the case for listed real estate in a multi-asset portfolio

Transcription

THE CASE FOR
LISTED REAL ESTATE IN A
MULTI-ASSET PORTFOLIO
For professional investors
WHITE PAPER
MAY 2016
The asset manager
for a changing
world
The case for listed real estate in a multi-asset portfolio I May 2016 I 2 I
AUTHORS
Xiao Lu, CFA,
is head of quantitative research of financial engineering at
BNP Paribas Investment Partners in Paris, France.
[email protected]
Tel: +33 (0)1 58 97 75 64
Raul Leote de Carvalho, PhD,
is deputy-head of financial engineering at
BNP Paribas Investment Partners in Paris, France.
[email protected]
Tel. +33 (0)1 58 97 21 83
Majdouline Zakaria
is a quantitative analyst in the financial engineering
team at BNP Paribas Investment Partners in Paris, France.
[email protected]
Tel. +33 (0)1 58 97 20 32
Shaun Stevens
is real estate strategist at BNP Paribas Investment Partners
in Amsterdam, the Netherlands.
[email protected]
Tel. +31 (0)20 527 5123
Jan Willem Vis
is chief investment officer of global listed real estate at
BNP Paribas Investment Partners in Amsterdam, the Netherlands.
[email protected]
Tel. +31 (0)20 527 5292
May 2016
BNP Paribas Asset Management,
14 rue Bergère, 75009 Paris, France
BNP Paribas Investment Partners are the source of all data in this document
as at end of March 2016, unless otherwise stated.
ABSTRACT
This is an expanded version of a 2015
paper which sets out to re-examine existing
literature and research on the role of listed
real estate as a proxy for direct real estate
and the impact of listed real estate on the
performance
of
multi-asset
portfolios.
Some investors have formed the view that
listed real estate is an equity product that
cannot accurately replicate the behavior
of a portfolio of directly held buildings.
The findings demonstrate that listed real
estate over the long term can in fact deliver
a comparable performance to direct real
estate and that listed real estate has the
capacity to improve the returns of a multiasset portfolio. The analysis then goes on
to consider the potential for active asset
managers to exploit the differences that may
or may not exist within the listed real estate
universe between countries, sectors and
individual companies.
In this paper, we have expanded our original research into the extent to which
listed real estate can act as a proxy for direct real estate1 in an investment
portfolio and the positive contribution that it can make to returns from a multiasset portfolio. The analysis was expanded in Q1 2016 and reinforces the findings of
our initial study.
Investing in listed real estate companies has still to find a more uniform acceptance
among investors generally. Our initial research set out to address investor
biases. Many investors still favour investing in real estate directly or in unlisted
investment vehicles despite the worldwide growth in real estate investment trust
(REIT) regimes and academic research showing the benefits of investing in both
listed and private real estate.
Our latest research re-examines whether investors can improve the risk/return
profile of their portfolios by including an allocation to listed real estate and
whether listed real estate can be an effective proxy for direct real estate by
delivering similar risk and return characteristics.
One of the more thought-provoking points in the original white paper3 covered
the respective liquidity characteristics of listed and direct real estate and the
opportunities and challenges for investors that liquidity can provide at different
stages of the real estate cycle. The illiquidity of direct real estate holdings is
indeed one of the issues that listed real estate can address successfully. Certain
segments of the real estate market which are more difficult to access due to the
large amount of capital required to invest in them can become readily accessible
to smaller investors when they opt for listed real estate. Even for larger investors,
listed real estate can offer a wider scope for allocating, and managing, exposure to
different segments of the market than would be available in a portfolio restricted
to direct real estate holdings. In this paper, we have expanded the analysis with
new research with the support of Jones Lang LaSalle.
We explored the potential contribution that listed real estate can make to portfolio
diversification, particularly as the balance between risk and reward has become more
complex to manage for institutional investors. The pressure to maximise portfolio
returns has risen as expected returns on risk-free assets have fallen significantly.
With sovereign bond yields forced ever lower by central banks aggressively fighting
declining inflation expectations, the search for alternative sources of yield among
global asset allocators has intensified.
1 Direct real estate includes physical property
investments and unlisted funds.
2 White paper – Zakaria M, Leote de Carvalho R,
Vis J, Stevens S, The case for listed real estate
in a multi-asset portfolio, February 2015,
BNP Paribas Investment Partners.
3 REOCs reinvest dividends in their business.
Real estate has come increasingly into focus, an acknowledgement of its potential
as an income component in overall returns. With this in mind, we assessed whether
listed real estate can improve the risk and return characteristics of a multi-asset
portfolio. However, investors have traditionally seen its relatively high correlation with
risky asset classes such as equities over short periods as limiting its diversification
potential from an ex-ante risk point of view. Despite this, the robust optimisation
techniques employed in our 2015 study and repeated here show that listed real estate
can provide diversification amid uncertainty over return forecasts and variance-
covariance forecasts in a multi-asset portfolio. Moreover, in the long term, listed
real estate tends to show low correlations with other asset classes and thus its
diversification benefits become more naturally apparent.
One of the most persistent investor criticisms of listed real estate is that over the
short term, real estate stocks behave like other equities and display the same
high degree of volatility associated with equity investing, while direct property
markets and stock markets move independently of each other. Under this simple
assumption, the direct sector is viewed as a securities portfolio diversifier, while
listed real estate is not.
We argue that the characteristics of listed real estate companies should allow investors
to earn the performance of a direct property portfolio through owning a basket of their
shares over the long term. Moreover, investors should also not overlook the underlying
real estate exposure that REITs and REOCs3 provide in terms of diversification through
the ownership of portfolios of multiple properties rather than investments in single
properties. Listed real estate companies own, service and manage properties and
collect rents and their capital expenditure, finance and development costs are similar
to those of privately-owned (unlisted) real estate companies. Thus, our research sets
out to explore whether direct real estate and listed real estate return correlations
vary when measured over varying holding periods and also whether over longer-term
holding periods, listed real estate does actually still behave like other equities.
"The analysis was expanded
in Q1 2016 and reinforces the
findings of our initial study"
Listed real estate offers opportunities for active management which cannot typically
be exploited in direct real estate holdings. From a broader investment management
perspective, portfolio managers can recognise the potential to generate additional
uncorrelated alpha by exploiting inefficiencies in the asset class both at the bottomup and the top-down level. We investigated the extent to which inefficiencies exist
in the listed real estate market for bottom-up investing, which the stock selection
process can exploit.
