Asset allocation combining macro and micro information–Empirical test based on entropy pool model

Abstract

Macroeconomic environment is an essential factor affecting asset return, but it is difficult to construct portfolios using macro information quantitatively in traditional models. In this paper, we extend the Black-Litterman framework to build an efficient portfolio by using views containing macro information and prior market distribution reflecting micro information. In order to enhance the model's flexibility, entropy pool method is used. Empirical evidence shows that with reasonable allocation across economic stages, the newly constructed portfolio enjoys a higher level of Sharpe ratio compared to classic allocation models, and the result is robust under different circumstance.