Abstract
We present a robust Black–Litterman (BL) model that takes into account the possibility of model misspecification. In place of a single prior distribution, we utilize multiple priors around the estimated expected excess returns and covariance matrix. The model has two primary advantages over the original BL model: (1) it systematically incorporates model misspecification in the form of Kullback–Leibler (KL) divergence and (2) by explicitly targeting robust allocations, it improves upon traditional bootstrap approaches.
Notes
This article contains the current opinions of the authors and not necessarily those of PIMCO (Pacific Investment Management Company LLC). These opinions are subject to change without notice.