In view of the sensitivity of real estate investments to changes in interest rates and
given the current market concerns that interest rates will eventually rise, our study
also examines the sensitivity of listed real estate to such changes. In addition, it looks
into the effectiveness of property equities as an inflation hedge over the longer term.
About our research
Our study considers several listed real estate indices which cover property markets in
the main regions of the world, offering different levels of exposure and liquidity. The
FTSE EPRA/NAREIT range, with its regional sub-indices, includes highly liquid indices
widely used by listed real estate managers. They cover the most relevant real estate
markets and include indices for global, US, Europe, UK, Asia and Australia listed real
estate. We used a longer history of index returns provided by FTSE EPRA/NAREIT and
detailed information on the composition of the indices in terms of constituents and
their market capitalisation. We believe the results are in both cases representative of
the listed real estate asset class as a whole.
LISTED REAL ESTATE AS A GLOBAL ASSET CLASS
Is listed real estate a proxy for direct real estate?
This section of the paper looks at whether and how effectively public real estate
equities can act as a substitute for owning direct property. Investors continue to
debate the respective benefits of owning REITs versus private market real estate.
Critics like MacKinnon (2010) argue that REITs and private real estate are not
perfect proxies for one another although they do acknowledge that they have some
similarities. And indeed the PREA4 research acknowledged that from a risk return
perspective, both forms of real estate have a role to play within a mixed-asset
portfolio. Indeed, research from Ang, Nabar, and Wald (2013) found that REITs
and private real estate investments had different components over the short- and
medium-term but over the full real estate cycle, the differences largely disappear,
and both public and private vehicles exhibit similar characteristics.
Investors looking to add real estate to their portfolios may find it difficult to invest
in direct real estate because of the low liquidity of the market, the high capital
requirements to build sufficiently diversified portfolios, the high transaction costs
and the need for skilled professionals to manage the property and all other costs
and taxes associated with property management.
Listed real estate offers a well sought-after alternative to direct real estate which
manages to avoid these shortcomings. Oikarinen and Hoesli (2012) and Crowe and
Krisbergh (2010) show that listed real estate delivers performances comparable
to those from investing in direct real estate portfolios. Indeed, the returns of listed
real estate companies are derived from investments in direct real estate and
thus from direct real estate returns. Oikarinen, Hoesli and Serrano (2013) arrive
at a similar conclusion for different segments of the real estate market in the
US. Listed real estate plays an important role in particular for smaller investors
by allowing them to access segments of the market which require more capital.
Listed real estate also allows for a quicker access to the market avoiding the long
time required for any direct real estate transaction. But even larger investors will
find it useful to use listed real estate when building portfolios in order to better
manage the exposure to different segments of the market and efficiently exploit
different stages of the property cycle.
4 PREA: Pension Real Estate Association MacKinnon G.
Nevertheless, in the short-term, correlations between direct and listed real estate
are low. This can probably be explained in great part by the rather different levels
of liquidity of these two forms of real estate investment. Listed real estate is
simply valued by the market on a real-time basis much like the other segments of
the equity market. Listed real estate offers daily liquidity and is thus, perhaps not
surprisingly, also immediately impacted by some of the same factors that impact
equity market returns and related to investor demand for risky assets and to the
macro-economic cycle. These factors are not as well captured by direct real estate
prices, not necessarily because they do not have an impact but more likely because
of the very low frequency of trades and price observations. Direct real estate has a
different basis of valuation with non-listed funds and direct property valued on a
much less frequent, annual, quarterly or monthly basis. The low volatility of direct
real estate returns and low short-term correlation with risk asset returns are
likely to be explained by the low frequency of price observation. Unlike listed real
estate price discovery is thin, largely appraisal based and transaction evidence is
scarce.
Oikarinen and Hoeslis’ (2012) research into the strength of the relationship
between listed and direct real estate returns in the US, Australia and UK suggests
that, despite the shorter-term differences, the returns from listed and direct real
estate are indeed comparable over the long-term. Their research supports a strong
relationship between direct real estate returns measured from NCREIF5 and IPD6
total return indices and listed real estate returns measured from NAREIT7 total
return indices. This comparison of NCREIF and NAREIT indices strongly support the
hypothesis that the same underlying fundamental characteristics of direct real
estate drive both listed and unlisted returns over the long term. This academic
evidence supports the case for holding listed real estate as an alternative to direct
real estate in the long-term.
How important are dividends to return performance?
"Over the long run,
the contribution to total
returns from reinvested
dividends is clearly stronger
for listed real estate than for
the broader equity market"
The specific structure of the underlying companies of most securities in listed
real estate such as the REITs makes them more likely to pay dividends than other
stocks. To keep profiting from their specific taxation framework, the unique rules
that apply to REITs push them to distribute almost all their income to shareholders.
In fact, in the US for example, REITs must satisfy the profit and dividend distribution
requirements of Code Section 857(a) recommending the payment of at least 90% of
their earnings in the form of dividends. Similar conditions are put into practice in
the UK, Europe and Asia with exigencies ranging from 70 to 90% of the income to be
distributed to shareholders through dividends. With real estate companies meeting
the requirements, they benefit from a lighter taxation regime. Consequently, real
estate stocks provide higher yield than other equities and have seen their total
returns and outperformance historically coming from dividends. When compared
with other stocks, many investment managers seeking income and long-term
capital appreciation find listed real estate an appropriate choice.
In exhibit 1 we show the decomposition of annualised average returns into price
returns and reinvested dividends for listed real estate stocks in different regions
using the FTSE EPRA NAREIT indices. We show the same for the equity markets in
the same regions using the MSCI indices. Five different regions were considered: US,
UK, Eurozone, Asia and developed countries. Over the period 1990 to 2015 nearly
half of the returns of real estate stocks came from dividends, the exception being
Asia where reinvested dividends contributed less to returns. Over the long-run, the
contribution to total returns from reinvested dividends is clearly stronger for listed
real estate than for the broader equity market in all regions. In the period, dividend
yields for US listed real estate have averaged approximately 500bps compared to
just 200bps for the MSCI US. For global real estate, the dividends average 400bps
compared to just 200bps for the MSCI World Index. The pattern is similar for other
regions, including Asia.
5 NCREIF: National Council of Real Estate
Investment Fiduciaries. The NCREIF Property
Index tracks the performance of unlisted real
estate market in the US.
6 IPD is a subsidiary of MSCI Inc. The IPD indices
track investment returns of the property
markets around the world.
7 NAREIT: National Association of Real Estate
Investment Trusts. The FTSE EPRA/NAREIT Index
tracks the performance of global and regional
listed real estate.
