Benefits of Direct and Securitized Real Estate Allocations

BeneŽts of Direct and Securitized Real
Estate Allocations within a Mixed-Asset
Portfolio
Karen Mitchell Smith*
INTRODUCTION
It has been found through numerous stud-
ies that real estate is an important component
of a well-diversiŽed portfolio. With the advent
of ERISA in 1974, pension funds have been
investing in real estate through various
vehicles, though most notably through direct
property acquisitions and securitized Real
Estate Investment Trusts (REITS).
Modern portfolio theory, developed by
Harry Markowitz in 1952, outlines the ben-
eŽts of diversiŽcation in a manner that
minimizes the variance of a portfolio without
necessarily sacriŽcing total returns. As an
asset class, real estate plays an integral role
in reducing risk in pension funds that focus
predominantly on the mean and variance of
portfolio returns.
Ciochetti, Craft and Shilling1
have shown
that private real estate investment by pen-
sion funds has little inuence over whether
said fund also participates in securitized REIT
ownership. Thus, the fact that a pension fund
may currently be invested in a single form of
real estate does not necessarily mean that it
will invest exclusively in that speciŽc real
estate vehicle.
Hence, is there a fundamental dierence
between owning securitized and non-
securitized real estate in such a portfolio? Is
owning both types of assets in a single
portfolio a form of naive diversiŽcation, or
can the argument be made that both types of
real estate should have a place in an “opti-
mal” portfolio allocation? These are two
questions which will be explored in this
paper.
Indeed, there is a debate in the academic
literature and among practitioners whether
there is a beneŽt derived from direct real
estate ownership and securitized real estate
such as REITs.
Direct real estate is considered to have
advantageous attributes, such as the ability
to invest in individual properties that are
distinctive in terms of Žnancial performance,
the potential to provide favorable tax advan-
tages, and the fact that direct real estate has
a low, even negative, correlation with the se-
curities markets, including that of securitized
real estate, which makes it an attractive
diversiŽer to these markets. Disadvantages
inherent in direct real estate are noted as
*Karen Mitchell Smith is a doctoral candidate at the Henley Business School, University of Reading. In addition
to attending the Henley Business School, Ms. Smith is a Managing Partner with Graham Mitchell Consultants,
specializing in compliance for Investment Management Firms and Hedge Funds. Previously, Karen was employed as
the Head Securities Trader for European Investors, Inc. and Robert E. Torray & Co., Inc.
Editor's Note: Special thanks to Dr. Tom G. Geurts for his editorial comments and encouragement.
Real Estate Review E No. 2
© Thomson Reuters
45

increased transaction costs, and the illiquid-
ity and lack of transparency in this market.
The advantages of the securitized real
estate market are that this asset class has a
pre-established management team that is
presumably knowledgeable within each mar-
ket, thus reducing management and search
costs at the individual pension fund level.
Moreover, there is the ability to attain owner-
ship positions in a portfolio of properties with
less capital outlay through the purchase of
shares of one or multiple REITs. And, Finally,
REITs are considered to be a liquid proxy for
direct real estate.
Indeed, Ciochetti, et al2
identiŽed liquidity-
constrained pension funds as having the
strongest preference for REITs, thus an es-
sential argument involves volatility risk versus
illiquidity risk. To illustrate this point, while
the REIT market is much more liquid than
direct real estate, the NAREIT Composite
Index, the widely accepted proxy for securi-
tized real estate, exhibits the strongest cor-
relations to small-cap stocks in the Russell
2000 Index (Exhibit I).
The variance of the Russell 2000 Index is
10.54%. One of the reasons that the Russell
2000 is more volatile than most other classes
of equity is because securities with smaller
market capitalization are less liquid, thus the
spread between the price bid and the price
oered can be much greater than a more liq-
uid security.
However, though the historic variance of
the NAREIT Composite has been substantially
lower than the Russell 2000 at 7.15% (Ex-
hibit I), and though there has been an increase
in the average market cap of the REIT mar-
ket overall, many of the NAREIT Composite
Index's constituents either qualify as, or
behave like, small cap stocks. This indicates
that like direct real estate ownership, there is
also inherent liquidity risk in the REIT market
as well.
As noted by the volatility in the Russell
2000, if a security or an index has a smaller
general market capitalization, a sell-o of any
Real Estate Review
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46

