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Investors’ Limited Attention: Evidence from REITs

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Abstract

This paper examines the degree to which the market prices of publicly traded firms reflect and respond to new information regarding the economic viability and vitality of organizations to which they are strategically linked. More specifically, we exploit the uniquely transparent nature of the lessor-lessee relationship across commercial real estate markets to evaluate whether future returns to real estate investment trusts (REITs) are systematically affected by the financial return performance and/or operational opacity of the tenants who lease their investment properties. Using a hand collected data set identifying the principal tenants of 96 publicly traded REITs, we find those firms with the best performing tenants generate annualized abnormal returns which are approximately six percentage points higher than those realized by REITs with the worst performing tenants. These results are robust to a variety of model specifications, and a closer inspection of the results reveals these performance differentials are consistent with emerging evidence across the literature suggesting investors’ limited attention materially influences the return predictability of assets. We thus conclude investors’ limited attention leads to the failure of REIT prices to fully reflect the valuation implications of their tenants’ return performance.

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Notes

  1. An emerging literature finds evidence of such investor under reaction to firm specific information, including information regarding related firms. Of note, Ramnath (2002) is among the first to empirically examine such issues, and finds evidence consistent with investor under reaction to the performance of peer firms within the same industry.

  2. Retail tenants frequently pay a base rent that does not depend upon their level of sales, plus an overage rent which is charged as a percentage of gross sales above some threshold level.

  3. In related work, a large literature explores whether REITs truly reflect the underlying fundamentals of real property markets. Among these studies, Giliberto (1990), Gyourko and Keim (1992), and Myer and Webb (1993) all find evidence that REIT returns are indeed a function of lagged (Russell-NCREIF) index values of the underlying real estate markets and property types in which they invest. While these studies do not map REITs to their individual tenants, they do support the notion that REIT valuation is directly contingent upon the economic vitality of the assets underlying their investment portfolios.

  4. For example, the moniker J.C. Penney’s and JCP are both used to identify the same retail tenant by alternative sample landlords/REITs.

  5. We acknowledge that within REIT markets, (adjusted) funds from operations (FFO) typically serves as the primary profitability metric employed by analysts. As REIT tenants are drawn from a much broader cross section of industries, many of which do not focus on FFO measures, to facilitate comparisons across tenants and landlords our reported results employ the more traditional return on assets (ROA = Net Income divided by Total Assets) metric to assess profitability. Not surprisingly, given the relatively high degree of correlation across these metrics for sample firms, our results are robust to the use of either metric.

  6. Institutional ownership levels for REITs at the beginning of our sample interval in 2000 average only 41.62%, but grew to 70.92% by 2013. Similarly, institutional ownership levels for sample tenants grew from 40.10% in 2000 to 68.45% by the end of our sample observation window in 2013.

  7. As the vast majority of REITs within our sample have more than one tenant, to measure the recent performance of their collective tenants we construct an equally (value) weighted portfolio of their corresponding tenants and measure the performance of this aggregated tenant portfolio. Thus, within the context of the empirical results, unless otherwise noted, tenant performance refers to the aggregate performance of these conservatively defined tenant portfolios.

  8. Relaxation of this constraint to include firms with at least either one or two, publicly traded tenants leads to qualitatively similar empirical conclusions. Similarly, consistent with the notion that REITs with larger numbers of publicly available tenants outstanding reduce the noise of the future profitability and cash flow signals we wish to examine, we find evidence that return predictable is more pronounced within those firms leasing properties to relatively large numbers of publicly traded tenants. See the Appendix (Tables 10 and 11, respectively) for these comparative results.

  9. S&P does not report the exact lease date between a REIT and each tenant. For both simplicity and tractability, we assume the link begins at the end of the year in which it is first reported. This overly conservative identification scheme reduces the power of our tests, but should enhance the validity of any relations we document.

  10. In operationalizing these metrics, we calculate abnormal returns using a time-series regression of the portfolio excess returns on traded factors in calendar time.

  11. Consistent with the previous literature, to minimize the influence of short-term return reversals our 1-year momentum factor is measured using months t-12 through t-2.

