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TRANSCRIPT
Leonard Lin
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ERES 2013 Conference
Did Specialised REITs outperform
Diversified REITs during the Credit Crunch?
Evidence from the UK
By Leonard Lin
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Contents
Acknowledgements ................................................................................................... 5
Abstract ..................................................................................................................... 6
Introduction .............................................................................................................. 7
Background........................................................................................................ 7
Aims of the Research Project ............................................................................. 9
Literature Review .................................................................................................... 11
Methodologies ........................................................................................................ 16
Data ........................................................................................................................ 20
Statistics Overview ........................................................................................... 25
Regression Analysis/Results ..................................................................................... 32
Portfolio Comparison Analysis/Results..................................................................... 36
Treynor & Jensen’s Analysis/Results......................................................................... 42
Conclusion ............................................................................................................... 45
References............................................................................................................... 48
Appendix ................................................................................................................. 51
Regression Simulations .................................................................................... 52
Portfolio Comparison ....................................................................................... 53
CD Containing All Excel and Eview 7 files .......................................................... 54
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Tables
Table 1 REIT Classification ........................................................................................ 21
Table 2 Summary Statistics – REITs by Sectors .......................................................... 25
Table 3 Performance Statistics for REITs – Equal Weighted Monthly Figures............. 28
Table 4 Return Data Tests for Normality, Heteroskedasticity and Autocorrelation .... 32
Table 5 Summary Statistics for Variables .................................................................. 33
Table 6 Sharpe Ratios (3 Year Period) ....................................................................... 33
Table 7 Regression Results – Sharpe Ratios versus Fund Characteristics ................... 34
Table 8 Value-weighted annual property type diversification proportion on the basis
of Diversified REITs portfolio .................................................................................... 37
Table 9 Equal-weighted annual property type diversification proportion on the basis
of Diversified REITs portfolio .................................................................................... 39
Table 10 Portfolio Performance Summary ................................................................ 40
Table 11 The Yearly Treynor Ratios & Jensen's Alpha for the UK REITs (Period
2007-2011) .............................................................................................................. 42
Figures
Figure 1 Correlation Matrix for the ELUK, FTSE 100, FTSE 200 and FTSE Small Cap
Indices ..................................................................................................................... 26
Figure 2 Correlation Matrix of Specialised REITs, Diversified REITs and FTSE Small Cap
Indices ..................................................................................................................... 27
Figure 3 Historical Value Weighted Monthly Returns (Specialised REITs versus
Diversified REITs) ..................................................................................................... 28
Figure 4 Average Return and Standard Deviation - Diversified versus Specialised REITs
................................................................................................................................ 29
Figure 5 Average Return and Standard Deviation - REITs by Sectors ......................... 30
Figure 6 Average Return and Beta - REITs by Sectors ................................................ 31
Figure 7 Compositions of Diversified REITs portfolio - average market cap (2007-2011)
................................................................................................................................ 36
Figure 8 Value-weighted Diversified REITs ................................................................ 37
Figure 9 Specialised REITs portfolio using the overall property type proportions of the
value-weighted Diversified REITs in Table 8 .............................................................. 38
Figure 10 Equal-weighted Diversified REITs .............................................................. 39
Figure 11 Specialised REITs portfolio using the overall property type proportions of
the equal-weighted Diversified REITs in Table 9 ....................................................... 40
Figure 12 Treynor Ratios .......................................................................................... 43
Figure 13 Jensen’ Alphas ......................................................................................... 44
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Equations
Equation 1 Sharpe ................................................................................................... 16
Equation 2 Multiple Factor Sharpe Ratio Regression ................................................ 16
Equation 3 Treynor .................................................................................................. 18
Equation 4 Jensen's Alpha ....................................................................................... 19
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Acknowledgements
I would like to thank my lecturers Professor Tony Key and Mr Stephen Lee and my
supervisor Dr Fotis Mouzakis for giving me the necessary inspiration, support and
guidance. It has been such a fantastic journey, exploring different methodologies,
self-learning the techniques and completing the research and analysis independently.
I also would like to thank my beloved wife, B. Hsiang, who has supported,
encouraged and believed in me, since I started in the masters program at Cass
Business School. This research is dedicated to her.
* The research dissertation was originally submitted as part of the requirements for the
award of the MSc in Real Estate program, Cass Business School, City University London
(September 2011). The original title for this research project was “Do the property type
Specialised REITs outperform the property type Diversified REITs in the UK?”.
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Abstract
This study looks at the return and risk characteristics of the Diversified and
Specialised REITs in the UK over the last four and half years commencing January
2007. The methodologies used in this study incorporate some simple statistic tools,
multiple factor Sharpe ratio regression, and portfolio construction and use of
efficient frontier models.
In summary, the hypothesis that the Specialised REITs can perform better than the
Diversified counterpart during the credit crunch can be supported. The Diversified
REITs show a moderate return with lower level of volatility. However, the
Specialised REITs track the market more closely.
The Office REITs and Retail REITs produce significant impact on the risk-adjusted
performance. The Specialised REITs portfolio under the equal-weighted portfolio
construction produces a better mean return at a similar level of the volatility, than
the Diversified REITs portfolio.
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Introduction
Background
Real estate investment trusts (REITs) were originally created by the U.S. Congress in
1960 for the purpose of providing small investors an opportunity to invest in real
estate assets and enjoying the same benefits that shareholders have in investment
trusts (Chan et al. 2003). Australia has a similar vehicle established and named
“Listed Property Trust” since 1970’s.
REITs have not been used or invested commonly by institutional investors in the US
until the introduction of the 1993 Revenue Reconciliation Act, where the restriction
of “no more than 50% of a REIT’s stock could be owned by five or fewer persons” was
lifted (Lee 2011a). With the REITs main advantages (tax transparency and liquidity),
it has progressively reached many mature and emerging markets and countries.
There are twenty-one countries that have already established REIT regimes and
approximately six or seven countries that are considering introducing the
establishment of the REITs.
There are three types of REITs in the market (Lee 2011a). Equity REITs invest
directly into real estate, and make returns from rents and property sales, with a debt
level at or around 35%. Mortgage REITs are portfolios of real estate loans with
loan-to-value ratios from 70% to 100%. Hybrid REITs are a mix of the Equity REITs
and Mortgage REITs. Lee further commented that the Equity REITs are being
identified as an effective real estate investment vehicle and representing 90% of the
REIT market. The use of a pure equity REIT sample has become the standard in
more recent years, as a way to reduce potential statistical bias such as
heteroskedasticity (Benefield et al. 2009).
There was also a noticeable shift from property type diversified REITs to property
type specialised (focused or pure-play) REITs in the US. It was found that
property-type diversification increases both property-level cash flows and general
and administrative expenses (including borrowing costs) and decreases liquidity
(Capozza & Seguin 1999).
There are several motivations behind this shift (Geltner & Miller 2001). It was
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suggested that management speciality and cost efficiency can be better achieved by
the specialised REITs. Investors refer to make their own portfolio diversification
decisions with the specialised REITs. From the analysts’ and stock markets’ point of
views, the specialised REITs with one or fewer market segments are easier to
understand and analyse.
The UK is relatively young in the development of REITs as the UK REIT Legislation has
only come in force on January 1st, 2007. To qualify as a REIT in the UK context,
there are a number of structure, activity, asset and income conditions to be met. A
UK REIT should be property rental business, with conditions such as that at least 75%
of its assets must be related to property rental business, and at least 75% of its
accounting profits must be related to property rental business (Deloitte 2010). A
REIT is to be a tax resident in the UK only, a closed-ended company, and listed on a
recongised stock exchange. A REIT must hold at least three properties (no single
property can exceed 40% of the total value of the properties), and must distribute
90% or more of its tax exempt income profit as dividends. If only these conditions
are satisfied, then the REIT will remain in the UK REIT Regime.
According to British Property Federation, there are twenty-three REITs being
recorded on the REITA’s list of UK REITs (REITA.ORG 2011). According to Bloomberg,
there are twenty-two REITs in the UK stock exchange, however, at the time of
conducting this research, there are only twenty-one REITs return data series being
made available on Bloomberg with a market capitalisation of approximately £27.36
billion GBP (Bloomberg 2011). In this instance, the UK REITs to be studied in this
research will be limited to these twenty-one REITs on Bloomberg.
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Aims of the Research Project
The REIT model is slightly different in each country depending on their legal
framework, taxation and reporting structures. REIT has progressively become a
global brand (Rodney 2011). REITs play a role in mixed asset portfolios, in real
estate markets, as well as in the capital market globally.
This research will explore the returns and risks characteristics that the specialised
REITs can offer to the general investors and institutional portfolio investors, in the
time of the credit crunch. The hypothesis is that the Specialised REITs can perform
better than the Diversified counterpart during the credit crunch.