given security, sector, or market may have
much the same eect on liquidity as in direct
real estate. Thus, those pension funds invest-
ing in securitized real estate for the sole ben-
eŽt of increased liquidity may experience the
same problems encountered by direct real
estate holders during a market downturn: il-
liquidity, a lack of transparency, and the sale
of shares below what would be considered
reasonable given the value of the underlying
assets.
REAL ESTATE MARKETS AND PENSION
ALLOCATIONS
Following the Žndings of Chun, Chiochetti,
and Shilling3
that the inclusion of real estate
in a stock-and-bond portfolio improves a
pension plan's overall returns in a mean-
variance space, a ‘typical’ pension portfolio
would consist of large, mid, and small-cap
equities, bonds, and real estate. Though
previous studies suggest that an optimal real
estate allocation for an institutional portfolio
is roughly 30–35%4
, pension funds have al-
locations of only 2–3% in this asset class5
.
The commercial real estate market is
valued at an estimated at $4.6 trillion and
pension funds account for approximately
23.3% of the investment in this sector6
. As
noted above, actual real estate allocations
within pension funds are far below what they
should be for optimal performance. However,
given the size of the overall real estate mar-
ket, it is ever more possible to satisfy in
increase in real estate allocations within pen-
sion funds without sacriŽcing the beneŽts of
the asset class itself.
INDICES
In looking at the question of direct and
securitized real estate and their place in a
pension fund, a number of indices were used
in this paper's analysis to represent the
aforementioned ‘typical’ pension fund's do-
mestic allocation choices: Large-cap, mid-
cap, and small-cap stocks represented by
the Dow Jones Industrial Average (INDU), the
Standard & Poor's 500 (SPX), and the Rus-
sell 2000 (RTY) indices respectively.
The bond allocation is represented by the
Smith Barney Broad Investment Grade Bond
Index (SBBIG), and securitized real estate by
the FTSE NAREIT Composite Index
(FNCOTR).
For direct real estate, there are two indi-
ces; the appraisal based NCREIF Index (NPI)
and the MIT Transactions-Based Index (TBI).7
The rationale for including two direct real
estate indices is the following: The NPI Index
is based on appraised values, not historical
cost. This gives rise to two major issues with
comparing it to securitized indices.
First, there is the potential for an artiŽcial
‘smoothing’ of data that is inherent in the ap-
praisal process that artiŽcially lowers the
variance of the NPI.8
There have been stud-
ies, such as the one done by Salama9
who
‘unsmoothed’ the NPI data and the result was
a much higher risk rate than the NPI indicates.
However, there have also been studies that
show that the long term low variance of the
NPI is more of a result of the lease structure
that provides a more stable income stream
than that of stocks and bonds.10
Second, the
infrequency of the appraisals in the NPI
means that the index lags changes in the
actual value of real estate.11
This means that
though the index is reported quarterly, the
entire index is only updated partially each
quarter as opposed to the securities indices
which are updated daily to reect changes to
their constituents.
To strengthen our analysis and following
BeneŽts of Direct and Securitized Real Estate Allocations within a Mixed-Asset
Portfolio
© Thomson Reuters
47

the idea presented by Geltner and Gatzla12
regarding a transactions-based index that
would address the issues with the NPI, the
data of the MIT Transactions-Based Index
(TBI) was added to our data set. The TBI is
an index that uses the recent appraised
values of properties in the NPI as a compos-
ite hedonic variable and represents transac-
tion prices that reect variable liquidity in the
real estate marketplace over time by apply-
ing the methodology outlined in Fischer, et
al.13
Additionally, the NPI Index reports the
pre-tax, unlevered total returns (income
return and capital value return) that are gross
of management fees of institutional-grade
commercial properties. As noted by Pagliari
and Webb14
, the NPI Index does not take into
account “dividends”15
paid by reporting
properties.
Dividends and dividend yields play a large
role in the performance of the securitized in-
dices as well, so rather than employ Pagliari
et al's process of creating a dividend series
by subtracting capital improvements from the
NOI, all of the returns used in this paper's
analysis of the indices are calculated on a
historical price-traded basis, non-inclusive of
dividends, so as to provide a more uniform
comparison. The assumption is made that all
dividends have been paid out and there is no
reinvestment of income.
Another index-related consideration in-
volved in this paper's methodology was the
disparity between the levered FNCOTR
index, and the unlevered NPI and TBI indices.
However, the author of this paper is examin-
ing securitized and direct real estate both
separately and together in relation to optimal
portfolio allocations rather than comparing
the two for similarity. They are then evalu-
ated as to how each performs as its own as-
set class and what then the optimal alloca-
tion would be for each class.
Finally, the author does not separate funds
by liquidity or by examining the timeframes
for pension liability16
as these factors are dif-
Žcult to standardize over multiple time
periods. Rather, the focus is on investigating
allocations strictly in relationship to Markow-
itz's ecient frontier.
RETURNS, VOLATILITY, AND CORRELA-
TIONS
The average returns over 10-, 15-, and
20-year annual time frames are shown in Ex-
hibit II. Note that for all of the time-frames, on
a price-traded basis, real estate outper-
formed all of the asset classes. The FNCOTR
was Žrst in the 15- and 20-year time frames
with the TBI Žrst in the 10-year time frame.
The 20-year time frame does include the
stock market crash of 1987, as well as the
period between 1987 and 1993 marked by
the RTC. Thus, this period incorporates
periods marked by volatility and illiquidity for
all asset classes.
Real Estate Review
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48

