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,...

The Black-Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample based version of the Black-Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity...

Striving for maximum diversification we follow Meucci (2009) in measuring and managing a multi-asset class portfolio. Under this paradigm the maximum diversification portfolio is equivalent to a risk parity strategy with respect to the uncorrelated risk sources embedded in the underlying...

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...