The mainstream corporate finance literatures suggest that diversified investment
vehicles trade at a discount, in comparison to the competing specialised investment
vehicles in the US market (Benefield et al. 2009). The authors tested their
hypothesis based on 75 equity REITs (mixture of specialised and property type
diversified REITs) in the US, between 1995 and 2006. Surprisingly, the authors
found that the property type diversified REITs are better performers, when the
overall economy and market conditions were performing well.
They further addressed that there is very limited evidence that the specialised REITs
would have performed better in the recession period(s). This opens a door of
opportunity for further research on whether the specialised REITs would outperform
the property type diversified REITs in the recessions.
Ro & Ziobrowski also investigated if the specialised REITs outperform property type
diversified REITS, and further compared the performance of specialised versus
diversified REIT portfolios, in the US, between 1997 and 2006 (Ro & Ziobrowski
2009).
They found that diversified REITs outperformed specialised REITs, and the specialised
REITs have higher market risk than diversified REITs. However, the element of the
specialised REITs’ performance was not addressed in the research.
A similar research and discussion were carried out in the UK. The discussion was on
real estate funds, and was on whether it is better to diversify the real estate funds by
a property type across regions or within a region across all the property types (Lee &
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Stevenson 2005). The authors also supported that the funds should be diversified
immediately, as the performance were indeed superior, comparing to the specialised
real estate funds.
Eichholtz attempted to investigate whether there was a benefit to develop the real
estate portfolio(s) from “one property type in one region” to “mixed property types
in one region” or to “mixed property types in multiple regions”. The data was
drawn from both the US and the UK (Eichholtz et al. 1995). The results showed the
nations behave quite differently to the composition of the portfolios. Again the
focuses were more on the population, scale of economy and characters of cities,
rather than performance of these portfolios in economy recessions or booms.
In summary, however, none were primarily focusing on the specialised REITs’
performance in the recessions. This research offers a closer look at the specialised
REITs’ performance against the property type diversified REITs in the recession or so
called “the credit crunch”, between 2007 and 2011.
The reminder of the study will proceed as follows: Section 2 provides relevant
literature reviews. Section 3 provides the methodologies in detail with formulas.
Section 4 provides the data and preliminary statistics overview, and Section 5
provides analysis and results, conclusions, limitation and recommendation for future
research.
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Literature Review
The term of property-type specialised REIT refers to a portfolio with no direct
exposure to any other property type. The term is also commonly referred to and
defined as “pure-play REIT” (Geltner & Kluger 1996). The authors used a term
called “Pure-play portfolio”, and further explained that a pure-play portfolio should
represent returns from a specific sector’s investment without any direct exposure to
other sectors. Some REITs may change strategy of holding a specific sector’s
investment depending on their long term or short term positions. The authors then
suggested analysing the exposure of these REITs from their balance sheets
(accounting data) or from their annual valuation (appraisal values). By doing this,
the REITs’ characters can then be quantitatively characterised. Organisations, for
example, REITA, part of the British Property Federation, describes the existing UK
REITs into REITs by sectors or diversified REITs.
Benefield further defined a specialised REIT as a REIT which is comprised of 75% or
more of the same property type with its portfolio (Benefield et al. 2009). In light of
the conflicted classifications or description of diversified and / or specialised adopted
by the REITA and Bloomberg, each REIT used in this study will be analysed and
rebelled based on Benefield’s definition of the “specialised REIT”.
As the UK REITs have only been established since January 2007, a challenge for this
study will be the shorter return data series. In this study, the weekly return data
series will be adopted for the calculations. It has been demonstrated that the use
of shorter time periods can be just effective in performance rating (Grinblatt &
Titman 1989). Return data from shorter time periods was used in the more recent
studies for the purposes of comparing “old” and “new” REITs. It was reported that
property-type diversified REITs performed poorly compared to the most of the
specialised REIT categories by using monthly return data of a sample of REITs
between 1993 and 1997 (Chen & Peiser 1999).
This study will firstly use some simple statistical tools to draw a picture of what
happened for REITs over the sample period. These statistics include the mean
returns, standard deviations, correlations and the use of market value weighted
index for a close comparison of the performance of “specialised” and “diversified”
REITS. Chen & Peiser (1999) used some simple methods to compare the “new” and
“old” REITs and found the “new” REITs exhibited higher returns.
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This study will then employ the performance ranking methodologies of Sharpe,
Treynor and Jensen’ Alpha, and further draw comparison of the performance of the
diversified and specialised REITs in the stock market, as part of this proposed
research.
Sharpe (1966) adopted a Capital Market model that generates predictions of the
future (in Sharpe’s paper, present data was adopted, instead) performance and risk
of the mutual funds. The author tested on a sample of 34 open-end mutual funds
in the period of 1954 – 1963. It was testing the measure of the net performance
(gross yield less management expenses) which the annual rate of return included the
sum of dividend payments, capital gain distributions and changes in net asset value.
The author then rated the performance by Reward-to-Variability ratio and the
Treynor Index.
Investors demand and receive higher returns with increased variability, suggesting
that variability and risk are related (Lee 2011b). The concept is that a portfolio
should give a return equal or no less than some minimum hurdle rate of return (risk
free investments in Treasury Bills and alike). The risk free rate from the returns will
be stripped out and the risk premium (the remaining return component) will be then
divided by standard deviation. This standard deviation refers to the measure of
variability of returns (Sharpe 1966). A portfolio’s Sharpe ratio being higher than a
benchmark’s Sharpe ratio or the competitor’s Sharpe ratio means the portfolio
manager has outperformed the benchmark or the competitor.
Morri and Lee (2009) studied the performance of Italian real estate mutual funds.
They use the monthly data for seventeen (17) real estate mutual funds, over a 3 year
period from Year 2005 to 2008 (for the purpose of limiting the survivorship bias).
Elements or factors that can affect the return and risk characteristics of a fund are
being discussed and tested in multiple factor Sharpe ratio regressions. These
elements or factors include, but not limited to, risk (by the indicators of beta or
standard deviation), expenses (testing the management efficiency of the funds or in
the context of managing property operationally), size, fund age, regional and
property-type diversification, and the impact of geographical concentration.
Beta and standard deviation indicators are used widely by the researchers to assess
the performance of the equities. Beta measures the systematic risk of a portfolio
compared to the market (Morri & Lee 2009). Higher the beta means that a fund
tracks the market more closely than a fund with lower beta (Chen & Peiser 1999).
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Standard deviation measures the volatility of the return in relation to its mean return,
including both systematic and unsystematic risks. These indicators will be used in
this study (see the later section).
Expenses that Morri and Lee (2009) used were management efficiency (fund
expenses over total assets) and property management (expenses of operating
properties over the number or total value of the properties). Morri and Lee further
explained a common claim that the fund managers who charge higher fees are more
skilled and able to provide higher investment returns. Expenses will be investigated
in this study as the Bloomberg provides the monthly operating expenses and total
asset value data. The limitation of using this data lies at the composition of the
operating expenses is unknown.
Size is suggested as the most significant variable factor in explaining the risk-adjusted
performance of real estate mutual funds (Lin & Yung 2004). Morri and Lee (2009)
suggested that the large mutual funds have advantages over the small ones such as
the economy of scale (cheaper overhead expenses) and superior bargaining and
negotiation positions (for prime investment opportunities). However, the larger
funds cannot grow perpetually as the investment opportunities are restricted by the
size of the market and the returns will eventually decline. Smaller firms can still
perform but the returns are restricted by the small pools of properties they own. Size
of the UK REITs is available on Bloomberg with level of change of total value on
monthly basis. This data will be used in constructing the market value weighted
Diversified and Specialised indices and in the multiple factor Sharpe ratio regression
model in the later section.
Of particular interest, Morri and Lee (2009) also studied the region and property type
diversification factors and looked at their impact on the risk adjusted performance of
the real estate mutual funds. They adopted the portfolio herfindahl index for
property typologies and locations. In this study, the property types will be
represented by dummy variables 1 and 0. A diversified REIT in the regression will
be rewarded “1” in the Diversified variable (DIV) and given “0” in other specialised
sector variables (see the Methodologies section for further details). Regional
diversification wise, the REITs are classified into the UK only, UK & Europe and UK &
Global (including investment in USA). The REITs investing in France will be
rewarded “1” in the variable factor - Europe and investing in California will be
rewarded “1” in the variable factor – Global.
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Leverage factor which was not discussed and included by Morri and Lee (2009) is
incorporated in this study. The preliminary tests for normal distribution of the
monthly return data of each REIT indicated that the REITs which leverage heavily
tend to have non-normal return distribution with significantly higher JB statistics.
Bloomberg provides the leverage data of each REIT.
The REITs monthly return data will be tested for Normality (JB statistics),
Heteroskedasticity (White’s Test) and Serial Correlation (LM’s Test). This is to ensure
that the REITs that are selected for the multiple factor Sharpe ratio regression have
normally distributed return data, efficient and unbiased (see Data section for further
detail).
