The Intrinsic Logic of Bayesian Allocation Framework

Authors: Cheung, W.

Publisher: SSRN


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. Practitioners can consider this framework a unified allocation theory, which can be used to understand, evaluate and improve existing portfolio construction practices as well.

Source: Manual