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The Journal of Real Estate Finance and Economics

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01-11-2013

Who Says there is a High Consensus Among Analysts when Market Uncertainty is High? Some New Evidence from the Commercial Real Estate Market

Authors: James D. Shilling, C. F. Sirmans, Barrett A. Slade

Published in: The Journal of Real Estate Finance and Economics | Issue 4/2013

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Abstract

This paper seeks to determine whether analyst consensus is a function of the level of price informativeness, and therefore attempts to gauge the extent to which analyst consensus is high when market uncertainty is high. There is the view that a small or declining volume of trading implies less information and lower quality information, and that a lower level of price informativeness will lead analysts to put more weight on their private information at the time of forecasting. We add to this view the notion that when uncertainty is high there might be a positive option value of waiting. In this case, it appears reasonable to conclude that analysts may actually lack consensus when uncertainty is high. If this hypothesis is correct, then one would expect the level of price informativeness to override the Keynesian incentive “to fail conventionally than to succeed unconventionally” or at least reduce its magnitude in periods of declining trading volume and low price discovery. Tests of this hypothesis produce favorable results.

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As discussed in McDonald (2000) and elsewhere, a project should be taken today only if it has a positive NPV, or, equivalently, only if the IRR is greater than a fixed and relatively invariant hurdle rate of, say, 10 to 15 % (unlevered). Therefore, if (unlevered) discount rates are being forecasted, very few observations should be far from, say, 10 to 15 % (assuming investor rationality) and so few deviations will be large, no matter the level of uncertainty. If these observations are true, little deviation in the expected return on a project should lead to very little deviation in analyst consensus.

We also investigated the case of apartment buildings (results not reported). We generally find similar patterns for the degree of consensus rates of return and market rent changes for office buildings and apartments, with one possible exception, the degree of consensus for market rent changes is considerably higher for apartments compared with office buildings in 2009–2011. One explanation is that there are more buying and selling opportunities and, hence, greater trading volume and price informativeness in the case of apartments than for office buildings. Holding all else constant, greater price informativeness implies greater analyst consensus.

A large literature has arisen as to whether that public and private real estate markets process information differently. Most of this literature has considered whether publicly-traded REITs and private equity real estate investments provide investors with similar rates of return. Glascock et al. (2000) and Yavas and Yildirim (2011) find that the two returns are cointegrated and that the price discovery process starts in the public market and information is transmitted to the private market, with a feedback loop between the two markets. For a review of the early works in this area, which generally suggest little correlation between the rates of return on publicly-traded REITs and private equity real estate investments, see Corgel et al. (1995). See, also, Barkham and Geltner (1995) who that the rates of return on private equity real estate investments lag securitized markets by more than 1 year. We know of no study, however, that examines whether analyst consensus is higher or lower in the public market than in the private market.

Williams (1993) and Grenadier (1996, 1999, 2005), among others use option exercise games to understand real estate markets. In these studies, the early entry of a developer/investor conveys private information to other investors in the market. Hence, as soon as one investor identifies, say, an opportunity to earn a positive economic profit, other investors will quickly follow suit, marching as one with each other. As the transition grows, all investors end up on the same investment path, with homogeneous expectations about asset returns (even in uncertain times). Thus, if there are leaders and followers, and if developers/private equity real estate investors are leaders and others are followers, then while there might be times where the public market generates better information than the private market, more often than not the opposite should be true. In either case, whether public analysts’ forecasts are more accurate than private analysts’ forecasts is an empirical question that needs to be investigated.

SFAS 87 requires firms to look ahead and estimate the pension benefits that current employees are likely to receive when they retire and to discount these pension benefits at the rate equal to the expected return on plan assets.

The base model relates IRRIndex _Pt ^* to z _Pt and MRCIndex _Pt ^* to z _Pt in the long-run : IRRIndex _Pt ^* = α + πz _Pt− 1 + μ _Pt and MRCIndex _Pt ^* = γ + ηz _Pt− 1 + μ _Pt. Next, the rate of adjustment towards the long-run equilibrium is assumed to ΔIRRIndex _Pt = ψ(IRRIndex _Pt ^* − IRRIndex _Pt − 1 ^* ) + (IRRIndex _Pt − 1 ^* − IRRIndex _Pt − 1) and ΔMRCIndex _Pt = λ(MRCIndex _Pt ^* − MRCIndex _Pt − 1 ^* ) + θ(MRCIndex _Pt − 1 ^* − MRCIndex _Pt − 1) where ψ, ϕ, λ and θ ∈ (0, 1), i.e., the rate of adjustment towards the long-run equilibrium depends on the change in the long-run equilibrium values and the past period’s disequilibrium. Finally, the model allows for a dynamic relationship between the dependent variables (which explains why ∆MRCIndex _Pt-1 shows up in the ΔIRRIndex _Pt equation and vice versa).

For some previous evidence on whether forecasters do a good job of predicting rental growth and future property returns, see Ling (2005).

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Title: Who Says there is a High Consensus Among Analysts when Market Uncertainty is High? Some New Evidence from the Commercial Real Estate Market
Authors: James D. Shilling
C. F. Sirmans
Barrett A. Slade
Publication date: 01-11-2013
Publisher: Springer US
Published in: The Journal of Real Estate Finance and Economics / Issue 4/2013
Print ISSN: 0895-5638
Electronic ISSN: 1573-045X
DOI: https://doi.org/10.1007/s11146-013-9430-3

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Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail

Are REIT IPOs Unique? The Global Evidence

Local Traits and Securitized Commercial Mortgage Default

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