Volatility during the same time periods
noted above, as represented by standard
deviations in Exhibit III, shows that the Rus-
sell 2000 Index possesses the greatest vari-
ance in all noted periods.
Examining the volatility of both direct real
estate indices and the bond index, the great-
est period of volatility is the 20-year period
with each successive period examined il-
lustrating a progressive decline in volatility,
with the 10-year period being least volatile.
However, each of the securities indices,
including the FNCOTR, exhibits the greatest
volatility over the 10-year period, followed by
the 20-year period that is inclusive of the
stock market crash. It appears that the stock
market crash had more of an eect on the
volatility of the equity markets than did the
period marked by the RTC for the direct real
estate markets.
The NPI consistently exhibits the lowest
volatility in all time periods, followed by the
bond index, though this may be a result of
the previously noted data smoothing relative
to the appraisal process.
In fact, within the 20-year time period of
March 1987 through March 2007, the NPI
only reported below average quarterly returns
in the years 1991, 1992, and 1993. Although
the volatility of the FNCOTR is greater than
either the NPI or the TBI, when looking at
securitized real estate, it is still lower than all
of the other securities indices. Hence, pen-
sion funds, with their need to limit downside
risk, should Žnd a combination of both direct
real estate and securitized real estate a bet-
ter investment option over the long term in
relationship to either stocks or bonds in
regards to both the returns noted above and
the lower risk variables noted here.
Correlations for the dierent time periods
are shown in Exhibit IV. This conŽrms earlier
Žndings17
as the NPI exhibits the lowest rela-
tionship to any of the other indices. The
FNCOTR had the least correlation to the NPI
and TBI indices than with any of the securi-
tized indices, with the highest correlation be-
ing with that of small cap stocks. These cor-
Portfolio
© Thomson Reuters
49

relations, or lack of correlations, give strength
to the argument that there is a place for both
securitized and non-securitized real estate in
a mixed-asset portfolio.
In addition; looking at the NPI and the TBI,
we see that they are becoming more posi-
tively correlated with the securities markets
while the FNCOTR is becoming less so. Thus,
the relative weightings for portfolios holding
both forms of real estate may shift substan-
tially as direct real estate becomes more cor-
related to the securities markets including
securitized real estate as direct real estate
loses some of the diversiŽcation beneŽts
sought by pension funds.
Real Estate Review
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50

OPTIMAL PORTFOLIOS
The data that is being used is historical in
nature, thus any interpretations of the data
should not be inferred as a guarantee of
future performance. All portfolios were run
incorporating some form of real estate based
Portfolio
© Thomson Reuters
51

on the assertion that real estate should be
an integral part of a well-diversiŽed pension
portfolio.
Examining the optimization results using
the appraisal based NPI and the securitized
FNCOTR for the 20-year period (Exhibit V), it
was found that direct real estate accounts
for the sole allocation to real estate when the
expected return rates are in the higher
ranges of 8%-10%. The variances for these
portfolios are also higher than the combined
real estate allocations exhibited in the lower
expected return range, at 1.23% to 5.75%,
though they are considerably lower than the
equity-only return and variance of 11% and
9.62% respectively.
Thus, a portfolio that does not include real
estate may expect an additional 1% in return
over one that includes real estate, but this is
tempered by an additional 3.87% in variance.
Real Estate Review
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52

