New Paper: “On the Bayesian interpretation of Black–Litterman” by Petter Kolm and Gordon Ritter

Petter Kolm and Gordon Ritter published a paper on a very general Black-Litterman model. They clarify the duality between Black-Litterman optimization and Bayesian regression. They show that this generalization is itself a special case of a Bayesian network or graphical model. As an example, they provide a full detailed treatment of views on factor risk premia in the context of APT. They also provide an example in which the portfolio manager specifies a view on realized volatility by trading a variance swap. You can read more here.