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On an adaptive Black–Litterman investment strategy using conditional fundamentalist information: A Brazilian case study

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  • Fernandes, Betina
  • Street, Alexandre
  • Fernandes, Cristiano
  • Valladão, Davi

Abstract

We propose an investment strategy based on the Black–Litterman model with conditional information. We present how observed price-earnings ratio and past returns can be used to determine 1-step ahead returns, considering investors with different risk profiles. The provided approach updates the conditional probability distribution of asset returns and mitigates asset allocation instability due to estimation errors. Our case study using Brazilian data shows the resulting optimal portfolios outperform traditional mean-variance portfolios even in an emerging market with one of the highest nominal interest rates.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:finlet:v:27:y:2018:i:c:p:201-207
    DOI: 10.1016/j.frl.2018.03.006
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    References listed on IDEAS

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    4. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    5. 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.
    6. Wolfgang Bessler & Heiko Opfer & Dominik Wolff, 2017. "Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black–Litterman, mean-variance, and naïve diversification approaches," The European Journal of Finance, Taylor & Francis Journals, vol. 23(1), pages 1-30, January.
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    Cited by:

    1. Barua, Ronil & Sharma, Anil K., 2022. "Dynamic Black Litterman portfolios with views derived via CNN-BiLSTM predictions," Finance Research Letters, Elsevier, vol. 49(C).

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