Ro and Ziobrowski (2009) compared the performance of Specialised REITs and
Diversified REITs by constructing two portfolios. One portfolio was comprised of
property type specialised REITs and the other portfolio was comprised of only
property type diversified REITs. In order to draw a like for like statistical comparison
of the return and risk characteristics of the two portfolios, the authors adjusted for
the balance of the weighting (equal weighted and valued weighted) and property
type mix.
The other two ranking methods which will be used in this study include the Treynor
ratio and Jensen’s Alpha. The Treynor ratio is similar to Sharpe ratio, sharing the
same numerator, however, the denominator is different; the Treynor ratio uses
“systematic risk” which is estimated by the portfolio beta (Lee 2011b).
Jensen (1968) proposed an absolute measure of performance to examine the
forecasting ability of the mutual fund managers in the US, rather than a portfolio’s
efficiency. His model was a form of capital asset pricing models and was taking
explicit account of the effects of “risk” on the returns of portfolios. The paper
highlighted the difference that a superior forecaster (manager or analyst) can make
on a managed portfolio (systematic risk, risk premium, risk on return, etc) as well as
the standard error of estimate of the performance measure.
Any positive or negative alpha can be examined and explained by the fund manager’s
outstanding investment ability or pure luck (Lee 2011b).
Eichholtz used a sample of equity REITs with data from 1990 to 1996 and concluded
that specialised REITs outperform the property-type diversified REITs according to
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Jensen’s Alpha (Eichholtz et al. 2000). The market proxies used were the Standard
& Poor 500 and a REIT index which include the sampled REITs. It was conducted
during the period when the REIT industry was going through transformation. Again,
the study was not carried out for the purposes of measuring the performance of
REITs during the recession, as this is the focus of the study. In this instance, either
the FTSE Small Cap and / or the FTSE UK REIT Indices will be used to determine the
alphas and betas depending on the correlation test result (see in the later section).
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Methodologies
This focus of this study is the performance differences or indifference of
property-type specialised REITs and diversified REITs in the time of the credit crunch.
Methodologies will be the market-based measures of performance which have been
utilised for pension funds, trust funds and mutual funds over years by various
corporate finance researchers.
Sharpe Ratio
𝑆 =R − 𝑅𝑓
σ
Equation 1 Sharpe
𝑆 = Sharpe Ratio on 3 Year Monthly Return Data
R = Monthly Return of a REIT (Return + Dividend)
𝑅𝑓 = Monthly Risk Free Rate of Return (in this case, UK Government Bond 1 Year)
σ = Monthly Standard deviation of the REIT’s Return
Note: Monthly Sharpe Ratio will then be square-rooted by “12” (months), for a yearly
figure.
Sharpe ratio can easily rank funds on risk-adjusted performance. Sharpe ratio does
not depend on indentifying the market portfolio and effectively avoids being
manipulated by leverage. However, the limitation is that Sharpe ratios can be
difficult to interpret and negative Sharpe ratios do not rank funds correctly (Lee
2011b).
Multiple Factor Regression Model (Sharpe Ratio)
𝑆𝑎𝑟𝑝𝑒 = 𝛼 + 𝛽1𝐴𝑔𝑒 + 𝛽2𝑆𝑖𝑧𝑒 + 𝛽3𝐷𝑒𝑏𝑡 + 𝛽4𝐸𝑓𝑓𝑔𝑖 + 𝛽5𝐷𝑖𝑣 + 𝛽6𝑂𝑓𝑓
+ 𝛽7𝑅𝑒𝑡𝑎𝑖𝑙 + 𝛽8𝐼𝑛𝑑 + 𝛽9𝐻𝑒𝑎𝑙𝑡 + 𝛽10𝑆𝑡𝑜𝑟𝑎𝑔𝑒 + 𝛽11𝑈𝐾
+ 𝛽12𝐸𝑢𝑟𝑜 + 𝛽13𝐺𝑙𝑜 + 𝜀
Equation 2 Multiple Factor Sharpe Ratio Regression
A 3 year performance period is used in the regressions in the later sector, to limit the
effects of survivorship bias (Morri & Lee 2009).
𝛼 = regression intercept term
𝛽𝑠 = regression coefficients
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ε = the regression error term
the dependent and independent variables are defined in the earlier section (see
Literature Review)
AGE: Majority of the REITs commenced since January 2007 with few exceptions of
REITS started in mid or late 2009 or 2010.
SIZE: each REIT is given a rating proportionately (the market cap of the REIT over the
entire REIT market cap)
DEBT: based on the total debt / total asset ratio provided by Bloomberg (3 year
average)
EFFIG: Management efficiency measured by the operating expenses over the total
assets (3 year average)
DIV: dummy variable, “1” rewarded for a Diversified REIT
OFF: dummy variable, “1” rewarded for an Office REIT
RETAIL: dummy variable, “1” rewarded for a Retail REIT
IND: dummy variable, “1” rewarded for an Industrial REIT
HEALTH: dummy variable, “1” rewarded for a Healthcare REIT
STORAGE: dummy variable, “1” rewarded for a Storage REIT
UK: dummy variable, “1” rewarded for REITs investing in the UK
EURO: dummy variable, “1” rewarded for REITs investing in Europe
GLO: dummy variable, “1” rewarded for REITs investing anywhere outside of the UK
and Europe
With this proposed model, multicollinearity can be the primary concern (Morri & Lee
2009). The most common test, they suggested, is by way of variance inflation factor
(VIF). VIF measures the degree of variance of an estimated coefficient 𝛽𝑠
increases if the independent variables are correlated. They further suggested the
VIF for an individual variable should be 4 or less, for avoiding multicollinearity.
Portfolio Construction and Comparison
The portfolios of the Diversified REITs and the property-type Specialised REITs are
constructed in two ways; first is the value-weighted and the other is equal-weighted.
In this study, six (6) diversified REITs have the yearly break down of the property-type
components and therefore these subjects are used to construct the Diversified REIT
portfolio. The performance of the diversified REITs portfolio will be likely
dominated by the larger REITs on the value-weighted basis. Ro and Ziobrowski
(2009) suggest that to compensate for the larger REITs in the portfolio, it is
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recommended to construct the diversified REITs portfolio on an equal-weighted basis.
In that case, then the larger REITs will become one of the equal components in the
portfolio.
The value-weighted specialised REITs portfolio will be constructed and matched to
the property-type proportions of the diversified REITs portfolio. Ro and Ziobrowski
(2009) suggest constructing a specialised REITs portfolio to match the diversified
REITs portfolio on an equal-weighted basis can best eliminate the disproportionate
size effect that the larger REITs have on the results.
Thirdly and lastly, two other common performance measures are employed in this
study to assess performance of the subject REITS and these include Treynor Ratio
and Jensen’s Alpha.
Treynor Ratio
𝑇𝑅𝑅𝐸𝐼𝑇 =𝑅𝑅𝐸𝐼𝑇 − 𝑅𝑓
𝛽𝑅𝐸𝐼𝑇
Equation 3 Treynor
𝑇𝑅𝑅𝐸𝐼𝑇 = Treynor Ratio on 4.5 Year Monthly Return Data
𝑅𝑅𝐸𝐼𝑇 = Monthly Return of a REIT (Return + Dividend)
𝑅𝑓 = Monthly Risk Free Rate of Return (in this case, UK Government Bond 1 Year)
𝛽𝑅𝐸𝐼𝑇 = Beta of the REIT, derived by regressing the REIT’s returns against the
benchmark’s return (in this case, FTSE Small Cap index)
Note: Monthly Treynor Ratio will then be square-rooted by “12” (months), for a
yearly figure.
This measure shows the excess return per unit of the systematic risk (beta). The
higher the Treynor ratio, the better the investment performance is. Therefore, it is
critical to use the most appropriate market portfolio to determine the beta.
The only difference between the Treynor and Sharpe ratios is the use of beta factor.
Theoretically, if a portfolio is fully diversified with no specific risk, then the Treynor
and Sharpe ratios shall give the same ranking. However, the number of properties
to hold in a portfolio will be large if it wishes to remove all the specific risk (Lee
2011b). Lee expected that the majority of the UK real estate portfolios will contain
high degree of specific risk/unsystematic risk and it will lead to different ranking
results on the Sharpe and Treynor measures.
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Jensen’s Alpha
𝐽𝐴𝑅𝐸𝐼𝑇 = 𝑅𝑅𝐸𝐼𝑇 − [𝑅𝑓 + 𝛽𝑅𝐸𝐼𝑇(𝑅𝑀 − 𝑅𝑓)]
Equation 4 Jensen's Alpha
𝐽𝐴𝑅𝐸𝐼𝑇 = Jensen’s Alpha ratio on 4.5 Year Monthly Return Data
𝑅𝑀 = the return of the market benchmark
𝑅𝑓 = Monthly Risk Free Rate of Return (in this case, UK Government Bond 1 Year)
𝛽𝑅𝐸𝐼𝑇 = Beta of the REIT’s return
Note: Monthly Alpha will then be square-rooted by “12” (months), for a yearly figure.
