Fama–French–Carhart Factor-Based Premiums in the US REIT Market: A Risk Based Explanation, and the Impact of Financial Distress and Liquidity Crisis from 2001 to 2020

Round 1

Reviewer 1 Report

The paper contains several obvious statistical errors.

First, the Sharpe Ratios presented in Table 2 and later (at least through Table 6) are incorrect. They are not the ratio of mean excess return and standard deviation. I checked if there was confusion between standard deviation and variance, if the risk-free rate was not subtracted correctly, or if it was a typo. None of these.

Second, footnotes 6 and 7 are wrong. Footnote 6 should be exactly reversed. Footnote 7 is also incorrect given standard definition of kurtosis: excess kurtosis indicates thicker tails. A higher peak and more concentration around the mean may just represent a lower variance.

Third, the results in Table 2 and later for the factor loadings are off. For instance, in Panel C, the s1 coefficient (for small REITs) should be positive and the s5 coefficient for large REITs) negative if there is a positive size premium for REITs.  Certainly, if the SMB factor is constructed from REITs as indicated in the Appendix, this is almost a mathematical certainty.

At this point I stopped reading carefully since I felt that none of the results can be trusted.  If the basic results already contain such negligent errors, the more complex analysis becomes very unreliable.

My preliminary comments at the time I stopped reading were as follows:

1.       It is very unclear whether you are using the factor returns from Fama-French or those constructed yourself from the REITs. If you use the factors from the REITs, it seems they are not systematic.  It makes little sense to study risk properties of REITs in a vacuum. They are exchange-traded assets just like stocks and generally part of portfolios that do not exclude other asset groups.

2.       If you use the Fama-French factors these are generally interpreted as capturing the risk of changes in future investment opportunities (i.e., Merton factors). Any alphas on REITs would be risk-free only if there are no omitted factors capturing investment opportunity changes. Hard to argue that these omitted factors are necessarily captured by the credit spread or liquidity.

Author Response

Please see attached.

 

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper examines the impact of financial distress and liquidity crises on premiums for US REITs over 2001-2020. An extensive econometric analysis is carried out on 246 REITs using procedures such as ADL, ECM and GC by employing the FFC models to assess the role of a number of factors on US REIT performance. Robustness checks are also conducted.

Comments: 

1: at 65 pages, this paper is far too long for a journal article; it needs to be reduced significantly; similarly with 25 tables and 6 figures and over 120 references, this is far too many; reduce significantly and refocus paper

2: P1: mention REITs deliver direct RE performance; see Hoesli papers

3: P1: reference is often made to REITs where it should be US REITs; US is not only REIT market globally

4: mention scale of global REIT markets as RE investment vehicle; US is about 65% of global market, but acknowledge there are other REIT markets

5: Table 13: are correlations significant

6: discussion is only statistical; there is nothing about practical investment implications about strategies for use of REITs by institutional investors. This needs to be expanded considerably.

7: references are largely finance or financial economics; this sees paper reading as being written by authors who seem to have found REITs as a data set and just rehash standard analysis procedures, with minimal understanding of what REITs are and their role in investment market

8: many of aspects are already assessed for stocks overall; why does analysis of REITs add value; are they different or have unique features. This is further compounded by length of paper; where is added value.

Overall, paper needs to be considerably reduced to fit into style of journal article, as well as addressing the above changes.

 

 

 

 

 

Author Response

Please see  the attached document.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

This paper investigates the premiums within the REIT market and strategies that yield superior returns. Overall, while I think the paper is carefully executed, I believe it is trying to do a bit too much. For instance, the paper is at a whopping 65 pages with 25 main tables, and it is one of the longest titles I have ever seen. On the one hand, the analyses are comprehensive. On the other hand, it also weakens the focus of the paper by trying a little too much to cover everything on premiums of the REIT market.

The paper keeps claiming it is novel to examine these premium factors. It is not exactly true. Note many studies (e.g., Ooi et al., 2007; Hung and Glascock, 2008; Goebel et al., 2012) have examined these factors within the REIT market, though may not be as comprehensive as the current study with the same period. Similarly, this study is not the first to understand the impact of financial crises on REIT returns. There are many studies that document REIT investors exhibit a “flight-to-quality,” which the current literature review has overlooked. There should also be more justification on why the effect of oil price is important in the current context. There are many important macroeconomic factors, and it is hard to see a direct and causal link between oil prices and real estate. Similarly, despite the reference of several studies related to exchange rate, there should be a better and stronger argument on how exchange rate affects the U.S. REIT market. Is the channel solely through retail and tourism? If so, how does its spillover spread to the office and residential markets? Or, are some of the REITs heavily exposed to foreign holdings?

Regarding the empirical findings, it would be helpful to highlight the REIT setting by comparing and contrasting how the current findings compare to prior studies in the result section. The comparison could be to general sample as well as REIT studies that focus on individual factors.

As mentioned, the paper is very long with a lot of tables. Note you are examining multiple factors and multiple determinants, there should be some ways you could streamline the presentation and present significantly fewer tables.

Given that many macroeconomic factors are correlated (despite your VIF showing low values), how could you arrive at conclusions that some findings are primarily driven by one factor? Is there a way to handle the multicollinear issue in your portfolio strategies?

There are some minor issues on formatting. First, perhaps it would be clearer to call the portfolios by different names instead of Q1, Q2, Q3, etc. (e.g., Table 2) as this could be confusing as Q could be quartile, quintiles, etc. Note the Qs do not exactly correspond to the columns of numbers in some places (e.g., Panels B-D in Tables 2-6).  

At the end, even the conclusions are about 2 pages long. Be precise and tell the readers what is novel about this study.

Author Response

Please see the attached document.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The paper has improved a bit and I now have a better idea of what you are trying to do.  Some remaining problems.

1.  The concept of risk you are using is unclear. When dealing with equilibrium pricing issues you need to refer to systematic risk.  You refer to "arbitrage risk". It is not clear to me what you mean by that. The best explanation of the risk found in the Fama French models is based on Merton's idea of uncertainty about future investment opportunities.

2. The "own" factor sensitivities that you show in Panels B of Tables 2 through 6 do not make sense and should be discussed.  For instance, for the SMB sensitivities in Table 2 the Small Q1 REITS are expected to have the largest (likely positive) sensitivity and the Large Q5 REITS the smallest (likely negative) sensitivity the the SMB factor. This is actually reversed in your results.  Why?

3. It is still not clear why it is interesting to look at SMB, RMW etc. premiums in the REITs market in isolation since these premiums should be based on systematic risk. Since REITs are not a self-contained group of assets I can see very little meaning to these "premiums"

4.  The most significant result that I see, from Table 2 is that FF5 alphas are non-zero (positive) and economically large the smallest REITs.  This appears to be related to a liquidity issue.

Author Response

please see file attached (entitled reply to reviewer 1, second round, 14-12-022)

Author Response File: Author Response.docx

Reviewer 2 Report

Whilst authors have revised paper in most areas, it is still totally lacking in any practical implications for REIT investors; it is just masses of models and regressions with no practical insight. A separate section is needed on this; it was requested in earlier referee's report.

 

 

 

 

Author Response

please see attached.

 

Author Response File: Author Response.pdf

Reviewer 3 Report

No further comments.

Author Response

no file attached. reviewer 3 requested no further changes. THANK YOU, 

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