Exhibit 1: Decomposition of total annualised average returns into price returns
and reinvested dividends for five regions: US, UK, Eurozone, Asia and developed
countries. A) shows the decomposition of returns for listed real estate in these
regions based on the FTSE EPRA/NAREIT indices. B) shows the same for the broader
equity market in each region and is based on MSCI regional equity indices. Averages
are based on annual data in local currencies from January 1990 to December 2015.
Data source: FTSE EPRA/NAREIT, MSCI and FactSet.
A) Annualised returns (in local currencies) for listed real estate, January 1990
to December 2015
16%
14%
Reinvested dividend
5%
Price return
12%
10%
8%
4%
5%
3%
4%
Asia Pacific
Developed
6%
4%
2%
0%
US
UK
Eurozone
B)Annualised returns (in local currencies) for equities, January 1990 to
December 2015
16%
Reinvested Dividend
14%
Price return
12%
10%
2%
8%
4%
3%
2%
6%
4%
2%
2%
0%
US
UK
Eurozone
Asia Pacific
Developed
How liquid is listed real estate compared to direct property?
Crowe and Krisbergh (2010) explain that given the cost of buying and selling
properties and the limited liquidity of direct real estate this should be only used as
a long-term investment. Anyone who has bought and sold a home, particularly in
challenging market circumstances, is familiar with how illiquid direct property can
be. Commercial private real estate portfolios tend to be long-term, buy-and-hold
investments given the transaction times and costs involved, as portfolio managers
will be constrained by the lack of liquidity. Liquidity is vital when markets suffer
shocks as investors scramble to adjust their allocations to real estate to adapt to
the market conditions. While it is easy to change sector or regional weights in a
few days in a listed global real estate portfolio, it can take months or years in the
case of a direct property portfolio.
The difference in liquidity between listed real estate and direct real estate can
be illustrated by looking at how long it would take to dispose of a hypothetical
EUR 1 billion direct property portfolio compared with the liquidation of a similar
sized global listed real estate portfolio. Jones Lang LaSalle Inc. (JLL), a professional
services and investment management company specialising in real estate, provided
the data required for this exercise.
In exhibit 2, we first considered the time it would take to sell a global direct real
estate portfolio of EUR 1 billion of prime modern properties comprising 35% office,
35% modern shopping centers, 10% residential, 10% industrial & hotels, and 10%
others. All the properties are categorised as class-A8, and located in major global
or mega cities, with a regional split of 45% in North America, 40% in Asia Pacific
and 15% in Europe. Then, we considered the time to sell a global listed portfolio
of EUR 1 billion composed of the FTSE EPRA/NAREIT global developed index stocks
at market capitalisation. Current market conditions are determined by the recent
traded volume for each stock. The selling rule allows for selling a maximum of
25% of the recent average volume of each stock every day. We used the average
volume estimated over the previous 20 working days and the average monthly
volume estimated over the last five months. These two average volume figures are
comparable and the results are the same whether we use one or another.
"Listed real estate clearly
offers much larger liquidity
than unlisted real estate,
although there are major
regional variations"
The direct real estate portfolio would be separated into three regional sub-portfolios
and the estimated liquidation period would be six to eight weeks in optimal market
circumstances, around five months in the current market conditions (March 2016)
and as long as eight months in less favorable market conditions (November 2008).
Our analysis suggests it would take just two days to sell 90% of the listed real
estate portfolio and 10 days to dispose of it completely.
Exhibit 2: Average number of days to liquidate 50%, 90% and 100% of a EUR 1billion
global portfolio of listed and direct real estate in similar market conditions as
from October 2015 to March 2016, local currency, monthly data.
Data source: Jones Lang LaSalle Inc. and FactSet.
Listed real estate
Direct real estate
% of portfolio
liquidated
50
90
100
fastest
average
slowest
Time
required for
transaction
1 day
2 days
10 days
7 weeks
5 months
> 1 year
Listed real estate clearly offers much larger liquidity than unlisted real estate,
although there are major regional variations, with listed real estate in Europe
being less liquid than in North America or Asia.
We performed the same exercise using the North-American, Asian and European
regional FTSE EPRA/NAREIT indices and the same assumptions. The results can be
found in exhibit 3 and exhibit 4 showing that selling a EUR 1 billion portfolio in
North-America would take approximately the same amount of time as for the global
portfolio, which is around 10 days. For Asia, the figures are similar with 12 days
needed to dispose completely of a portfolio invested in listed real estate. On the
other side, a European portfolio could take slightly more than 40 days to be entirely
8 Class-A buildings represent the highest quality
buildings in their real estate sub-sector
compared to class B and C.
sold. In all cases, whatever the region considered, listed real estate markets show
a much more attractive liquidity than direct real estate markets. Listed real estate
offers an effective way to manage exposure to properties in a portfolio by avoiding
the risk of illiquidity, especially during the 2008 crisis when the direct real estate
market was particularly illiquid.
Exhibit 3: Average number of days to liquidate listed real estate EUR 1 billion portfolios
invested according to the capitalisation weighted allocation in the FTSE EPRA/NAREIT
indices. The graph shows the percentage of the portfolio remaining a number of days
after the selling started and allowing for selling just 25% of the average monthly
volume in the previous five months for each stock. Data source: FTSE EPRA/NAREIT
and FactSet, March 2016.
Liquidation of EUR 1 billion listed real estate portfolios
100%
80%
Global
60%
North America
Europe
Asia
40%
20%
0%
0
5
10
15
Number of days
-20%
Exhibit 4: Average number of days required to liquidate completely a EUR 1 billion
portfolio invested according to different capitalisation weighted FTSE EPRA/NAREIT
indices. Data source: FTSE EPRA/NAREIT and FactSet, March 2016.
Average number of days
Global
Europe
North America
Asia
10
40
6
12
Are listed real estate returns correlated with direct real estate and
other asset classes?
9 IPD is a subsidiary of MSCI Inc. The IPD indices
track investment returns of the property
markets around the world. PREA: Pension Real
Estate Association - MacKinnon G.
In exhibits 5, 6 and 7 we show the correlations between the returns of listed
real estate and the returns of direct real estate, equities and treasuries for the
US and UK respectively and between the returns of listed real estate and the
returns of global equities and global treasuries. For listed real estate we used
the FTSE EPRA/NAREIT for the US, the UK and Global. For direct real estate we
used the NCREIF Property Index for the US and the IPD9 Index for the UK. For
equities we used the S&P500 for the US, the FTSE100 for the UK and the MSCI
ACWI for the Global. For treasuries we used the US 10 Year Treasury Note Index,
the Citigroup UK GBI 7-10 Year Index and the Citigroup World GBI 7-10 Year
Index.