Jensen’s alpha computes the difference between the average return to the fund and
the average return to the market portfolio whose systematic risk (𝛽𝑝) is identical to
that of the fund (Jensen 1968). Hence this return can be attributed purely to the
fund manager’s selection ability (Lee 2011b).
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Data
British Property Federation website records total number of twenty-three (23) REITs
on the REITA’s list of UK REITs (REITA.ORG 2011). Bloomberg on the other hand
records twenty-two (22) REITs in the UK stock exchange, however, at the time of
conducting this research, there are only twenty-one (21) REITs return data series
being made available on Bloomberg, excluding Vector Hospitality (Bloomberg 2011).
REITA describes, rather than classifies the sectors that the REITs invest in with terms
– diversified, self storage, retail, offices, industrial, residential, and health care. In
some cases, REITA uses the term “diversified” in one instance (British Land), and use
description such as “retail, offices, industrial” for REITs that invest in multiple sectors
(see Glenstone Property Group’s and Hammerson’s descriptions). Of the
twenty-one (21) REITs, REITA described seven (7) REITs as “diversified” and fourteen
(14) REITS as “non-diversified”.
Bloomberg uses the classifications more consistently on the other hand.
Bloomberg adopts the terms – diversified, storage, office property,
warehouse/industrial, retail and health care. It is clear that the REITs labelled as
“diversified” are indeed diversifying across some or all sectors and the REITs labelled
as “office property” are indeed specialising in one sector only. Of the twenty-one
(21) REITs, Bloomberg labels fourteen (14) REITs as “diversified” and five (5) REITs as
“specialised in a specific sector”, whilst two (2) REITs were not labelled.
The two sources above clearly use the terms and description of the REITs’
classification inconsistently. Before analysing the REITs in question and their
performance, it is logical to review the composition of these twenty-one (21) REITs
individually and classify these REITs independently in light of the seeing the
inconsistent classification of the REITs. In question, there are ten (10) conflicted
labels by cross-referencing the two major sources (see the REIT Classification table
below).
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Table 1 REIT Classification
In this study, a REIT will be labelled as a “specialised” REIT if it is comprised of 75% or
more of the same property type with its portfolio, for more than half of the sample
period (Benefield et al. 2009). Bloomberg provides the summary of the total assets
that each REIT currently holds or has held from the accounting periods beginning in
March / April 2007 till March / April 2011.
Capital Shopping Centre was a REIT with conflicting labelling and description shown
as “Retail” in REITA.ORG but as “Diversified” in Bloomberg. Screening the past
annual reports available online (Capital Shopping Centres 2011), the retail
component within the portfolio indeed has been in excess of 75% consistently over
the sample period. Therefore, it is labelled as “Retail” in this study.
Derwent London REIT has been classified by Bloomberg as a Diversified REIT without
a clear disclosure of the composition of the assets, for three accounting periods
commencing December 2008. The composition of Derwent’s portfolio is
predominately of commercial properties and residential properties in London, and a
small number of shopping centres located in Scotland (Derwent London 2011). A
further investigation has been carried out by reviewing the balance sheet reports
from its website backdated to Year 2007, however, the available financial reports
online also do not disclose the allocation of the assets, sector wise. The reports
only referred to their assets as “trading properties” and did not classify any further in
REIT Name Sector Label by REITA.ORG Sector Label by Bloomberg Label for Proposed Research
1 Big Yellow Group Self Storage Storage Storages
2 British Land Diversified Diversified Diversified
3 Caiptal Shopping Retail Diversified Retail
4 Derwent London Offices Diversified Diversified
5 *Glenstone Property Group Retail, offices, industrial n/a n/a (no return data available)
6 Great Portland Estates Offices Office Property Offices
7 Hammerson Retail, offices Diversified Diversified
8 Hansteen Industrial Warehouse/Industrial Industrial
9 Highcroft Investments Diversified Closed-end funds Diversified
10 Land Securities Diversified Diversified Diversified
11 Local Shopping REIT Retail Diversified Retail
12 London & Stamford Property Offices, Retail Diversified Diversified
13 McKay Securities Offices Diversified Offices
14 Metric Property Investments Retail Diversified Retail
15 Mucklow (A & J) Group Offices, Industrial Diversified Diversified
16 NewRiver REIT Retail n/a Retail
17 *Pineapple corporation Residential, Industrial n/a n/a (no return data available)
18 Primary Health Group Health Care Health Care Healthcare
19 Shaftesbury Retail Diversified Diversified
20 Segro PLC Industrial Diversified Industrial
21 Town Centre Securities Retail Diversified Retail
22 Warner Estate Retail Diversified Diversified
23 Workspace Group Offices, Industrial Office Property Diversified
24 *Vector Hopsitality n/a Hotels and Motels Hotels (no return data available)
Diversified Labels 7 14 10
Non Diversified Labels 14 5 11
No Labels 2
Total 21 21 21
Note: * refers to these return data not made available on Bloomberg
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detail. The indicator which it is used to classify Derwent London REIT as a
“diversified” REIT for this study is by screening at the properties on the website in
conjunction of the REIT’s description listed on Bloomberg.
Great Portland Estates has been classified by REITA.ORG and Bloomberg as “Offices”
REITs, however, the annual reports indicated that the REIT invests in both offices and
retail assets and there are three out of five sample periods showed the office
component in excess of 75%. This REIT is on the border line between “diversified”
and “specialised” as a REIT, however, it still fits in the “specialised” benchmark and
will be treated as “specialised” in this study.
McKay Securities showed a conflicted classification as it was classified as “diversified”
in the Bloomberg and as “specialised/offices” in the REITA.ORG. The annual reports
starting from 2007 and ending 2011 were studied and it was found that the McKay
Securities consistently invested in offices in excess of 75% over the sample period
(McKay Securities 2011). It is therefore classified as “specialised” in this study.
Metric Property Investment PLC REIT only commenced in April 2010. Metric was
described by REITA.ORG as “Retail” and by Bloomberg as “Diversified”. According
the portfolio description provided (Metric Property Investments 2011), all the assets
are retail parks and supermarkets and it is appropriately described as
“Retail/Specialised” by REITA.ORG.
Of interest, Mucklow A & J Group PLC was labelled as a “diversified” REIT investing
across industrial, office and retail sectors (Mucklow A & J Group PLC 2011). It was
however showed a consistency of owning in excess of 70% in industrial sector across
the sample period. Its performance will indeed be reviewed closely in this study.
Sergo PLC was labelled as “diversified” in Bloomberg but as “industrial” in REITA.
After reviewing its published property analysis over the sample period, the industrial
sector assets indeed have been consistently in excess of 75%. Therefore it will be
labelled as “specialised” in this study.
Shaftsbury PLC was labelled as “diversified” in Bloomberg but as “retail” in REITA.
Shaftsbury have 7 portfolios which the majority are wholly owned portfolios with
one joint venture (Longmartin). Their annual reports disclose the total square
footage of their shops, restaurants & leisure, offices and residential, however the
estimate asset values of their assets by sector are not made available. It is
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understandable that labelling of this REIT without transparent and publically made
available data is difficult. In this case, Bloomberg’s label will used in this study.
Town Centre Securities annual reports indicated that it has owned in excess of 75% of
retail assets consistently over the sample period and it is therefore being labelled as
“retail” in our study (Town Centre Securities PLC 2011). It was labelled previously
by Bloomberg as “diversified”.
Workspace Group was another REIT with conflicted labelling. The sources available
from the online annual reports and Bloomberg do not provide indication of the
allocation of its sector diversification (Workspace Group 2011). However,
Workspace Group offers a variety of spaces to its tenants including, but not limited to,
storage spaces, yard space, retail space, offices and industrial units. This REIT is
labelled as “diversified” in this study, which matches REITA’s classification of
Workspace Group (REITA.ORG 2011).
Warner Estate’s annual reports showed that no single property type has had
dominated the portfolio for over 75% over the sample period (Warner Estate 2011).
REITA.ORG described the REIT more correctly than Bloomberg. This REIT will be
classified as “diversified” in this study.
In summary, out of the twenty-one (21) REITs, there are ten (10) diversified REITs and
eleven (11) specialised REITs. Note: In some calculations, two Retail REITs with
short data trend will be removed from calculation to avoid any biased or distorted
results. Removal of the two Retail REITs will be clearly identified in the later
sections.