It is also at the 10% expected rate of return
that an allocation is made to real estate, and
said allocation is made in the form of direct
real estate rather than securitized real estate.
As the expected returns drop, it is found that
the overall allocation to real estate increases.
Hence, any allocation to real estate lowers
the overall risk in a portfolio, and for those
funds looking for returns of 7% or less, the
best way to achieve those goals is through
investment in both direct and securitized real
estate.
Portfolio
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53

The same phenomenon is found in the
transactions-based TBI over the same period
(Exhibit VI), though the overall allocation to
real estate drops considerably for the same
expected rates of return with an increase in
investment to bonds to make up the
dierence. The allocations to the FNCOTR
for both indices, given the expected returns
of 6–7%, are within 200bp of each other,
though the direct real estate allocations vary
by half in each case.
Thus, despite the fact that both direct real
estate indices show the closest correlation
to each other relative to the other indices
used in the analysis and that the TBI is only
nominally correlated to the SBBIG, on a
comparative basis there is a marked dier-
ence between the appraisal-based and
transaction-based direct real estate
allocations.
Real Estate Review
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54

Over the 15-year period, the results reect
those of the 20-year period (Exhibit VII & Ex-
hibit VIII), though the combination of real
estate products does not come into play until
the portfolio has an expected 8% annual rate
of return. The largest total allocation to real
estate is seen in a portfolio with a 6% ex-
pected rate of return and is found to decrease
with each percentage increase in expected
return, though real estate in some form is
found to be a part of each allocation.
Portfolio
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Real Estate Review
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In examining the 10-year period, the same
general pattern is found as noted in the 15-
and 20-year time frames. However, the al-
location to real estate overall is higher for
this period with the highest percentage being
Portfolio
© Thomson Reuters
57

found in the portfolio with a 6% expected
return.
Though, as in the other time frames, the
overall allocation to real estate diminishes as
the expected rate of return increases, the
combination of securitized and direct real
estate allocations begins at a much higher
level of expected returns (Exhibit IX & Exhibit
X). This can be explained by both the favor-
able rate of return of real estate relative to
the general securities markets during this
time period, and the lower risk attributed to
these investments.
Of note, the TBI index and the FNCOTR
index are not closely correlated until the 10-
year timeframe, but the allocations to the
pension portfolios are more similar than the
NPI.
Real Estate Review
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Portfolio
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If the data are examined based on vari-
ance rather than expected return, over the
20-year period, portfolios have a greater al-
location to direct real estate, even at higher
expected rates of return. As the portfolio's
risk tolerance decreases, we Žnd an increase
in the allocation to securitized real estate.
This indicates that the advantages of owning
Real Estate Review
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60

direct real estate outweigh the inherent dis-
advantages, as reected in a mean-variance
portfolio.
The percentages of securitized real estate
allocated to the portfolio increase as the al-
locations to direct real estate decrease,
though not in the same proportion (Exhibit
XI). This pattern is even more pronounced in
the 15-year time horizon (Exhibit XII). How-
ever, during the 10-year period, real estate,
both securitized and direct, has heavy, and
usually dual, weightings within the lower risk-
tolerance portfolios (Exhibit XIII). This is,
again, attributed to the superior performance
and lower variance as compared to the other
indices.
Portfolio
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61

CONCLUSION
This study has examined the relationship
between direct real estate allocations and
securitized real estate allocations in a mean
and variance of return-focused pension
portfolio. Any allocation to real estate lowers
the overall risk in a portfolio, though in the
case of funds looking for greater returns and
that have a higher risk tolerance, this study
Real Estate Review
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64