The correlations of returns plotted in exhibit 5, exhibit 6 and exhibit 7 were estimated
using different data frequencies over the entire period. In exhibit 5, 6 and 7 the
returns to the asset classes were calculated using quarterly data from January 1994
to December 2015. The first point in each figure is the correlation of returns of the
two series at the highest frequency available. The subsequent points in each figure
are average correlations calculated from data at lower frequency using all possible
starting points. The lowest frequency used is 20 quarters.
For the US, our analysis confirms that, while direct real estate and listed real estate
appear to have lower correlations with higher frequency returns, this correlation
increases for lower frequency returns, i.e. at longer-term horizons. We find similar
results for the UK although convergence is slower.
The correlation between listed real estate returns and equity returns does tend to
be high at higher frequencies and drops as the frequency decreases, i.e. longer-term
horizons. At lower frequencies, the correlations between listed real estate returns
and equity returns are low for the US and UK. The results are very compelling:
in the shorter-term, listed real estate tends to behave more like equity markets.
However, at longer-term horizons, listed real estate market is more correlated
with direct real estate. For global real estate the correlation tends to remain high
irrespectively of the horizon.
"Listed real estate is over
longer-term horizons, clearly
a diversifier of equities while
offering an increasing exposure
to direct real estate"
The returns to bonds are highly interest rate sensitive, as it should be part of the
return from listed real estate securities. Nevertheless, it is natural to expect that
listed real estate should also be sensitive to what happens in the direct real estate
markets. The fact is that the correlation between listed real estate and treasury
returns is low, even negative, in the US, UK and at global level, and does not change
even when data frequency is decreased. As exhibit 5, exhibit 6 and exhibit 7 show,
the correlation rarely raises above 10%.
Listed real estate is thus expected to have a diversifying role in multi-asset
portfolios. Its low correlation with fixed income makes it a natural diversifier of
bonds and, at least over longer-term horizons, it is also clearly a diversifier of
equities while offering an increasing exposure to direct real estate.
Exhibit 5: Correlations between the US listed real estate total returns and the
returns to other US asset classes over different investment horizons (different return
frequencies) from January 1994 to December 2015, based on USD quarterly returns.
Data source: FTSE EPRA/NAREIT, S&P, Citigroup and FactSet.
US asset class correlations
100%
80%
60%
40%
20%
0%
-20%
-40%
Listed real estate vs. direct real estate
Listed real estate vs. equities
Listed real estate vs. bonds
-60%
-80%
0
12
24
Months
36
48
60
Exhibit 6: Correlations between UK listed real estate total returns and the returns
to other UK asset classes over different investment horizons (different return
frequencies) from January 1994 to December 2015, based on GBP quarterly returns.
Data source: FTSE EPRA/NAREIT, FTSE, Citigroup and FactSet.
UK asset class correlations
100%
80%
60%
40%
20%
0%
-20%
-40%
-60%
-80%
0
Listed real estate vs. direct real estate
12
24
Months
36
48
60
Exhibit 7: Correlations between the global listed real estate total returns and the
returns to other global asset classes over different investment horizons (different
return frequencies) from January 1994 to December 2015, based on USD quarterly
returns. Data source: FTSE EPRA/NAREIT, MSCI, Citigroup and FactSet.
Global asset class correlations
100%
80%
60%
40%
20%
0%
-20%
-40%
0
12
24
Months
36
48
60
How diversified is global listed real estate?
Direct real estate is a heterogeneous asset class with exposures to a diversity of
segments, sectors and regions that drive its performance and that of listed real
estate companies. The type of assets that companies own, the economic sectors
they are exposed to, lease lengths in their portfolio as well as their market and
sub-market locations all have differentiating impacts on portfolio and company
performance. Some REITs tend to follow more secular trends while others are
cyclical in nature. As a result of this diversity in property holdings and regional
exposures, we can see substantial variations in performance that investors can
exploit over varying time frames.
Exhibit 8: Properties owned by listed real estate companies in the
FTSE EPRA/NAREIT Developed Index as of 30 September 2015. Data source: SNL
Financial and FTSE EPRA/NAREIT.
Number of properties owned by companies in the FTSE EPRA/NAREIT Developed Index
Australia
Austria
978
340
Belgium
1,368
Canada
3,916
China
524
Finland
977
France
1,955
Germany
3,094
Hong Kong
Italy
Japan
797
217
2,700
Netherlands
936
Norway
224
Singapore
338
Sweden
Switzerland
United Kingdom
"Listed real estate companies
in the developed markets
own a total of almost 125,000
properties"
3,453
562
2,489
USA
99,945
Total
124,813
Clearly the greatest benefit from owning large and diverse portfolios of assets can
be seen in the underlying exposures provided by the FTSE EPRA/NAREIT Global
Index. The index provides exposure to thousands of buildings worldwide from a
portfolio of global property equities and can allow investors to minimize the risk
of reliance on the performance of one property, while potentially maximizing the
returns through a multi-asset portfolio. As this shows, listed real estate companies
in the developed markets own a total of almost 125,000 properties.
Indeed, if investors are still shy of investing in listed real estate they may be
underestimating the diversification benefits that this asset class can bring to a
multi-asset portfolio.
THE STRATEGIC ROLE OF LISTED REAL ESTATE
IN MULTI-ASSET PORTFOLIOS
The evidence in the previous section supports the thesis that listed real estate
can adequately substitute for direct real estate in investors’ portfolios. We next
consider whether listed real estate can improve the risk and return characteristics
of a multi-asset portfolio.
In line with modern portfolio theory, investors should minimize risk for a
given level of expected return or maximize returns for a given level of risk.
Diversification is effective in minimizing overall risk as correlated asset classes
are poor diversifiers. Mean-variance optimization is, however, known to suffer
from assuming that future returns, volatilities and correlations can be predicted
with no estimation error, which is never the case. Extreme portfolio allocations
with the portfolio concentrated in just a few assets are often found from meanvariance optimization when correlated assets are considered. This is a sign that
something is wrong with the forecasts used as inputs in the mean-variance
optimizer and with the assumption that our returns and variance-covariance
forecasts are known exactly.
Robust optimization10 techniques recognize the added value of correlated assets
by taking into account that neither future returns, nor volatilities nor correlations
are known exactly in ex-ante. These robust techniques show that correlated
assets offer diversification against the uncertainty of future outcomes and thus
are still useful in a portfolio even if their impact on ex-ante risk may be negligible.