As the study focuses on the market-based measures of performance, REITs included
in the analysis should the ones traded publically, with the price information available
from Bloomberg. The data used is the monthly “last price” including non trading
days and it will then be converted into the appropriate returns and indices for this
research. Government bond (1 year) data will be used as Risk Free rate for the
calculations of Sharpe ratios, Treynor and Jensen’s Alpha ratios. The sample period
is from January 2007 to June 2011.
The stock market return indices such as FTSE EPRA/NAREIT UK REIT Index (ELUK),
FTSE 100 Index (UKX), FTSE 250 Index (MCX), FTSE 350 Index (NMX), FTSE Small Cap
Index (SMX) and FTSE All-Shares Index (ASX) are also collected from Bloomberg, for
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the purpose of comparing the return and risk characteristics of the UK REITS.
The prices of the REITs traded on weekly basis are extracted from Bloomberg,
depending on the commencement of each REIT on the stock exchange. Majority of
REITs commenced trading in January 2007 and three (London & Stamford Property,
Metric Property Investment and NewRiver REIT) only joined the UK REIT regimes in
late 2007 and or between 2009 and 2010.
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Statistics Overview
The returns (including dividends) and standard deviations for the Specialised REITs
and Diversified REITs are examined. The portfolios of the Specialised and
Diversified REITs and Property Type Specialised REIT Indices are conducted both on
market value weighted average monthly return and equal weighted (unweighted)
average monthly return basis. Table 2 below shows the summary statistics of the
data series. During the sample period from January 2007 to July 2011, the number
of the Diversified REITs in the sample is 10 with an average market capitalisation of
£1.3 billion. The Specialised Property REIT Portfolio, Office REIT, Retail REIT,
Industrial REIT and other REIT types are all smaller than the Diversified REITs in terms
of the market capitalisation.
Table 2 Summary Statistics – REITs by Sectors
The Diversified REIT return is right-skewed; however, the Diversified REIT return is
less extreme on the value weighted basis. In terms of excess kurtosis (K-3), the
Diversified REIT returns on both value and equal weighted basis are leptokurtic (peak
around the mean and flatter at the tails); however, the value weighted diversified
REITs return is less leptokurtic than the equal weighted diversified REITs. On value
weighted basis, the Diversified REITs outperformed the Specialised REITs (Portfolio
wise) with a higher return and a lower standard deviation. However, on equal
weighted basis, the result is noticeably an opposite outcome. When returns are
equal weighted, the Diversified REITs return is the least attractive and its volatility sits
in the middle of all other REIT types. This exhibits a different result from Ro &
Ziobrowski’s result finding in their survey in 2009, which suggests that the Diversified
REITs exhibit the least risk than their specialised counterparts.
The result also indicates that the Health REIT had the lowest volatility on both value
Period (2007 - 2011)
Sector# of
REITs
Market Cap
(£m) Return St. Dev Skewness Kurtosis Return St. Dev Skewness Kurtosis
Diversified Property REIT Portfolio 10 1335.30 -0.47% 7.98% 0.16 3.90 -0.87% 7.60% 0.73 6.81
Specialsed Property REIT Portfolio 9 585.07 -0.66% 9.08% -0.19 4.75 -0.53% 7.39% 0.78 6.40
Office REIT Index 2 85.56 0.11% 8.01% 0.43 3.95 -0.58% 8.01% 1.13 6.25
Retail REIT Index 3 261.20 -0.86% 9.37% -0.38 3.57 -0.72% 9.38% 0.55 6.75
Industrial REIT Index 2 189.96 -0.85% 12.17% 0.03 5.31 -0.49% 10.03% 0.44 6.24
Healthcare REIT Index 1 13.12 -0.19% 2.09% 0.49 2.24 -0.19% 2.09% 0.49 2.24
Storage REIT Index 1 35.23 -0.62% 10.88% 0.95 7.60 -0.62% 10.88% 0.95 7.60
Note: The number of REIT indicates the number of REITs used to construct each porfolio or index. All data are on monthly basis. Two Retail
REITs that started in 2009 and 2010 were removed from this analysis due to short data trend.
Value Weighted Equal WeightedAverage Monthly
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and equal weighted basis. Industrial REITs are the most volatile on value weighted
basis.
Figure 1 (below) shows index return data that are collected from Bloomberg and
indices include FTSE EPRA/NAREIT UK REIT Index (ELUK), FTSE 100 Index (UKX), FTSE
250 Index (MCX), FTSE 350 Index (NMX), FTSE Small Cap Index (SMX) and FTSE
All-Shares Index (ASX). The index returns have been re-based at 1 January 2007
(from January 2007 to July 2011, the sample period).
Figure 1 Correlation Matrix for the ELUK, FTSE 100, FTSE 200 and FTSE Small Cap Indices
Although FTSE 100 Index is more commonly used as a benchmark for investment
analysis, the finding indicates that the FTSE EPRA/NAREIT UK REIT Index performs
more closely to FTSE Small Cap Index with a positive correlation of 0.83. This is in
line with Lee’s view of REITs performing like small caps (Lee 2011a).
The ten (10) diversified REITs and nine (9) specialised REITs of the twenty-one (21)
REITs selected for this study have been separated and computed into two separate
indices – Diversified REIT Index (DivIndex) and Specialised REIT Index (SpecIndex).
This is of a monthly return index based on market value weighted average return
(including dividend) of the respective REITs type. With this information, it allows to
further look at the performance of the DivIndex & SpecIndex against FTSE Small Cap
Index (SMXIndex).
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Figure 2 Correlation Matrix of Specialised REITs, Diversified REITs and FTSE Small Cap Indices
The correlation statistics (above) show that the Specialised REITs perform more
closely and share more systematic risk with the FTSE Small Cap Index, with a positive
correlation of 0.71. Diversified REITs and Specialised REITs share a strong
correlation of 0.90 with each other.
Covariance Analysis: Ordinary
Date: 08/18/11 Time: 12:36
Sample (adjusted): 2007M02 2011M06
Included observations: 53 after adjustments
Balanced sample (listwise missing value deletion)
Covariance
Correlation DIVRETURN SPECRETURN SMXRETURN
DIVRETURN 0.006247
1
SPECRETURN 0.006431 0.008082
0.904963 1
SMXRETURN 0.003647 0.00424 0.004428
0.69346 0.708684 1
Note: Two Retail REITs (METP & NRR) with short data trend are removed
from this calculations.
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Figure 3 Historical Value Weighted Monthly Returns (Specialised REITs versus Diversified REITs)
The change in volatility of both Diversified and Specialised REITs is shown in Figure 3
above. The historical monthly returns chart shows some observations of the
Specialised REITs especially in the downside periods between Year 2007 and 2010.
Specialised REITs index has been indeed more volatile than the counterpart
Diversified REITs index.
Table 3 Performance Statistics for REITs – Equal Weighted Monthly Figures
Table 3 (above) displays the average monthly returns, beta and standard deviations
for the Diversified REITs, Specialised REITs, REITs by sectors and FTSE Small Cap Index.
Period (2007 - 2011)
Sector Return Beta St. Dev
Diversified Property REIT Portfolio -0.87% 0.31 7.60%
Specialsed Property REIT Portfolio -0.53% 0.39 7.39%
Office REIT Index -0.58% 0.34 8.01%
Retail REIT Index -0.72% 0.56 9.38%
Industrial REIT Index -0.49% 0.40 10.03%
Healthcare REIT Index -0.19% -0.03 2.09%
Storage REIT Index -0.62% 0.33 10.88%
FTSE Small Cap Index -0.13% 1.00 6.72%
Equal Weighted
Average Monthly
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Note: Warner Estates is removed from the calculation as this is one of the most
extreme outliers with non-normal return data.
The figures provided above are not adjusted by the market capitalisation and
therefore are equal weighted (un-weighted). The figures excluding the extreme
outliers provide a better statistical estimate (Chen & Peiser 1999). Chen & Peiser
suggest that un-weighted figures can be a more effective indicator for comparing the
performance of REITs in different sectors.
Betas for the Specialised REITs are higher than the Diversified counterparts, except
the Healthcare REIT. Most of the REITs betas had a low average – between 0.30 and
0.35, indicating that the correlation between REITs and the FTSE Small Cap Index is
not very strong.
Standard deviations for industrial, retail and storage are very high. The Diversified
REITs performed poorly against the non diversified REITs in this study as the
Diversified REIT had a low return, comparing to all other REITs. This suggests that
the market did not value the diversified REITs as much as they value the more
specialised REITs. This finding is in line with Chen & Peiser’s observation of the
Diversified REITs (1999).
