Identifying Equity REITs Worth Keeping Versus Those To Avoid Right Now - Part II: Data-Center And Storage (NYSEARCA:VNQ) (2024)

Background

Earlier this month, I've presented an analysis regarding the performance of mortgage-REITs (REM, MORL), "mREITS" hereinafter, during periods of increasing rates and yields. In total, I've covered forty names across four different types (of mREITs): Commercial, Residential, Hybrid/Special and Traditional/Agency. The main findings when it comes to mREITs performance during increasing rates and yields periods were:

• While the performance of the sub-groups varied, commercial mREITs - e.g. ARI, LADR, STWD, BXMT (The first three names are part of my A-Team) - have outperformed the other sub-groups.
• Few selective names (NRZ, ARI, BXMT, STAR) have continuously and consistently outperformed.

(Side notes: NRZ is one of my top picks and I have recently explained my preference for ARI over BXMT from a risk/reward perspective, at least when it comes to the A-Team purposes)

The mREITs analysis was not only comprehensive but it also assisted me in arranging my own thoughts and views in regard to both past and future actions that I took/need to take when it comes to various mREITs that I held/hold.

As such, I believe that just as the mREITs coverage was helpful in better understanding the resilience of mREITs to higher rates/yields, it can be beneficial to run the exact same analysis with eREITs. Not only because I believe that mREITs are better positioned than eREITs, but especially since I believe that many eREITs are overvalued and, as a result, I have short positions in more than a handful of those that are part of my H-Team.

Part I of this series focuses on residential eREITs

Part II - the one you're currently reading - is focusing on data-center & storage eREITs.

eREITs: A Much Bigger and More Diversified Universe than mREITs

There are ~x6 more eREITs than mREITs. There is also far greater diversification within eREITs-dom than the 4-5 different types of mREITs. As such, it doesn't make sense - technically (too long) and fundamentally (too different) to cover the eREITs arena altogether in a single article.

Therefore, I'm cutting the eREITs analysis into smaller parts/articles; each part/article is focusing on a different type of eREITs.

Before presenting the list of the eREITs that will be part of the analysis, there are few important clarifications that need to be made:

1. Companies with a market cap <$100mil. and/or <18-month track record were automatically "disqualified".
2. The classification of the groups has been done on a "best effort" basis. In more than a few cases, companies could easily be placed in more than one group. Nonetheless, even in cases where a company fit more than one group, it was placed within the group that most closely characterized it to my best judgment.
3. When applicable (only for three types of eREITs) and for the purpose of this specific analysis, the $3bn mark is what distinguish between large caps (>$3bn) to small caps (<$3bn)

Here is the list of all the 120 eREITs that are going to be part of this analysis, sorted alphabetically by their respective tickers:

The 120 eREITs were spread out across 11 different types of eREITs (Including three types that were separated into large and small caps due to the large number of companies and/or wide range of market caps within the specific classification).

While, as mentioned above, few names may belong to more than one type I believe that the above list is both comprehensive and representative; it's a well balanced-diversified reflection of the eREITs segment as a whole as well as an accurate-focused mixture of names within each type of eREITs.

Methodology

In total we have eleven sub-groups of eREITs:

1. Apartments: AIV, APTS, AVB, BRG, CPT, EQR, ESS, IRET, IRT, MAA, MORE, UDR
2. Data-Centers & Storage: CONE, COR, CUBE, DFT, DLR, EQIX, EXR, IRM, NSA, PSA, QTS
3. Healthcare, Large-Caps: ARE, HCN, HCP, HR, HTA, MPW, OHI, SNH, VTR
4. Healthcare, Small-Caps: CCP, CHCT, CTRE, DOC, LTC, NHI, SBRA, SNR, UHT
5. Hospitality, Large-Caps: APLE, HPT, HST, LHO, RHP, RLJ, SHO
6. Hospitality, Small-Caps: AHP, AHT, CHSP, CLDT, DRH, FCH, HT, INN, PEB, XHR
7. Industrial/Commercial: DCT, DRE, EGP, FR, GOOD, GPT, LPT, PLD, PSB, REXR, STAG, TRNO, WPC
8. Shopping-Centers & Malls, Large-Caps: BRX, DDR, EQY, FRT, GGP, KIM, MAC, REG, RPAI, SKT, SPG, TCO, WRI
9. Shopping-Centers & Malls, Small-Caps: AKR, CBL, KRG, PEI, ROIC, RPT, SRG, UBA, UE, WHLR, WPG, WSR
10. Special: ACC, AMT, CCI, CORR, DEA, EDR, FPI, GLPI, GOV, HASI, LAND, MYCC
11. Triple Net Lease: ADC, EPR, FCPT, GNL, LXP, MNR, NNN, O, OLP, SRC, STOR, VER