10Robust optimization is a field of optimization
theory that deals with optimization problems in
which certain measure of robustness is sought
against uncertainty that can be represented
as deterministic variability in the value of the
parameters of the problem itself and/or its
solution.
11A bootstrap is a computer-intensive method of
estimation of parameters and distributions by
resampling the original data.
Bootstrapping11 optimization is a one of the simplest forms of robust optimization
that takes into account the estimation error in return and variance-covariance
forecasts. This technique is based on running multiple mean-variance
optimizations for different return and variance-covariance scenarios. Each
scenario is built from a sub-period of the entire history of returns considered.
The final portfolio is simply the average of the portfolios obtained from the
mean-variance optimization for each scenario with the average returns and the
variance-covariance matrix estimated over the sub-period considered. Here we
considered 10,000 five-year sub-periods sampled from the history of monthly
returns considered: January 1990 to December 2015. In each mean-variance
optimization we looked for the portfolio allocation that maximized the Sharpe
ratio under the constraints specified below. Since the volatility is not constrained
in the optimization, the maximum Sharpe ratio portfolios may not have the same
volatility. For a more comprehensive discussion of this optimization technique we
recommend the book by Scherer (2004).
We used bootstrapping optimization to find the optimal portfolio allocation which
maximizes the Sharpe ratio of multi-asset portfolios for different investment
universes, (global, US, EMU and UK) to integrate several client strategic objectives.
We considered the impact of allowing for the portfolio to also invest in listed real
estate. The other asset classes considered on a regular basis by investors are
equities, bonds and commodities. Monthly returns in local currencies where used.
• Equities: • Bonds: MSCI regional indices
Government bonds < 10-year maturity
Corporate investment-grade bonds
• Commodities: S&P GSCI Index
• Listed real estate: FTSE EPRA/NAREIT regional indices
When using bootstrapping optimization, the portfolio is not subject to severe
constraints. This is because bootstrapping optimization does not suffer from the
drawbacks of mean-variance. As a result the portfolio is not subject to constraints
that could be considered to be restrictive.
The optimal portfolios are shown in exhibit 9. For each region we show two
portfolios, one excluding listed real estate and one including. We find that the
optimizer allocates a significant weight to listed real estate in the maximum
Sharpe ratio portfolio when this asset class is allowed. In the US and EMU, the
optimal listed real estate allocation comes close to 15%, and in the EMU close to
12% whereas in the UK is smaller, at 5%. In the portfolio invested in global assets
the weight is close to 9%. The improvement in the Sharpe ratio of the portfolio is
significant: +13% for the World and +20% for the US, for EMU and for the UK. The
volatility of the portfolio investing in listed real estate is similar to the volatility of
the portfolio where listed real estate is excluded, even if this latter is unconstrained
in the optimization.
"Including listed real estate
in an allocation has the
impressive benefit of improving
returns drastically without
increasing the volatility"
Bootstrapping optimization shows that listed real estate plays an important role
in multi-asset portfolios and can bring important diversification benefits over fiveyear periods. Including listed real estate in an allocation has the impressive benefit
of improving returns drastically without increasing the volatility for all three
regions. Listed real estate would have provided a significant diversification effect in
multi-asset portfolios general stocks, bonds, and commodities in these key regions
between 1990 and 2015 (1997 and 2015 for the UK). The results strongly suggest
that local and global investors can increase portfolio diversification and achieve
superior returns by adding listed real estate to their multi-assets portfolios. The
demonstration described here is based on several assets classes that we have
defined. However, it is designed to adapt to other detailed investment universes
that could and should be carried out hand-in-hand with clients.
Our results are in line with older research from Lee and Stevenson (2005) and Lee
(2012) who found evidence that including REITs in a multi-asset portfolios provides
not only diversification benefits but also improves the returns and allocate a
significant weight to listed real estate.
Exhibit 9: Maximum Sharpe ratio portfolio allocation for US, UK, EMU and
World portfolios with and without listed real estate derived from bootstrapping
optimization. Monthly returns in local currencies. From January 1990 to December
2015 for US, EMU and World, and January 1997 to December 2015 for UK. Data
source: FTSE EPRA/NAREIT, MSCI, S&P and FactSet.
Maximum Sharpe
ratio portfolios
Global
Listed real estate
Equities
Bonds
Corporates
Commodities
Listed real estate
MSCI World
Citigroup US GBI 10Y+
Merril Lynch Global Broad Market Corp Index
S&P GSCI Commodity Index
FTSE EPRA/NAREIT Developed
Annualised excess return (USD)
Volatility of returns (USD)
Sharpe ratio
excluded
included
19.0%
31.8%
42.7%
6.4%
0.0%
15.3%
28.2%
43.5%
4.4%
8.6%
4.9%
5.8%
0.89
5.7%
5.9%
1.01
US
Equities
Bonds
Corporates
Commodities
Listed real estate
Listed real estate
MSCI USA
Citigroup US GBI 10Y+
Merril Lynch US Corp Index
FTSE EPRA/NAREIT USA
Annualised excess return (USD)
Volatility of returns (USD)
Sharpe ratio
excluded
22.9%
27.3%
42.1%
7.7%
0.0%
included
16.6%
23.5%
40.1%
5.0%
14.7%
6.0%
6.5%
0.96
7.2%
6.5%
1.15
Eurozone
Equities
Bonds
Corporates
Commodities
Listed real estate
Listed real estate
MSCI EMU
Citigroup EMU GBI 10-15 Year
Merril Lynch EMU Corp Index
FTSE EPRA/NAREIT Eurozone
Annualised excess return (EUR)
Volatility of returns (EUR)
Sharpe ratio
excluded
10.9%
43.5%
40.5%
5.0%
0.0%
included
5.4%
37.6%
41.5%
3.6%
11.9%
5.1%
5.2%
0.92
5.6%
5.0%
1.11
UK
Equities
Bonds
Corporates
Commodities
Listed real estate
Listed real estate
MSCI UK
Citigroup UK GBI 10-15 Year
Merril Lynch Sterling Corporate Index
FTSE EPRA/NAREIT UK
Annualised excess return (GBP)
Volatility of returns (GBP)
Sharpe ratio
excluded
11.7%
40.5%
40.8%
7.0%
0.0%
2.9%
4.8%
0.62
included
8.3%
45.8%
36.8%
3.9%
5.2%
3.2%
4.5%
0.75
LISTED REAL ESTATE
AND MACROECONOMIC RISK
How sensitive is listed real estate to interest rates?
