We postulate that utilizing return prediction models with fundamental, macroeconomic, and technical indicators instead of using historical averages should result in superior asset allocation decisions. We investigate the predictive power of individual variables for forecasting industry returns...

With greater economic and financial market integration, it is critical for asset managers to choose the investment universe that provides superior diversification and performance op-portunities. Therefore, it is important to investigate whether international diversification benefits arise from...

Given the tremendous growth of factor allocation strategies in active and passive fund management, we investigate whether either asset allocation strategies based on factors or sectors provide investors with a superior portfolio performance. Our focus is on comparing factor versus sector...

In this paper we analyze the contribution of hedge funds in optimal asset allocations for different investor clienteles. The preferences of specific institutional investors are captured by implementing a Bayesian asset allocation framework that incorporates heterogeneous expectations regarding...

The Black-Litterman (BL) model aims to enhance asset allocation decisions by overcoming the weaknesses of standard mean-variance (MV) portfolio optimization. In this study we implement the BL model in a multi-asset portfolio context. Using an investment universe of global stock indices, bonds,...