Over the past five years, we have witnessed three periods of rising rates/yields:

• Period I: 4/26/2013 - 12/27/2013
• Period II: 1/30/2015 - 7/3/2015
• Period III: 7/8/2016 - 12/15/2016

For each type/classification of eREITs there are three charts that show the performance of the relevant group of companies during the three periods - three charts per group, one chart per period.

Then, the average return for each group during each period was calculated in three different ways:

• Average based on all the observations (of all the companies that publicly-traded) during the period.
• Average that excludes the best and the worst observations that were recorded during the period.
• Median or average of the median (if it comprises of two observations).

By excluding the best and worst, we "soften" the "bumps" that may occur due to specific/extreme news/events that may have affected a certain company. In other words, we avoid temporary "noise".

After receiving three different averages, I calculated an equal-weighted average for all three averages. By doing so I believe that the data is more reliable and less affected by temporary specific news, events or returns that one or two companies may have gone through the examined period.

Bear in mind that this is a relative drill - an attempt to point out at specific types and names of eREITs that perform more or less favorably during periods of higher rates/yields. Therefore, more than an accurate mathematical-scientific result I'm mostly interested in presenting the trends and the different performances of various types of eREITs'. That way, we will be able to draw better conclusions regarding each sub-group's relative strength compare to other sub-groups within the eREITs segment.

Comparisons

Before presenting the charts for the specific eREITs' sub-group that this article focused on, it's worthwhile taking a closer look at how the main-best comparable ETFs have performed during the three periods (of higher rates/yields) that we examine.

Here is how the Vanguard REIT Index ETF (NYSEARCA:NYSEARCA:VNQ), the iShares U.S. Real Estate ETF (NYSEARCA:NYSEARCA:IYR), the US Treasury 10-Year and 30-Year yields (UST, TLT, PST, TBF, TBT) and the SPDR S&P 500 Trust ETF (NYSEARCA:SPY) performed during the relevant periods:

• Period I: 4/26/2013 - 12/27/2013
• Period II: 1/30/2015 - 7/3/2015
• Period III: 7/8/2016 - 12/15/2016

As we can see, during periods of higher rates/yields, the real-estate related ETFs (VNQ, IYR) performed poorly. That is true in both absolute, i.e. negative returns, and relative, i.e. outperforming the SPY, terms.

Clearly, this should come as no surprise to anyone. I have wrote a couple of times about the relationships between rates/yields to eREITs prices; while the former move higher the latter move lower.

This fact only makes this analysis even more challenging/intriguing because, knowing that eREITs underperform during period of increasing rates/yields, the real question is: Can we find specific names that may strive while most ,if not all, of their eREITs peers suffer?

Why Combining Data-Center & Storage eREITs?

There are two main reasons why I've decided to combine the two sub-groups, data-center and storage - into one type of eREITs:

1. Quantity/Size: There aren't enough names belonging to these two sub-groups. While I wish to have at least 8 names per sub-group, there are only 6 data-center eREITs (CONE, COR, DFT, DLR, EQIX, QTS) and only 5 storage eREITs (CUBE, EXR, IRM, NSA, PSA).

2. Substance/Similarity: The storage element very much exist in data-center eREITs too. Although the content of the stored items and the identity of the "tenants"/customers are different - "storage" seems like a common ground with enough substance.

Nevertheless, in order to capture both the similarity as well as the differentials between the two types, I'm providing in this article data regarding the combined "storage sub-group" as well as for each type separately.

While I stick to three charts, when presenting the calculations and conclusions I'm also referring to data-center and to storage (pure plays) separately. In a way, the reader, i.e. SA, gets here two products (sub-groups) for the price of one (article)... Sounds like a good deal to me, isn't it?