Figure 4 Average Return and Standard Deviation - Diversified versus Specialised REITs
Figure 4 (above) exhibits that the Diversified REITs had a lower average return and a
Diversified REITs
Specialised REITs
FTSE Small Cap Index
-1.00%
-0.90%
-0.80%
-0.70%
-0.60%
-0.50%
-0.40%
-0.30%
-0.20%
-0.10%
0.00%
6.60% 6.70% 6.80% 6.90% 7.00% 7.10% 7.20% 7.30% 7.40% 7.50% 7.60% 7.70%
Average Return and Standard Deviation Jan 07 - Jul 11
Ave
rage
Mo
nth
ly R
etu
rn
Standard Deviation
Average Return and Standard Deviation
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greater volatility than the Specialised REITs. However, the Specialised REITs had a
higher beta than its counterpart REITs and it means that they track the market
performance more closely than its counterpart REITs.
Figure 5 Average Return and Standard Deviation - REITs by Sectors
Figure 5 (above) plots the return/risk position of the REITs by Sectors. It can be
seen that Diversified REITs had the lowest return comparing to all other REITs by
sectors, with a standard deviation sitting in the middle of the range (close to office
REIT and FTSE Small Cap). It is noticed that the Healthcare REIT had a high return
and a lower standard deviation than the rest of the REIT sectors, largely due to high
dividend pay-out.
All REIT sectors show a higher risk than the FTSE Small Cap Index.
Diversified
Healthcare
Industrial
Office
Retail
Storage
FTSE Small Cap Index
-1.00%
-0.90%
-0.80%
-0.70%
-0.60%
-0.50%
-0.40%
-0.30%
-0.20%
-0.10%
0.00%
0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00%
Average Return and Standard Deviation
Average Return and Standard Deviation Jan 07 - Jul 11Standard Deviation
Ave
rage
Mo
nth
ly R
etu
rn
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Figure 6 Average Return and Beta - REITs by Sectors
Figure 6 (above) displays the average returns and betas for the Diversified REITs,
Specialised REITs, the REITs by Sectors, and the FTSE Small Cap Index.
Retail REITs had the highest beta of 0.56, which means they track the market
performance more closely than the Diversified REITs and other REITs by Sectors.
Healthcare REITs had a negative beta and a positive return. It can be seen that
industrial REITs, office REITs and storage REITs scattered relatively closed to each
other, meaning they share a reasonably matched average return and beta figure.
Diversified
Healthcare
Industrial
Office
Retail
Storage
FTSE Small Cap Index
Specialised
-1.00%
-0.90%
-0.80%
-0.70%
-0.60%
-0.50%
-0.40%
-0.30%
-0.20%
-0.10%
0.00%
-0.20 0.00 0.20 0.40 0.60 0.80 1.00 1.20
Average Return and Beta Jan 07 - Jul 11Beta
Ave
rage
Mo
nth
ly R
etu
rn
Average Return and Beta
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Regression Analysis/Results
Last prices and dividend of the individual REIT on monthly basis are extracted from
Bloomberg and are used to derive the monthly returns of the REITs. These monthly
returns are then being input into calculations of Sharpe ratios and other performance
ranking measures (see the later section). Return data are being tested for normality,
heteroskedasticity and autocorrelation.
Table 4 Return Data Tests for Normality, Heteroskedasticity and Autocorrelation
Apart from the absence of the return data of GPG, PC and VNY and a shorter period
return data (less than 3 years) for NRR, the reminder of the REITs show a mixture of
results for normality, White’s test and LM’s test. It appears that the REITs that have
higher leverage (DEBT) ratio also have the non normal return data. By using only
the REITs that pass all three tests, there will be only a handful of REITs for running the
regression. Possibilities of using the nonparametric regression or quantile
regression will be further discussed in the conclusion as a recommendation for
further research.
In this study, the following observations, which were recorded from screening the
characteristics of the sample REITs, will be incorporated in the regression studies.
Ticker3 year
SharpeAge Size Debt EFFGI
Monthly Return for
Normality (JB test)
Heteroskedasticity White's
Test (P-value)
Autocorrelation LM's Test (P-
value)
BYG 0.27 4.55 0.01 0.36 0.00 22.6155 0.5239 0.0894
BLND 1.37 4.55 0.19 0.38 0.00 0.1232 0.6669 0.1835
CSCG -0.44 4.55 0.11 0.52 0.01 2.4746 0.3716 0.7440
DLN 2.77 4.55 0.06 0.38 0.05 19.9018 0.0204 0.0877
GPG na na na na
GPOR 3.07 4.55 0.05 0.27 0.00 2.6877 0.6662 0.2404
HMSO 0.42 4.55 0.12 0.42 0.01 5.0191 0.0718 0.7252
HSTN 1.07 4.55 0.02 0.46 0.01 22.6108 0.0901 0.3105
HCFT 1.02 4.55 0.00 0.01 0.07 26.9570 0.0002 0.0074
LAND 0.31 4.55 0.24 0.38 0.01 0.7501 0.5475 0.1560
LSR 2.72 4.30 0.00 0.61 0.01 3.8404 0.6441 0.4928
LSP 2.86 3.72 0.03 0.20 0.01 14.3907 0.6998 0.7883
MCKS 0.23 4.55 0.00 0.47 0.01 28.2433 0.4254 0.5136
METP na 1.30 0.01 0.00 0.02 1.2092 0.8641 0.0069
MKLW 1.56 4.55 0.01 0.18 0.01 15.8450 0.6124 0.0048
NRR na 1.88 0.00 0.65 0.02 8.6167 0.4303 0.6454
PC na na na na
PHP 5.24 4.55 0.01 0.57 NA 2.2033 0.1739 0.6130
SHB 2.86 4.55 0.05 0.46 0.00 6.6037 0.8384 0.0472
SGRO 0.06 4.55 0.08 0.46 0.01 2.3288 0.3455 0.9575
TCSC 1.46 4.55 0.00 0.51 0.01 18.7239 0.2725 0.1275
WNER -1.82 4.55 0.00 0.59 0.02 100.7816 0.0002 0.7430
WKP 0.92 4.55 0.01 0.52 0.01 11.4372 0.9502 0.0618
VNY na NA na na na
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Table 5 Summary Statistics for Variables
Variables that are to be incorporated in the regression present some features of
interest. The mean Sharpe ratio (for the 3 year period) is 1.37 with six REITs
outperforming the mean Sharpe ratio (see Table 6 below).
Table 6 Sharpe Ratios (3 Year Period)
Secondly, most of the REITs started since the introduction of the REITs regulation in
January 2007. Thirdly, the average total debt / total debt ratio for the UK REITs is
0.41. Half of the REITs in the UK are “Diversified”. Most of the UK REITs invest
locally and only a small number of REITs invest internationally. Lastly, the
management efficiency (EFFGI) is not strongly correlated with the Sharpe ratios,
Variables Mean Max Min Corr p
SHARPE3 1.37 5.24 -1.82
AGE 4.49 4.55 3.72 -0.28 0.25
SIZE 0.05 0.24 0.00 -0.20 0.42
DEBT 0.41 0.61 0.01 -0.09 0.70
EFFGI 0.01 0.07 0.00 0.00 0.70
DIV 0.53 1.00 0.00 -0.09 0.70
OFF 0.11 1.00 0.00 0.06 0.80
RETAIL 0.16 1.00 0.00 -0.03 0.89
IND 0.11 1.00 0.00 -0.18 0.47
HEALTH 0.05 1.00 0.00 0.59 0.01
STORAGE 0.05 1.00 0.00 -0.17 0.50
UK 1.00 1.00 1.00 NA NA
EURO 0.16 1.00 0.00 -0.24 0.33
GLO 0.05 1.00 0.00 0.21 0.38
-3.00
-2.00
-1.00
0.00
1.00
2.00
3.00
4.00
5.00
6.00
3 Year Sharpe Ratios
3 Year Sharpe
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which is contradictory to Morri & Lee’s findings. The accuracy of the data extracted
from Bloomberg is therefore challenged.
Table 7 Regression Results – Sharpe Ratios versus Fund Characteristics
The initial regression model on the left hand side of Table 7 incorporates the 19 REITs
that have the return data longer than three years. This model includes the majority
of the variables allowed (excluding Storage & UK) as restricted by the size of the
sample included. This model is mainly for purpose of illustrating that all possible
regression models are considered and tested. Given that a number of the REITs’
monthly return data fail the normality tests, the model (left) will not likely to capture
the impact that the variables will have on the REITs’ performance. It has been
suggested that Quantile regression will be more robust to deal with large return data
outliers.
A later regression model on the right hand side of Table 7 incorporates only the 8
REITs which their monthly return data pass the normality, heteroskedasticity and
autocorrelation tests. It is understood that a regression model incorporating a
small number of samples faces risks of having biased or inaccurate results or makes
the results not greatly convincing.
A number of the possible regressions (see appendix) has been tested out based on
the later regression model with 8 REIT samples. All fourteen (14) variables are
mixed and tested and a number of variables showing huge errors or excessively high
VIFs, failing t-statistics or being insignificant are eliminated.
