Many investors think of real estate investment trusts (REITs) as a distinct asset class because, in aggregate, they historically have had relatively low correlation with both stocks and bonds, and their returns were not well explained by the single-factor CAPM model. For example, over the period from January 1978 through May 2017, the monthly correlation of the Dow Jones U.S. Select REIT Index with the S&P 500 was 0.58, and was just 0.08 with five-year Treasury bonds.


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The low correlation, along with the fact that the Dow Jones Select REIT Index produced a higher return (12.2%) than either the S&P 500 (11.7%) or five-year Treasury bonds (7.1%), led many investors to believe that adding REITs to a mixed-asset portfolio expanded the efficient frontier, providing superior risk-adjusted returns.

The evolution of modern financial theory and the development of more sophisticated multi-factor models provide us with tools to question the “traditional” view of REITs as both a separate asset class and one that expands the efficient frontier. With that in mind, I will review recent papers that specifically address these issues. The first is a May 2017 study by two of my colleagues, Jared Kizer and Sean Grover of the Buckingham Family of Financial Services.

Motivated by the observation that a lot of previous research treated REITs as a distinct asset class based on correlation alone, they decided to take another look at REITs in their own study, Are REITs a Distinct Asset Class? Their data sample covered the period from January 1978 through September 2016.

Kizer and Grover began by establishing criteria that an asset class must meet for it to be considered distinct. These criteria are:

  1. Low correlation with established asset classes, such as broad market equities and government bonds.
  2. Statistically signi?cant positive alpha with respect to generally accepted factor models.
  3. Inability to be replicated by a long-only portfolio holding established asset classes.
  4. Improved mean-variance frontier when added to a portfolio holding established asset classes.

Prior research had shown that, in terms of equity risk, REITs have significant exposure not only to market beta, but also to the size and value factors. In addition, they have been shown to have exposure to the term premium. In their analysis, Kizer and Grover employed a six-factor model comprising the market, size, value and momentum equity factors as well as the term and credit bond factors. The credit factor (referred to as IGDEF) subtracts the return of a duration-matched portfolio of Treasury bonds from the total return of the corporate bond index in order to isolate the return premium associated with the weaker credit of corporate bonds.

Their regression analysis included not only REITs, but also 12 other industries available on Ken French’s website. The following is a summary of their findings:

  • Demonstrating the explanatory power of the six-factor model, virtually all industries are well explained by four equity factors and two ?xed income factors. Only one industry category (a catch-all that included mining, construction, transportation, entertainment and hospitality, among other sectors) had statistically signi?cant annualized alpha, and the estimate was negative. It demonstrates that the factor model works well in explaining returns across industries, including REITs.
  • The annual alpha estimate for REITs was -0.89% with a t-stat near zero (-0.3).
  • REITs showed statistically significant exposures to market beta (0.61 with a t-stat of 10.2), size (0.44 with a t-stat of 6.1) and value (0.77 with a t-stat of 9.9), as well as a small negative (-0.08) and statistically insignificant (t-stat of -1.7) exposure to the momentum factor, a large (0.70) and statistically significant (t-stat of 3.8) exposure to the term premium, and a large (0.92) and statistically significant (t-stat of 3.9) exposure to the credit (default) premium.
  • While the R-squared ratio (which measures how well the factor model explains returns) was relatively low for REITs (0.51), this was also true for other industries, including energy, utilities and health care.


By Larry Swedroe, Read the full article here.