brazilian case study," Finance Research Letters, Elsevier, vol. 27(C), pages 201-207.
    4. Frieder Meyer-Bullerdiek, 2021. "Out-of-sample performance of the Black-Litterman model," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 10(2), pages 1-2.
    5. Zhu, Bo & Zhang, Tianlun, 2021. "Long-term wealth growth portfolio allocation under parameter uncertainty: A non-conservative robust approach," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

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    More about this item

    Keywords

    Finance; Black–Litterman model; Multivariate conditional volatility; Portfolio optimization; Tail risk;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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