Since the outbreak of the Great Financial Crisis in 2007-2008, we have witnessed
an unprecedented amount of intervention in the capital markets by global
central banks, which has had a profound impact on interest rates in North
America, Asia and Europe. In view of the current background of ongoing interest
rate uncertainty, we considered it highly relevant to examine the performance
of listed real estate under different scenarios for movements in short-term and
long term interest rates.
One should be forgiven for expecting listed real estate to suffer in periods of
interest rate raises. After all, as seen before, listed real estate companies pay
higher dividends and tend to be relatively high-yielding investments. Moreover,
these companies tend to use leverage. A negative sensitivity to raising interest
rates should perhaps be expected. Indeed, when the US Federal Reserve
suggested it would reduce quantitative easing in May 2013, this was followed by
a major sell off in US REITs and in listed real estate globally. But investors need
to think beyond simply how listed real estate performs in the very short term.
Rising rental rates and property prices in an improving economic environment
can more than compensate for rises in interest rates over the longer run (see
exhibits 10 and 11 on page 18). Direct and listed real estate also respond at
different speeds to the threat of long and short-term interest rate increases.
When short-term rates rise, it tends to have little impact on property cap rates
because it generally signals that the economy is improving.
When interest rates move, the government yield curve either steepens or
flattens. In exhibit 10 we show how the US yield curve moved in the past. Gray
background periods represent steepening periods whereas white background
represents flattening periods. The yield curve is measured by the difference
between 10 year yields and three month cash rates.
Exhibit 10: US yield curve based in 10 year bond yields minus three months cash rates
for the US, from January 1989 to December 2015. Steepening periods are represented
with green background and flattening periods in white. Data source: FactSet.
12
Steepening periods
US Benchmark bond - 10 year - yield
US 10 year - US 3 month
10
8
Flattening periods
US Benchmark bond - 3 month - yield
6
4
2
0
Nov.-2014
Nov.-2013
Nov.-2012
Nov.-2011
Nov.-2010
Nov.-2009
Nov.-2008
Nov.-2007
Nov.-2006
Nov.-2005
Nov.-2004
Nov.-2003
Nov.-2002
Nov.-2001
Nov.-2000
Nov.-1999
Nov.-1998
Nov.-1997
Nov.-1996
Nov.-1995
Nov.-1994
Nov.-1993
Nov.-1992
Nov.-1991
Nov.-1990
Nov.-1989
-2
These movements in rates occur as the economy and policy environment evolve
leading to changes in interest rates as investors trade (often large) blocks of
fixed income securities. Flattening and steepening can actually be divided into
bear and bull periods giving rise to four different types of yield curve movements:
• Bear Flattening: short-term interest rates are rising faster than long-term
interest rates
• Bull Flattening: long-term rates fall faster than short-term rates do, causing
the yield curve to flatten as the short-term and longterm rates converge
• Bear Steepening: steepening of the yield curve is caused by long-term rates
rising faster than short-term rates
• Bull Steepening: short-term rates fall faster than long-term rates do, causing
the yield curve to steepen
Exhibit 11: Average annualised total returns and volatility of listed real estate and
developed equities conditioned to yield curve regimes. Monthly total returns in USD
for the period January 1990 to December 2015. Source: FTSE EPRA/NAREIT, MSCI and
Datastream.
Annualized returns (1990-2015)
FTSE EPRA/NAREIT
MSCI World
Global
(EUR)
Americas
(USD)
Asia
(EUR)
Europe
(EUR)
(EUR)*
(USD)
Bear flattening
25.8%
26.2%
23.5%
22.4%
18.9%
12.8%
Bear steepening
16.4%
10.7%
17.1%
17.2%
18.5%
17.1%
Bull flattening
14.2%
18.8%
10.7%
13.0%
-6.4%
8.2%
Bull steepening
-5.7%
8.4%
-3.6%
-5.1%
-4.8%
-0.8%
* Since 1998
Volatility of returns
FTSE EPRA/NAREIT
Bear flattening
Global
(EUR)
Americas
(USD)
12.8%
14.1%
Asia
(EUR)
18.2%
MSCI World
Europe
(EUR)
(EUR)*
11.6%
11.1%
(USD)
10.5%
Bear steepening
16.3%
13.4%
21.7%
13.7%
10.0%
10.6%
Bull flattening
16.6%
15.9%
28.1%
14.3%
17.5%
16.2%
Bull steepening
21.0%
27.6%
24.3%
17.3%
17.0%
18.3%
* Since 1998
In exhibit 11 we show the average returns of the FTSE EPRA/NAREIT indices of
different regions and compare them to the average returns of the MSCI World
Index conditioned to these four movements of the US yield curve. The analysis
covers the period 1990 to 2015. Periods of bull steepening were difficult not only
for the listed real estate (exception for Asia Pacific) but also for global equities.
Periods of bear steepening were more favorable to equities but listed real estate
also delivered generous returns (although less in North America).
Rising short-term US interest rates tend to be positive for global listed real
estate, which in turn largely outperformed global equities during periods of bear
flattening. Seeing real estate out-performing equities in bear flattening periods
rather than bear steepening may be due to real estate firms financing themselves
with long rather than short rates. Our objective was to illustrate different scenarios
and evaluate the impacts for listed real estate with some assumptions and some
limits identified due to the existing market environment (the lowest yield curve
generating abundant liquidity for 25 years or a longer economic cycle).
Can listed real estate hedge against inflation?
We shall now explore if listed real estate has been effective as a hedge against
inflation in the past over the long term. Glascock et al. (2002) discussed the ability
of direct real estate to protect investors from loss of purchasing power. Since
listed real estate is exposed to direct real estate, investing in real estate through
ownership of publicly traded stocks presents a good hedge against inflation, if the
effect of changes in monetary policies is put aside. In fact, the hedging effectiveness
of listed real estate seems much closer to those of direct real estate than global
equities. The main driver of this hedge is the income component of listed real estate
returns that adjusts with inflation over the long-term. This could also be expected
given the long-term correlation of listed real estate returns with direct real estate
returns, which is much stronger than with equity returns as discussed earlier.
"The hedging effectiveness
of listed real estate seems
much closer to those of
direct real estate than
global equities"
In order to show the effectiveness of the hedge against inflation in the longer-term
we chose to show to what extent the performance of listed real estate exceeds
price inflation in a given period. We also compare the effectiveness of listed real
estate with that of other asset classes using the same approach. We look at the
effectiveness over different investment horizons: 1 year, 3 years, 5 years and 10
years and we include overlapping periods in the simulations. The success rate is
defined by the probability that the average returns exceeded the average inflation
rate over the investment horizon considered.
