articles Corporate /en/research-insights/articles/blending-factors-in-your-smart-beta-portfolio content
BY CONTINUING TO USE THIS SITE, YOU ARE AGREEING TO OUR USE OF COOKIES. REVIEW OUR
PRIVACY & COOKIE NOTICE
Log in to other products

Login to Market Intelligence Platform

 /


Looking for more?

Request a Demo

You're one step closer to unlocking our suite of comprehensive and robust tools.

Fill out the form so we can connect you to the right person.

  • First Name*
  • Last Name*
  • Business Email *
  • Phone *
  • Company Name *
  • City *

* Required

In This List

Blending Factors in Your Smart Beta Portfolio

S&P Dow Jones Indices

How Smart Beta Strategies Work in the Chinese Market

S&P Dow Jones Indices

Considering the Risk from Future Carbon Prices

S&P Global Ratings

COP24 Special Edition Shining A Light On Climate Finance

S&P Global

Best Practices in Corporate Climate Disclosure


Blending Factors in Your Smart Beta Portfolio

In recent years, smart beta strategies have seen a significant increase in popularity. These strategies seek to measure systematic factors and aim to harvest the associated long-term risk premium. While many empirical studies show that smart beta strategies have historically outperformed their cap-weighted benchmarks, there is less evidence to suggest that any one factor will consistently outperform another. In fact, different factors tend to outperform in different market environments. Therefore, holding a combination of these strategies in a blended portfolio could potentially provide a powerful source of diversification and more stable excess return outcomes.

This paper briefly reviews the definition and performance characteristics of the S&P 500® Single-Factor Indices, demonstrates their historical cyclicality and correlation, and presents a few examples of how market participants could potentially use investment vehicles tracking these single-factor indices as part of their own factor allocation, either as strategic or tactical plays. These examples expand the traditional asset allocation frameworks to factors, including optimal allocation frameworks, heuristic allocation frameworks, and a trend-based timing framework.