Idiosyncratic Risk and Expected Returns in REITs

Ooi, Wang and Webb (2009) employ the Fama-French (1993) three-factor model to estimate the level of nonsystematic return volatility in REITs as a proxy for idiosyncratic risk. They report that idiosyncratic risk constitutes nearly 80% of the overall return volatility of REITs between 1990 and 2005. This result is consistent with the estimates in the finance literature that average common stock volatility is mostly driven by idiosyncratic risk (Goyal and Santa-Clara, 2003). Ooi et al. (2009) also analyze the relationship between expected returns and conditionally estimated idiosyncratic risk as well as market risk (beta). They employ the methodology of Fama and French (1992) to control for other systematic risks including size, value and momentum at the firm-level, and find a significant positive relationship between expected returns and conditionally estimated idiosyncratic risk contrary to Modern Portfolio Theory (MPT).;In this research, I examine other potential sources of systematic risk in REITs which may explain the seeming violation of the MPT found by Ooi et al. (2009). MPT argues that all unsystematic risk can be diversified away thus there should be no relationship between idiosyncratic risk and return. The fact that REITs tend to be a homogeneous asset class suggests that the level of systematic risk in REITs should be higher than that found in common stocks.;I re-examine the proportion of idiosyncratic risk in REITs following the methodology of Ooi et al. (2009). Historic idiosyncratic risk in REITs is calculated from 1996 to 2007 based on the Fama-French three-factor model (FF3). Monthly idiosyncratic risk is the regression residual and measured by daily excess returns over the past month for each REIT as a first-pass regression. Next, I add a potential systematic risk variable not included by Ooi et al. (2009), Carhart's (1997) momentum factor, which is largely applied on the FF3 to control for the persistency of stock returns as supplemental risk in the finance literature. Obtained factor loadings for each idiosyncratic risk and systematic risks are further applied into a second-pass regression model. I hypothesize that systematic risk will be increased significantly and idiosyncratic risk will be reduced accordingly.;Next, I conduct a second-pass regression. Due to the time varying property of idiosyncratic risk (Ooi et al., 2009; and Fu, 2009), I apply a conditional estimation GARCH model for expected idiosyncratic risk and market risk (beta). I also employ the methodology of Fama and French (1992) to control other systematic risks at the firm-level including size, value and momentum. Cross-sectional regression is conducted every month throughout the sample period and the significance of results is tested by t-statistics. I hypothesize that the expansion of applied asset pricing model from the FF3 to the FF4 including the momentum factor eliminates or at least significantly weakens the relationship.;I further test the role of property sector on idiosyncratic risk as well as on its relationship with expected returns. I hypothesize that market risk is systematically different by property sector and significant difference in the amount of idiosyncratic risk as well as in its relationship to returns are attributed to property sector. I employ both intercept and slope dummy variables and test if there is a significant proportion of systematic risk attributed to particular property sectors.;The addition of the momentum factor to the FF3 slightly reduces the proportion of idiosyncratic risk in REITs consistent with the findings in the finance literature though the level of reduction is not statistically significant. The second hypothesis is rejected. Although the positive relationship between idiosyncratic risk and return is weakened due to the addition of momentum to the Fama French three-factor model (FF3), the positive relationship does not totally disappear. The third hypothesis is also rejected. I find that the relationship between idiosyncratic risk and expected returns becomes insignificant when I control for property sector; however, none of dummy variables show any statistical significance.;These conclusions suggest three things. First, momentum has a relatively minor effect on the idiosyncratic risk consistent with the financial literature. Second, the effect of momentum is not strong enough to cause a significant change in the relationship between idiosyncratic risk and expected returns. Third, a REIT portfolio diversified across property sectors neutralizes the relationship between idiosyncratic risk and expected returns, though the contribution of each property sector is not statistically significant. These findings could shed light on the idiosyncratic risk in REITs as a contribution to the real estate literature.