Building robust portfolios with private assets: the importance of macro alpha and beta

Elevated geopolitical risks and heightened uncertainty have made it increasingly difficult to anticipate the future and invest accordingly. 

In our view, traditional portfolio construction approaches yield portfolios that are sub-optimally positioned to navigate this new investment paradigm. We apply advanced machine learning techniques to assess the relationship between key macro factors and asset performance to identify strategies to build more robust portfolios. 
Our approach significantly outperforms traditional factor estimation methods, includes both private and public markets, and takes into account the returns smoothing of private assets to improve comparability across private and public markets. 

We find clear evidence that higher private market exposures are desirable and result in increased portfolio resilience to broad macro volatility, better insulation against specific macro risks, improved overall portfolio robustness, and enhanced through-the-cycle risk-adjusted returns.