Scientific Beta

Several articles in the May 2016 edition of the P&I EDHEC-Risk Institute Research for Institutional Money Management supplement are dedicated to the subject of smart beta, looking at the issue of combining different smart beta strategies and introducing the Scientific Beta six factor multi-smart factor indices, refuting simplistic explanations of smart beta performance, and examining conventional wisdom on the performance drivers of equity smart beta performance. 

Several articles in the May 2016 edition of the P&I EDHEC-Risk Institute Research for Institutional Money Management supplement are dedicated to the subject of smart beta. 

For asset owners pursuing a passive equity investment strategy, in addition to the question of selecting a suitable equity index as a stand-alone investment, the question of combining different smart beta strategies naturally arises in the context of an extensive range of smart beta offerings. A first article addresses the issue of combining several smart beta strategies, clarifies the conceptual underpinnings and relevant questions arising when considering smart beta index combinations and introduces the Scientific Beta six factor multi-smart factor indices. 

“Monkey portfolio” proponents argue that all equity smart beta strategies generate performance that is similar to results obtained by any random portfolio strategy. In a second article, we analyse these claims using test portfolios that follow commonly employed methodologies for explicit factor-tilted indices. Our results show that smart beta strategies display exposure to a variety of factors, and there are pronounced differences in factor exposures across different strategies. An important implication of our results is that a careful assessment of investment philosophy and index design is indeed relevant as such strategies do not behave like monkey portfolios.

In a third article, we examine conventional wisdom on the performance drivers of equity smart beta performance by drawing on conceptual considerations and empirical evidence. The analysis shows that, more often than not, superficially convincing claims about smart beta performance drivers stand on shaky foundations. Our analysis also shows that considering a breadth of evidence and conceptual considerations may perhaps lead to more balanced conclusions and a more nuanced understanding of smart beta performance.