We used a historical sample from 199112 to 2015 based on quarterly data. In
exhibit 12 we show the results. We used:
• Equities: • Bonds: • Commodities: • Listed real estate: • Direct real estate: • Inflation: S&P500 (US)
STOXX600 (Europe)
FTSE100 (UK)
ASX200 (Australia)
TOPIX100 (Japan)
Citigroup Government bond 7-10 years indices
S&P GSCI Index
FTSE EPRA/NAREIT developed indices
IPD Direct Property local indices
CPI Index
12European bond quarterly data are available
from 1994, and European direct real estate from
2000 on a yearly basis. We did not consider
direct real estate data for Japan and Australia
due to licensing issues.
Exhibit 12: Probability of out-performing inflation for different countries and at different
(overlapping) horizons. Quarterly (yearly for EMU direct real estate) data based on
local currency returns from 1991 (1994 for European bonds and 2000 for European
direct real estate) to 2015. The highest probabilities are displayed with bold figures.
Data source: FTSE EPRA/NAREIT, IPD, S&P and FactSet, March 2016.
Probability of outperforming inflation
Holding period
Listed
real estate
Equities
Bonds Commodities
Direct
real estate
1 year
US
EMU
UK
Australia
Japan
79%
81%
64%
75%
53%
72%
68%
66%
61%
48%
78%
61%
78%
78%
85%
50%
52%
49%
50%
54%
82%
93%
82%
3 years
US
EMU
UK
Australia
Japan
77%
80%
76%
78%
57%
63%
60%
62%
64%
47%
92%
78%
98%
99%
98%
55%
58%
53%
52%
60%
77%
75%
82%
5 years
US
EMU
UK
Australia
Japan
78%
76%
71%
70%
56%
54%
41%
52%
65%
35%
99%
80%
99%
100%
100%
50%
49%
52%
54%
61%
90%
100%
74%
10 years
US
EMU
UK
Australia
Japan
94%
100%
89%
58%
83%
67%
51%
63%
73%
33%
98%
69%
98%
100%
100%
69%
67%
72%
73%
88%
94%
100%
94%
Listed real estate reached better results than other asset classes, with the exception of
bonds, coming out on top in terms of hedging power for several regions and periods.
European and Australian listed real estate exhibit the highest success rates among other
assets over the four periods considered with probability of beating inflation between 75%
and 100%. For the US, listed real estate provided very similar hedge against inflation
to that offered by direct real estate for all holding periods with a probability of beating
inflation higher than 75%. For the UK, even if listed real estate inflation protection is
a rising function of the holding period, UK direct real estate appears to have the best
results in terms of inflation hedging compared to other assets. On the other hand, Japan
showed quite low inflation hedging success rates at around 55% for all periods, except
for 10-year holding period where probability of beating inflation is higher. Commodities
had a success rate reaching 88% for the 10-year period.
Even though results are a function of the economy and underlying market of the country
considered, listed real estate presents similar or better inflation hedging properties
when compared to other asset classes when this measure of success is taken into
account. For the EMU, we find that direct real estate had been a better hedge of inflation
than bonds in the 1, 5 and 10-year period considered.
THE ACTIVE MANAGEMENT OPPORTUNITIES
FROM INEFFICIENCIES IN LISTED REAL ESTATE
The very diverse nature of listed real estate markets in terms of geography and
sector suggests that investors should be able to exploit the significant differences
that mark the listed real estate investment universe in terms of region, country,
sector and segmental characteristics as well as individual diversity at the stock
level. Depending on the depth and extent of this differentiation, managers with
specialised expertise in the real estate sector should be well placed to consistently
generate excess returns.
The existence of top down and bottom up divergence means that managers can
generate alpha by actively managing listed real estate portfolios to exploit these
inefficiencies. This alpha is an excess return uncorrelated with the returns of the
listed real estate market and with the returns of other asset classes. Alpha is thus
highly valuable for portfolio diversification and for increasing the long-term riskadjusted returns of the overall multi-asset portfolio.
How diverse is the listed real estate sector?
Global listed real estate is the one of the few sectors that offers such a diverse
exposure to various countries and subsectors. In fact, a portfolio invested in global
real estate may represent several different property types in multiple countries.
As reflected in exhibit 13 the FTSE EPRA/NAREIT is exposed to more than 10
property sectors and no less than 13 countries.
Listed real estate offers exposure to properties that would have never been
considered by many investors such as hotels, malls and self-storage for example.
Small investors would never be able to buy such properties. But even large
investors can access better diversified portfolios via listed real estate than
through direct real estate. Specialised REITs also bring the adequate competence
to manage such type of properties, something difficult for most investors. Listed
real estate is diverse in terms of geography and sector offering opportunities for
active management in different market segments.
Exhibit 13: Listed real estate exposure through FTSE EPRA/NAREIT to property
A) sub-sectors and B) countries on 31 August 2015.
Data source: FactSet and FTSE EPRA/NAREIT.
A) Sector allocation in the FTSE EPRA/NAREIT on 31 August 2015
60%
50%
40%
30%
27.0%
24.9%
20%
13.1%
12.0%
10%
7.4%
5.5%
4.2%
Healthcare
Industrial
Hotel
& Resort
6.0%
0%
Diversified
Retail
Residential
Office
Other
B) Country allocation in the FTSE EPRA/NAREIT on 31 August 2015
60%
52.7%
50%
40%
3.1%
2.8%
2.6%
2.4%
1.6%
1.1%
0.9%
0.5%
1.5%
Sweden
Switzerland
Belgium/
Luxembourg
Other
5.7%
France
6.7%
Singapore
7.1%
Netherlands
11.5%
10%
Canada
20%
Germany
30%
Australia
Hong Kong
UK
Japan
United States
0%
Where are the potential top-down inefficiencies?
In exhibit 14 we show the correlations between the returns of different listed real
estate sector and country FTSE EPRA/NAREIT indices. The average of all correlations
for all sectors is about 77% and for all major countries about 37% in the 25-year
period considered. Lower average country return correlations make it easier to
generate tracking error by actively investing in some countries in favour of others
with relatively small active weights, when compared to investing in some sectors
instead of others.
A number of inefficiencies exist in the listed real estate market at country level.
