Black–Litterman Optimization Results

W. Brent Lindquist, Svetlozar T. Rachev, Yuan Hu and Abootaleb Shirvani
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W. Brent Lindquist: Texas Tech University
Svetlozar T. Rachev: Texas Tech University
Yuan Hu: University of California San Diego
Abootaleb Shirvani: Kean University

Chapter Chapter 6 in Advanced REIT Portfolio Optimization, 2022, pp 87-92 from Springer

Abstract: Abstract The Black–Litterman model was designed to mitigate issues of input sensitivity and estimation error maximization by using a Bayesian approach to incorporate the returns of a market index. It also incorporates the ability to include subjective views based on investment analyst estimates. As subjective views are specific to the market day and the analyst, the exploration of this model in this chapter is restricted to incorporating market equilibrium returns. The performance of Black–Litterman optimized domestic and global REIT portfolios, under long-only investment strategies is compared to the corresponding mean variance optimized counterparts of Chaps. 4 and 5 . Reflecting its design, the performance of the Black–Litterman portfolios more closely tracks that of the selected market index than do optimizations that concentrate solely on maximizing the Sharpe ratio.

Date: 2022
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DOI: 10.1007/978-3-031-15286-3_6

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