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The Journal of Portfolio Management

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The Black–Litterman Approach and Views from Predictive Regressions: Theory and Implementation

Alois Geyer and Katarína Lucivjanská
The Journal of Portfolio Management Summer 2016, 42 (4) 38-48; DOI: https://doi.org/10.3905/jpm.2016.42.4.038
Alois Geyer
is a professor at WU (Vienna University of Economics and Business) and Vienna Graduate School of Finance in Vienna, Austria.
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  • For correspondence: alois.geyer@wu.ac.at
Katarína Lucivjanská
is an assistant professor at VU Amsterdam in Amsterdam, the Netherlands.
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  • For correspondence: k.lucivjanska@vu.nl
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Abstract

A major attraction of the Black–Litterman approach for portfolio optimization is the potential for integrating subjective views on expected returns. In this article, the authors provide a new approach for deriving the views and their uncertainty using predictive regressions estimated in a Bayesian framework. The authors show that the Bayesian estimation of predictive regressions fits perfectly with the idea of Black–Litterman. The subjective element is introduced in terms of the investors’ belief about the degree of predictability of the regression. In this setup, the uncertainty of views is derived naturally from the Bayesian regression, rather than by using the covariance of returns. Finally, the authors show that this approach of integrating uncertainty about views is the main reason this method outperforms other strategies.

TOPICS: Portfolio management/multi-asset allocation, derivatives, theory

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The Journal of Portfolio Management: 42 (4)
The Journal of Portfolio Management
Vol. 42, Issue 4
Summer 2016
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The Black–Litterman Approach and Views from Predictive Regressions: Theory and Implementation
Alois Geyer, Katarína Lucivjanská
The Journal of Portfolio Management May 2016, 42 (4) 38-48; DOI: 10.3905/jpm.2016.42.4.038

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The Black–Litterman Approach and Views from Predictive Regressions: Theory and Implementation
Alois Geyer, Katarína Lucivjanská
The Journal of Portfolio Management May 2016, 42 (4) 38-48; DOI: 10.3905/jpm.2016.42.4.038
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  • Article
    • Abstract
    • PORTFOLIO CHOICE WITH PREDICTIVE REGRESSION IN THE BLACK–LITTERMAN FRAMEWORK
    • PREDICTIVE REGRESSION
    • THE BLACK–LITTERMAN SETUP
    • OPTIMAL PORTFOLIO CHOICE
    • A SAMPLE APPLICATION
    • DATA
    • EMPIRICAL RESULTS
    • CONCLUSIONS
    • ENDNOTES
    • REFERENCES
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