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A Bayesian Approach for Asset Allocation

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  • Mihnea S. Andrei
  • John S. J. Hsu

Abstract

The Black-Litterman model combines investors’ personal views with historical data and gives optimal portfolio weights. In this paper we will introduce the original Black-Litterman model (Section 1), we will modify the model such that it fits in a Bayesian framework by considering the investors’ personal views to be a direct prior on the means of the returns and by including a typical Inverse Wishart prior on the covariance matrix of the returns (Section 2). We will also consider an idea of Leonard & Hsu [1992] for a prior on the logarithm of the covariance matrix (Section 3). Sensitivity analysis for the level of confidence that investors have in their own personal views was performed and performance of the models was assessed on a test data set consisting of returns over the month of January 2018.

Suggested Citation

  • Mihnea S. Andrei & John S. J. Hsu, 2020. "A Bayesian Approach for Asset Allocation," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(4), pages 1-1, July.
    • Handle: RePEc:ibn:ijspjl:v:9:y:2020:i:4:p:1
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    Cited by:

    1. Mihnea S. Andrei & Sujit K. Ghosh & Jian Zou, 2021. "Dynamic Correlation Multivariate Stochastic Volatility Black-Litterman With Latent Factors," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(2), pages 1-1, March.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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