Data-Center & Storage eREITs - Charts and Analysis

Chart 1: Data-Center & Storage eREITs, 4/26/2013 - 12/27/2013

(Please note that this chart contains no data regarding NSA because it wasn't a public company as of yet during the relevant period)

Data regarding the combined data-center & storage eREITs sub-group

Average including all observations: 1.84%

Average excluding best and worst observations: 1.40%

Median: -1.47%

Average performance of all three averages: 0.59%

Data regarding the data-center eREITs only

Average including all observations: 3.06%

Average excluding best and worst observations: 2.79%

Median: 3.55%

Average performance of all three averages: 3.13%

Data regarding storage eREITs only

Average including all observations: 1.50%

Average excluding best and worst observations: -0.47%

Median: -0.47% (=same result as the above since there are only four storage eREITs for this period)

Average performance of all three averages: 0.19%

Chart 2: Data-Center & Storage eREITs, 1/30/2015 - 7/3/2015

Data regarding the combined data-center & storage eREITs sub-group

Average including all observations: -0.58%

Average excluding best and worst observations: -0.17%

Median: -0.09%

Average performance of all three averages: -0.28%

Data regarding the data-center eREITs only

Average including all observations: 2.58%

Average excluding best and worst observations: 1.69%

Median: 1.64%

Average performance of all three averages: 1.97%

Data regarding storage eREITs only

Average including all observations: -4.38%

Average excluding best and worst observations: -2.89%

Median: -2.30%

Average performance of all three averages: -3.19%

Chart 3: Data-Center & Storage eREITs, 7/8/2016 - 12/15/2016

Data regarding the combined data-center & storage eREITs sub-group

Average including all observations: -14.54%

Average excluding best and worst observations: -14.68%

Median: -14.50%

Average performance of all three averages: -14.57%

Data regarding the data-center eREITs only

Average including all observations: -13.40%

Average excluding best and worst observations: -12.99%

Median: -13.25%

Average performance of all three averages: -13.21%

Data regarding storage eREITs only

Average including all observations: -15.91%

Average excluding best and worst observations: -17.24%

Median: -18.00%

Average performance of all three averages: -17.05%

Data-Center & Storage eREITs - Main Results and Findings

First, let's put the data that we gathered from the charts into tables:

Data regarding the combined data-center & storage eREITs sub-group

Data regarding the data-center eREITs only

Data regarding storage eREITs only

There are few conclusions one may draw regarding data-center & storage eREITs out of the data during periods of higher rates/yields:

1. After examining the first two periods, data-center eREITs seemed like "the real thing" - the ultimate eREITs to weather periods of increasing rates/yields. Then came the third period with a horrible data that overshadowed the previous two periods positive data. This proves two things that investors should always bear in mind: i. Reality always wins; it may take more or less time but at the end - the "this time is different" self-conviction hardly ever materializes, and ii. It's much easier and it takes much less time to lose than to gain. One lousy period can easily wipe out many positive periods.
2. As expected, the data-center eREITs outperformed the storage eREITs during each and every period. This reminds me of my pair-trading strategy and I should probably add a new pair going forward: Go long data-center eREITs against shorting storage eREITs. This seems to be working just as accurately as a Swiss clock.
3. Although not even a single name managed to perform throughout all the three periods, some did much better than others. EQIX and QTS are the only two names in the combined sub-group that managed to record an average positive return along all three periods (combined).
4. On the other side of the scale - PSA and CUBE "shine" for the wrong reasons. these two names recorded negative returns on each and every period of increasing rates/yields. Investors may prefer to adopt a "dogs of the Dow" kind-of theory or perhaps claim that "this time it's going to be different (for sure!)" but the facts are facts.

Bottom Line

The bottom line is very easy and very clear:

• Equity REITs: Not the place to be during increasing rates/yields periods. Even data-center eREITs may fall and even the ones seem most immune among them all can be victims of a very unfriendly environment.
• Data-center & storage eREITS: The combined averages point out that this double-head sub-group is not performing too well during increasing rates/yields periods. However, there's no doubt that data-center eREITs have the ability to weather the storm much better and in some cases to ignore the "noise". Just as we conclude in regard to residential eREITs: If you really feel like you "must" own a few (eREITs) - data-center eREITs may be a worthwhile sub-segment to focused on.
• Among data-center eREITs there are two names that lead the pack during periods of increasing rates/yields: EQIX and QTS.
• Among storage eREITs there are two names that lag substantially during periods of increasing rates/yields: PAS and CUBE.

Please note that the above are only interim conclusions. Final-decisive conclusions regarding the entire eREITs segment will be drawn only when this eleven-part series will come to an end.

Only after analyzing all types of eREITs we will be in a position to better differentiate between right ("resilient eREITs") and wrong ("under-threat eREITs") when it comes to investing in eREITs during periods of rising rates/yields. Bear with me, be patient and stay tuned!

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