Dependent Variable: SHARPE3 Dependent Variable: SHARPE3
Sample: 19 REITs Sample: 8 REITs
Variable Coeff SE T-Stat VIF Variable Coeff SE T-Stat VIF
C 7.612 8.757 0.869 NA C 5.240 1.667 3.144 NA
AGE -1.094 2.012 -0.544 1.41
SIZE -4.290 5.804 -0.739 1.45
DEBT -5.873 3.438 -1.708 2.54
EFFGI -49.774 33.414 -1.490 2.84
DIV 1.411 1.626 0.868 6.34 DIV -4.400 2.041 -2.156 2.81
OFF 1.630 1.730 0.942 2.71 OFF -2.170 2.357 -0.921 1.75
RETAIL 2.260 1.839 1.229 4.32 RETAIL -4.100 2.041 -2.009 2.25
IND 1.550 2.342 0.662 4.96 IND -4.760 3.118 -1.527 3.06
HEALTH 6.519 2.173 3.000 2.26
EURO -0.218 1.531 -0.142 2.99 EURO -0.420 2.041 -0.206 2.25
GLO 3.645 1.873 1.946 1.68
R-squared 0.701 R-squared 0.789
Adjusted R-squared 0.230 Adjusted R-squared 0.261
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The best outcome is displayed in Table 7 with five (5) variables – DIV, OFF, RETAIL,
IND and EURO. An average VIF of 2.43 is achieved, indicating the multicollinearity
problem is being attended and minimised. In addition, the R-squared is 0.789 and
the Adjusted R-squared is 0.261 indicting that these variables individually or
combined are significantly related to the excess return performance.
This outcome suggest that over the last three (3) years, the property type specialised
REITs (namely the Office and Retail Sectors) and regional diversified REITs (namely
the REITs which invest in Germany, France, etc) produce higher risk-adjusted
performance.
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Portfolio Comparison Analysis/Results
The portfolios of the Diversified REITs and the property-type Specialised REITs are
constructed in two ways; first is the value-weighted and the other is equal-weighted.
In this study, only six (6) out of the ten (10) diversified REITs having the yearly break
down of the property-type components are used to construct the Diversified REIT
portfolio. The following pie chart shows the composition of the six (6) Diversified
REITs in terms of the combined market capitalisation.
Figure 7 Compositions of Diversified REITs portfolio - average market cap (2007-2011)
As the figures indicate above, British Land, Land Securities and Hammerson REITs are
larger than the other three REITs included in the portfolio. The performance of the
diversified REITs portfolio will be likely dominated by the three larger REITs on the
value-weighted basis. Ro and Ziobrowski (2009) suggest that to compensate for the
BLND 34.22%
WNER 0.36%
MKLW 1.38%
HCFT 0.20%
LAND 42.36%
HMSO 21.49%
Compositions of diversified REIT portfolio
BLND
WNER
MKLW
HCFT
LAND
HMSO
REIT Name Ticker
2007 - 2011
Average Market
Cap (£m)
Percentage
British Land BLND 4388.44 34.22%
Warner Estate WNER 45.63 0.36%
Mucklow (A & J) Group MKLW 176.76 1.38%
Highcroft Investments HCFT 25.40 0.20%
Land Securities LAND 5432.06 42.36%
Hammerson HMSO 2756.14 21.49%
Total 12824.42 100.00%
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larger REITs in the portfolio, it is recommended to construct the diversified REITs
portfolio on an equal-weighted basis. In that case, then the larger REITs will
become one of the equal components in the portfolio.
The value-weighted specialised REITs portfolio will be constructed and matched to
the property-type proportions of the diversified REITs portfolio shown in the
following chart.
Figure 8 Value-weighted Diversified REITs
Table 8 Value-weighted annual property type diversification proportion on the basis of Diversified REITs
portfolio
Initially, all available diversified REITs are aggregated and weighted by their own
market capitalisation within a portfolio for the calculation of the overall
property-type proportions. The table above shows the property type composition
of the diversified REITs portfolio on a value-weighted basis. The average
proportions of offices and retail dominate nearly 80% of the portfolio.
0.00 1000.00 2000.00 3000.00 4000.00 5000.00 6000.00
BLND
HCFT
HMSO
LAND
MKLW
WNER
Offices
Retail
Industrial
Shopping
Residential
Others
Value Weighted diversified REITs
Panel A: Value Weighted
Year Offices Retail Industrial Shopping Residential Others Total
2007 40% 40% 1% 6% 0% 13% 100%
2008 41% 39% 1% 6% 0% 12% 100%
2009 39% 42% 1% 0% 0% 18% 100%
2010 35% 50% 1% 0% 0% 13% 100%
2011 36% 52% 1% 0% 0% 11% 100%
Mean 37% 46% 1% 2% 0% 14% 100%
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The proportions are then matched to the weight of each property-type specialised
REIT index within the specialised REIT portfolio as shown below.
Figure 9 Specialised REITs portfolio using the overall property type proportions of the value-weighted
Diversified REITs in Table 8
For the comparison, the proportions of the Offices, Retail, Industrial and Others
within the diversified REIT portfolio are 37%, 48%, 1% and 14% respectively. The
specialised REIT will match with the above quoted percentages. Note: Retail and
Shopping Centre components are combined. Residential which is of a smaller
portion will be combined with the “Others”. Others include other specialised REITs
such as Healthcare and Storage REITs.
Ro and Ziobrowski (2009) suggest constructing a specialised REITs portfolio to match
the diversified REITs portfolio on an equal-weighted basis can best eliminate the
disproportionate size effect that the larger REITs have on the results.
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Offices Retail Industrial Shopping Residential Others
Specialised REIT portfolio usign the overall property type %
Offices
Retail
Industrial
Shopping
Residential
Others
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Figure 10 Equal-weighted Diversified REITs
Table 9 Equal-weighted annual property type diversification proportion on the basis of Diversified REITs
portfolio
The table above shows the property type composition of the diversified REITs
portfolio on an equal-weighted basis. Under the equal-weighted basis, the retail
component drops 20% comparing to the value-weighted counterpart (shown in
Figure 9), whilst the industrial component increases to 20%. The office component
stays in a fairly similar level under both the value-weighted and equal-weighted basis.
Note: the residential proportion is very small in the UK instance as the residential
REITs are still not available in the UK stock exchange. This makes the mix of the
portfolios significantly different from the portfolios that Ro & Ziobrowski (2009) and
Benefield et al. (2009) structure, where the residential components are at least 30%.
0 1000 2000 3000 4000 5000
BLND
HCFT
HMSO
LAND
MKLW
WNER
Offices
Retail
Industrial
Shopping
Residential
Others
Equal Weighted diversified REITs
Panel B: Equal Weighted
Year Offices Retail Industrial Shopping Residential Others Total
2007 39% 23% 16% 12% 1% 9% 100%
2008 39% 22% 17% 12% 1% 9% 100%
2009 35% 25% 21% 6% 1% 13% 100%
2010 34% 29% 22% 3% 1% 10% 100%
2011 35% 30% 22% 3% 1% 9% 100%
Mean 36% 26% 20% 7% 1% 10% 100%
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Figure 11 Specialised REITs portfolio using the overall property type proportions of the equal-weighted
Diversified REITs in Table 9
For the comparison, the proportions of the Offices, Retail, Industrial and Others
within the diversified REIT portfolio are 36%, 33%, 20% and 11% respectively. The
same process is then repeated to create a specialised REIT portfolio.
After completing the construction of the specialised REITs portfolios under both
value-weighted and equal-weighted basis, the value-weighted and equal-weighted
specialised REITs index returns are then being input into the efficient frontier models
(monthly return basis) respectively, based on the property-type proportions
calculated earlier.
Table 10 Portfolio Performance Summary
The sample of the returns and standard deviations are all calculated for the time
period commencing January 2007 (ending July 2011), with fifty-three (53) months of
monthly return data.
As the results from the efficient frontier suggest, the performance of the diversified
REITs and specialised REITs under the value-weighted basis is of only a marginal
0%
5%
10%
15%
20%
25%
30%
35%
40%
Offices Retail Industrial Shopping Residential Others
Specialised REIT portfolio usign the overall property type %
Offices
Retail
Industrial
Shopping
Residential
Others
Average
Monthly
Div REIT
Portfolio
Spec REIT
Portfolio
Div REIT
Portfolio
Spec REIT
Portfolio
Mean -0.63% -0.60% -1.21% -0.67%
Std. Dev. 8.36% 7.48% 8.04% 7.63%
Value Weighted Equal Weighted
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difference. At a similar level of the monthly return, the specialised REITs portfolio
produces the return with less volatility.
On the other hand, the specialised REITs portfolio under the equal-weighted
construction produces a better mean return at a similar level of the volatility. This
calculation, however, ignores the leverage element, which in Ro and Ziobrowski’s
view, may potentially bias the findings.