  12. Interestingly, and in direct contrast to Cohen and Frazzini's (2008) results, premiums accruing to our tenant momentum strategy appear to be driven largely by the relatively slow diffusion of positive news rather than short side returns. While a complete analysis of this phenomenon is beyond the scope of the current investigation, one potential explanation for this differential finding flows directly from the relative transparency of REIT assets. More explicitly, Blau et al. (2011) suggest the increased transparency of REIT assets, and by extension REIT markets, reduces the ability of short sellers to predict negative future returns within this market sector. In untabulated tests, we attempt to further explore this issue by segmenting our sample observations based upon whether their tenants exhibited aggregate positive (good news) versus negative (bad news) returns. Unfortunately, while we find limited evidence that return predictability is more pronounced with respect to our positive tenant return observations, the relative paucity of observations with negative returns limits our ability to find significant differences along this dimension, which in turn further diminishes our ability to make definitive conclusions regarding the speed of adjustment to positive versus negative news innovations.

  13. Throughout the empirical analyses in Table 3, we exclusively employ total returns. To the extent investors ignore mundane daily price movements and concentrate more attention on major corporate events and announcements such as earnings and dividend declarations, it has been suggested that price appreciation returns may provide a more appropriate theoretical basis for our comparisons. On the other hand, such an approach ignores the impact of dividend activity on both notional stock prices, as well as any potential strategic dividend behavior on the part of managers. With respect to the current investigation, these conceptual differences are of little to no practical import, as re-estimating our base case Table 3 results exclusively on price returns generates results which are virtually identical to those found using total returns. Specifically, our equally-weighted return differences accruing to the Buy-Sell portfolios average less than a 1 basis point return difference across the two competing methodologies, while the value –weighted results are approximately 2 basis point higher (on average) using exclusively price returns.

  14. Throughout the heterogeneity examinations which follow, we report results exclusively using value-weighted returns. Results from using equally-weighted returns produces qualitatively similar results and are available directly from the authors upon request.

  15. See, for example, Shleifer and Vishny (1986), Huddart (1993), and Maug (1998).

  16. For international evidence on the importance and efficacy of corporate governance in public, securitized real estate markets see Kohl and Schaefers (2012) and Lecomte and Ooi (2013).

  17. For examples of studies using Google search volume to explore financial and economic phenomena, see Da et al. 2011, Fang et al. 2016, etc. See Mori (2015) and Meshcheryakov (2018) for examples of similar methodologies applied within the context of real estate markets.

  18. Retail leases often contain percentage rent clauses designed to align the interests and incentives of landlords with those of their tenants. Such clauses, as with management fees based upon center revenue, further strengthen and underscore the economic relations between REIT landlords and their tenants.

  19. Conceptually, lease commitments may be viewed in a manner similar to fixed-income security contracts. Changes in tenant risk alter the required return on these contracts, with resulting price volatility implications magnified over longer investment horizons.

  20. This lag also mimics the standard gap imposed across the existing literature to match accounting variables to subsequent price and return data. See, for example, Fama and French (1993).

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Acknowledgements

We thank Zhixiang Deng, Masaki Mori, Joseph Ooi, and Xiaodi Zhang, as well as seminar participants at the University of Central Florida, College of Charleston, St. John’s University, Western Kentucky University, 2016 Southern Finance Association (SFA) annual meetings, 2017 Financial Management Association (FMA) annual meetings, 2017 American Real Estate Society (ARES) annual meetings, and Cambridge-Florida-Singapore 2017 Real Estate Finance & Investment Symposium for helpful comments and suggestions on an earlier draft of this paper. Chen acknowledges partial financial support from a SunTrust professorship.

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Authors and Affiliations

  1. College of Business Administration, University of Central Florida, Orlando, FL, 32816, USA

    Honghui Chen & David M. Harrison

  2. Catawba College, Ketner 324, 2300 W. Innes St, Salisbury, NC, 28144-2441, USA

    Mahsa Khoshnoud

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  1. Honghui Chen
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Correspondence to David M. Harrison.

Appendix

Appendix

Table 10 Tenant momentum strategy, abnormal returns 2000-2013 (by minimum # of publicly traded tenants)
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Table 11 Tenant momentum strategy, abnormal returns 2000-2013 (by tenant concentration)
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Chen, H., Harrison, D.M. & Khoshnoud, M. Investors’ Limited Attention: Evidence from REITs. J Real Estate Finan Econ 61, 408–442 (2020). https://doi.org/10.1007/s11146-018-9667-y

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