We show that a number of macroeconomic and property specific factors have
predictive power for the cross section of listed real estate country returns and can
be used to generate alpha:
• Macro factors: Short-term rates
Policy rates
Inflation
Consumer confidence
Retail sales
• Property factors Office market yields
Office market vacancies
As shown in exhibit 15 for the period 1992 to 2015, macroeconomic factors have
been good predictors of cross-sectional country returns in the global listed real
estate with information ratios as high as 0.63 for inflation. Countries with falling
rates and inflation tend to outperform while countries with rising rates and inflation
tend to underperform. Countries with stronger increases in consumer confidence
and sales tend to outperform countries with the weakest dynamics in consumer
confidence and sales. Property factors tend to be contrarian and investors should
prefer countries which have gone too far. Weakest growth in yield rates and strongest
growth in vacancies signal the time to overweight countries.
Exhibit 14: Pairwise correlations of returns of different FTSE EPRA/NAREIT A) sectors
and B) countries based on monthly local currency returns. The period is January
1990 to February 2015. Data source: FTSE EPRA/NAREIT and FactSet.
A) Sector correlations
Diversified
Diversified
Retail
Office
Residential
Industrial
Hotels
Healthcare
100%
79%
86%
76%
76%
75%
58%
Retail
Office
100%
91%
82%
87%
81%
75%
Residential
100%
84%
100%
84%
71%
78%
73%
73%
68%
Average correlation: 77%
Industrial
Hotels
100%
83%
71%
100%
58%
"The average
correlation for all
major countries is
relatively low at 37%"
B) Country correlations
USA Canada UK
USA
100%
Canada
54% 100%
UK
59%
37% 100%
Belgium
37%
27% 45%
Germany
31%
18% 36%
France
43%
30% 58%
Sweden
36%
19% 44%
Netherlands 50%
41% 56%
Australia
56%
46% 48%
Hong Kong
32%
30% 29%
Singapore
34%
38% 33%
Japan
28%
29% 30%
Belgium Germany France Sweden Nether- Australia Hong Singapore
lands
Kong
100%
29%
56%
46%
52%
38%
22%
26%
14%
100%
44% 100%
28%
52% 100%
45%
74%
47% 100%
25%
45%
41%
52%
17%
26%
25%
31%
25%
31%
29%
36%
11%
27%
25%
25%
Average correlation: 37%
100%
42%
41%
32%
100%
74%
23%
100%
31%
Exhibit 15: Information ratio of macroeconomic and property specific factors in
country allocation, based on the performance of long-short country portfolios.
Monthly re-balancing with returns in USD. January 1992 to December 2015.
Data source: Bloomberg, FTSE EPRA/NAREIT, Datastream and FactSet.
Information
ratio
Macro factors
Short term rates
Policy rates
Inflation
Consumer confidence index
Retail sales
Property factors Office market yields
Office market vacancy
Preferred countries
0.43
0.53
0.63
0.52
0.49
Falling rates
Falling rates
Falling inflation
Rising confidence
Rising sales
0.34
Weakest growth in yield rates
0.48
Strongest growth in vacancies
Where are the bottom-up inefficiencies?
So-called factor premiums also exist in the listed real estate market. We show that
value factors, in particular, need to be considered as part of the stock selection
process and had significant predictive power in the cross section of listed real
estate stocks in different regions.
We also include some bottom up back-tests based on January 1990 to December 2015
monthly data for the FTSE EPRA/NAREIT indices. The results show the efficacy of value
factors in three different regions: North America, Europe and Asia. The information
ratios are positive everywhere and significant in the global universe. In Europe, all but
the book per share to price ratio are significant. In Asia and the US the results are also
significant.
Exhibit 16: Information ratio of value factors in listed real estate based on the
FTSE EPRA/NAREIT, indices of different regions based on the returns to a longshort portfolio invested in the top ranked stocks and shorting the bottom ranked
stocks using quartiles. The factor strategies invest in the top ranked quartile stocks
and sell short the bottom ranked quartile stocks. Cheap stocks have the highest
dividend per share to price, book per share to price and earnings per share to
price. Monthly rebalancing in EUR for Europe and USD otherwise. January 1990 to
December 2015. Data source: Bloomberg and FTSE EPRA/NAREIT.
Information ratio
Value factors
Dividend per share/price
Book per share/price
Earnings per share/price (next year forecast)
Global
North
America
Europe
Asia
0.68
0.59
0.68
0.46
0.47
0.63
0.56
0.48
0.46
0.55
0.44
0.46
CONCLUSIONS
This white paper underscores the benefits that investing in listed real estate can
bring to investors, including its role as a suitable proxy for direct real estate. By
including an allocation to listed real estate, investors can improve the risk/return
profile of their balanced portfolios. We believe both this extension and the original
research highlight the opportunity that investing in real estate equities can offer to
the broader investment community.
The listed real estate sector has expanded considerably in both size and diversity
over the last 15 years, but it has yet to find wider acceptance among investors.
Despite the worldwide growth in REIT regimes and research suggesting that investing
in a blend of listed and private real estate can offer benefits, many investors remain
biased towards investing in real estate directly or in unlisted investment vehicles.
One of the more thought-provoking findings from our research is that global listed
real estate’s liquidity characteristics have allowed investors to continue investing
in real estate despite the volatile start to 2016 in financial markets. The research
confirms the liquidity advantage enjoyed by listed real estate over direct property
investments, allowing investors to move in and out of markets easily and change
their country and sector allocations in a matter of days rather than the months or
even years it would take in the case of directly-owned property. In our view, this is a
key benefit of an allocation to real estate stocks.
Our research also found that listed real estate can offer similar risk/return
characteristics to owning real estate directly over holding periods of five years and
beyond, so we believe it makes sense for investors to substitute direct real estate in
their portfolios with listed property stocks, at least partially.
Real estate stocks can act as a good portfolio diversifier because over the long term,
they have shown low correlations with asset classes such as general equities, bonds
and commodities. They can improve investment returns in a multi-asset portfolio
without materially increasing volatility, shown in our research.
Finally, this study reinforces the findings of academic research conducted in recent
years by many others, including the European Public Real Estate Association, into the
benefits of blending listed real estate with direct real estate in overall real estate
allocations. In summary, given the increased uncertainty now gripping global capital
markets and economies, we believe investors could potentially earn higher returns
by considering a flexible allocation to listed real estate estate, combined with an
active stock selection process that pays particular attention to value factors.
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real estate allocation?" EPRA Research Paper (2013).
10Scherer, B. "Portfolio construction and risk budgeting." 2nd ed., Risk Books
(2013), pp. 80- 142.
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the case for listed real estate in a multi-asset portfolio

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