The Intrinsic Logic of the Augmented Black-Litterman Model
affiliation not provided to SSRN
December 18, 2010
Portfolio management is an art as well as science. We argue that portfolio managers eventually face two fundamental scientific challenges: (a) how to allocate; and (b) how to mimic. These require scientific answers. Other challenges in portfolio management are arts where different tastes, preferences, judgments and beliefs should be allowed. A general portfolio management framework should provide principles for solving the scientific problems, but remain neutral and facilitate interactions with the art part. The Augmented Black-Litterman (ABL) model rightly meets these requirements. This article reveals its intrinsic logic. It features:
- An exploration of the motivation and general requirements of portfolio construction;
- A dissection of the ABL allocation model;
- Three ABL endogenous techniques and their efficiency evidences;
- The intrinsic logic of the ABL model; and
- Justifications of the model as a unified Bayesian allocation framework.
Practitioners can consider this framework a unified allocation theory, which can be used to understand, evaluate and improve existing portfolio construction practices.
Number of Pages in PDF File: 28
Keywords: allocation, factor mimicking, hedging, Augmented Black-Litterman (ABL), Fama-French, factor risk model
JEL Classification: C10, C11, C61, G11working papers series
Date posted: December 26, 2010 ; Last revised: April 25, 2012
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