has clearly shown that an allocation to direct
real estate is more favorable than an alloca-
tion to securitized real estate.
When looking at direct real estate, there
are signiŽcant dierences to both overall al-
locations to real estate and the speciŽc direct
real estate allocation when incorporating the
transactions-based index v. the appraisal-
based index into a portfolio using the identi-
cal parameters. Funds with a lower risk tol-
erance beneŽt from a greater weight in real
estate in either form, or in combination, as a
percentage of their overall portfolio.
A portfolio with expected returns of 8% or
lower beneŽt the most from an allocation to
both direct and securitized real estate, with
securitized real estate becoming more heavily
weighted as expected returns decrease.
Finally, funds with a time horizon in the range
of 10-years would have been the greatest
beneŽciaries of both an increased allocation
to real estate overall, and a dual allocation of
direct and securitized real estate.
Though the allocation levels outlined in this
study are unlikely objectives for all pension
funds, it is clearly shown that not only are
pension fund target allocations below what
they should be for optimal performance18
but
the author has also shown that direct real
estate and securitized real estate both have
a place within the asset allocation framework.
The data also have shown that the relative
weightings for portfolios holding both forms
of real estate may shift substantially if direct
real estate continues to become more closely
correlated to the securities markets.
For a pension fund looking to minimize the
probability of not realizing anticipated returns,
both securitized real estate and direct real
estate have been shown to be important con-
stituents in portfolios across a wide range of
expected risk and returns. More importantly,
one should consider each form of real estate
to be a separate allocation category, each
able to act in a complimentary fashion within
the framework of a fully optimized pension
portfolio.
NOTES:
1
Ciochetti, B. A., Craft, T. M., & Shilling, J. D.
(2002). Institutional Investors' Preferences for REIT
Stocks. Real Estate Economics, 30 (4), 567–593.
2
3
Chun, G. H., Ciochetti, B. A., & Shilling, J. D.
(2000). Pension-Plan Real Estate Investment in an
Asset-Laibility Framework. Real Estate Economics, 28
(3), 467–491.
4
Geltner, D., Rodriguez, J., & O'Connor, D. (1995).
The similar genetics of public and private real estate
and the optimal long-horizon portfolio mix. Real Estate
Finance, 12 (3), 13–26.
5
6
Ibbotson Associates Global Real Estate Study:
Optimizing Portfolios With Global Listed Real Estate
Allocations. (2007, May). Retrieved June 2007, from
National Association of Real Estate Investment Trusts
Web Site: www.investinreits.com/webinar/IbbotsonSu
mmary.pdf
7
All quarterly data for the range March 1987–
March 2007 was sourced through Bloomberg Finance
L.P. and the MIT Center for Real Estate (Transactions-
Based Index (TBI). (n.d.). Retrieved June 2007, from
MIT Center for Real Estate Commercial RE Data Labo-
ratory all-QuarterlyIndex.csv: http://web.mit.edu/CRE/
research/credl/tbi.html)
8
Geltner, D. M. (1993). Estimating Market Values
from Appriased Values without Assuming an Ecient
Market. Journal of Real Estate Research, 8 (3), 325–
345.
9
Salama, K. (1995). Measuring Risk in Commercial
Rea lEstate Investments, Real Estate Investing in the
1990's. ICFA Continuing Education. Charlottesville, VA,:
AIMR.
10
Linneman, P. (1989, September). Limitations of
the FRC Index. Baring Investment Property Bulletin, 1
(2), 1–4.
11
Gyourko, J., & Keim, D. B. (1993). Risk and
Return in Real Estate: Evidence from a Real Estate
Stock Index. Financial Analysts Journal, 49 (5), 39–46.
12
Gatzla, D., & Geltner, D. (1998, Spring). A
Transaction-Based Index of Commercial Property and
Portfolio
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65

its Comparison to the NCREIF Index. Real Estate
Finance, 7–22.
13
Fisher, J., Gatzla, D., Geltner, D., & Haurin, D.
(n.d.). Controlling for the Impact of Variable Liquidity in
Commercial Real Estate Price Indices. Retrieved June
2007, from MIT Transactions-Based Index (TBI):
http://web.mit.edu/CRE/research/credl/pfd/FGGH
Variable Liq RRE.pdf
14
Pagliari, J. J., & Webb, J. R. (1995). A Fundamental
Examination of Securitized and Unsecuritized Real
Estate. The Journal of Real Estate Research, 10, 381–
425.
15
As typically reported, the NACREIF Property
Index publishes income, based on net operating income,
and appreciation returns. Pagliari and Webb were able
to obtain additional data outlining capital improvements,
partial sales, and beginning and ending asset values.
The authors then accounted for a separate “dividend
series” that they approximated by subtracting capital
improvements from net operating income.
16
17
Mueller, A. G., & Mueller, G. R. (2003). Public and
Private Real Estate in a Mixed-Asset Portfolio. Journal
of Real Estate Portfolio Management, 9 (3), 193–203.
18
The results of which are in line with previous
studies.
Real Estate Review
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66

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