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Treynor & Jensen’s Analysis/Results
Table 11 The Yearly Treynor Ratios & Jensen's Alpha for the UK REITs (Period 2007-2011)
Treynor and Jensen measures, on the other hand, take into account of the
correlation between the market index (FTSE Small Cap index) and the respective
REIT’s return. The table above displays the yearly Treynor ratios and Jensen’s Alpha
for seventeen (17) REITs that have the return data series commencing since January
2007. This includes nice (9) Diversified REITs and eight (8) Specialised REITs.
Ticker Sector Treynor Ratio Jensen's Alpha Avearge Treynor Jensen's
BLND Divr -0.52 0.01 Div -0.42 0.09
DLN Divr 0.07 0.33 Spec -0.36 0.17
HCFT Divr -0.01 0.32 All -0.40 0.13
HMSO Divr -0.20 0.15
LAND Divr -0.52 0.01
MKLW Divr -0.06 -0.21
SHB Divr 0.13 0.21
WKP Divr -0.12 0.52
WNER Divr -2.60 -0.51
PHP Healthcare -1.82 0.04
HSTN Ind 0.01 0.18
SGRO Ind -0.24 0.17
GPOR Offices 0.03 0.26
MCKS Offices -0.51 0.02
CSCG Retail -0.23 0.18
TCSC Retail -0.09 0.36
BYG Storage -0.08 0.16
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Figure 12 Treynor Ratios
Managers have complete control over the property stocks he or she chooses to trade,
buy or sell, despite the controls or restrictions which the senior management may lay
on. If it wasn’t a market related risk, it would then be a managerial problem,
instead (Treynor 1965).
Figure 12 shows that individually the two Diversified REITs – Derwent London and
Shaftsbury have positive ratios (0.07 and 0.13), which are higher than the two
Specialised REITs – Hansteen and Great Poland Estates (0.01 and 0.03).
The average yearly Treynor ratio for all seventeen (17) UK REITs is -0.40 over the
period from January 2007 to July 2011. The average Treynor ratio for the
Specialised REITs is -0.36 and for the Diversified REITs is -0.42. Overall, the
Specialised REITs outperform the Diversified REITs by showing better average fund
managers’ management abilities.
-3.00
-2.50
-2.00
-1.50
-1.00
-0.50
0.00
0.50
Treynor Ratio
Treynor Ratio
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Figure 13 Jensen’ Alphas
Jensen’s alpha examines the forecasting ability of the mutual fund managers, rather
than a portfolio’s efficiency (Jensen 1968). Jensen’s model is a form of capital asset
pricing models and is taking explicit account of the effects of “risk” on the returns of
portfolios. Jensen’s paper highlights the difference a superior forecaster can make
on a managed portfolio.
Figure 13 shows that individually a number of the Diversified REITs (DLN, HCFT, SHB &
WKP) have an alpha of 0.21 and / or higher and a number of the Specialised REITs
(GPOR & TCSC) have an alpha of 0.26 and / or higher. Workspace Group (WKP)
demonstrates the highest Alpha of 0.52 (within the Diversified REITs), whilst Town
Centre Securities (TCSC) shows the highest Alpha of 0.36 (within the Specialised
REITs).
The average Jensen’s Alpha on the seventeen (17) REITs is 0.13 with the average
Alpha on the Diversified REITs being 0.09 and the Specialised REITs being 0.17. In
summary, the Specialised REITs outperform the Diversified REITs by showing better
average fund managers’ forecasting abilities.
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
Jensen's Alpha
Jensen's Alpha
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Conclusion
This study looks at the return and risk characteristics of the Diversified and
Specialised REITs in the UK over the last four and half years commencing January
2007, which experienced the credit crisis and great economy uncertainty. The
twenty-one (21) REITs are screened, assessed and compared on group, individual and
portfolio basis.
The methodologies used in this study incorporate some simple statistic tools
(correlation & index comparison used by Chen & Peiser), multiple factor Sharpe ratio
regression (with some variation and with inspiration of Morri & Lee’s work on Italian
Real Estate Mutual Funds), and portfolio construction and use of efficient frontier
models (with some variation and with great influence from Ro & Ziobrowski).
Initially, the statistical finding indicates that the FTSE EPRA/NAREIT UK REIT Index
perform more closely to FTSE Small Cap Index with a positive correlation of 0.83.
The correlation statistics show that the Specialised REITs perform more closely and
share more systematic risk with the FTSE Small Cap Index, with a positive correlation
of 0.71.
In terms of the change in volatility of the both Diversified and Specialised REITs (as
shown in Figure 3), the historical monthly returns chart shows some observations of
the Specialised REITs especially in the downside periods between Year 2007 and 2010.
Specialised REITs index has been indeed more volatile than the counterpart
Diversified REITs index.
The Diversified REITs perform poorly against the non diversified REITs in this study as
the Diversified REIT had a low return, comparing to all other REITs. This suggests
that the market did not value the diversified REITs as much as they value the more
specialised REITs.
The multiple factor Sharpe ratio regression suggests that over the last three (3) years,
the property-type specialised REITs (namely the Office and Retail Sectors) and
regional diversified REITs (namely the REITs which invest in Germany, France, etc)
produce higher risk-adjusted performance.
Subsequently, the results from the portfolio comparison and efficient frontier models
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suggest that the performance of the Diversified REITs and Specialised REITs under the
value-weighted basis is of only a marginal difference. At a similar level of the
monthly return, the specialised REITs portfolio produces the return with a marginally
lesser volatility.
On the other hand, the specialised REITs portfolio under the equal-weighted
portfolio construction produces a better mean return at a similar level of the
volatility.
In terms of the Treynor ratio ranking methodology, the Specialised REITs, overall,
outperform the Diversified REITs by showing better average fund managers’
management abilities. However, it is worth noting that individually Derwent
London and Shaftsbury have highest positive ratios (0.07 and 0.13) among all other
individual REITs.
In terms of the Jensen’s Alpha ranking methodology, the Specialised REITs
outperform the Diversified REITs by displaying better average fund managers’
forecasting abilities. As a note, Workspace Group (WKP) demonstrates the highest
Alpha of 0.52 (within the Diversified REITs), whilst Town Centre Securities (TCSC)
shows the highest Alpha of 0.36 (within the Specialised REITs).
In conclusion, the hypothesis that the Specialised REITs can perform better than the
Diversified counterpart during the credit crunch is supported. The Diversified REITs
show a moderate return with lower level of volatility. However, the Specialised
REITs track the market more closely. The Office REITs and Retail REITs produce
significant impact on the risk-adjusted performance. The Specialised REITs portfolio
under the equal-weighted portfolio construction produces a better mean return at a
similar level of the volatility, than the Diversified REITs portfolio.
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Limitation and Future Research
One of the shortcomings of the study on the performance of the UK REITs is the short
return data trend. Majority of the REITs commenced since January 1st, 2007 which
leave only 53 observation months of monthly return data for the analysis. This
opens a window of opportunity for further research incorporating the return data of
the same securities (prior to becoming the UK REITs) into the regression models and
portfolio analysis. This may offer the investors and practitioners an in-depth
understanding of the performance of REITs before and after becoming REITs.
Having a longer time period return trend also allows the study of the performance
into multiple sub periods by the use of Chow test (structural break, see Benefield et
al.).
Another shortcoming of the study is the fact of having relatively small number of the
REITs. There are twenty-one (21) REITs that Bloomberg provides monthly return
data trend. However, given the requirement of the normality test and other
statistical restriction, there are only eight (8) REITs that can be incorporated into a
multiple factor Sharpe ratio regression. This opens a window of opportunity for
carrying out the regression testing in the nonparametric format or quantile
regression format.
The multiple factor Sharpe ratio regression can be further improved by adopting
variables such as the fund management efficiency, property management efficiency
and the portfolio herfindahl indices for property typologies and locations. The
efficiency (EFFGI) variable calculated from the Bloomberg database show a great
standard error and a weak correlation with the Sharpe ratios, indicating that the
validity of the data is questionable. It is advisable that the future researchers can
get in touch with the fund managers of the REITs directly and obtain the most
accurate efficiency data for the similar regression testing.
Words: 10,191
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Appendix
1. Regression Simulations
19 REIT Samples
8 REIT Samples
2. Portfolio Comparison
Tables
Value-weighted
Equal-weighted
3. CD Containing All Excel and Eview 7 files
Method 1-Diversified versus Specialised Indices
Method 1-Performance Statistics for individual REITs
Method 2-Regression Models with Dividend (and Results)
Method 2-REIT Monthly Sharpe, Treynor and Jensen’s Alpha
Method 3-Diversified REITs – Property Type Components Value vs Equal
Method 3-Portfolio Construction Spec. Value & Equal
Method 3-Specialised 4x Funds Value versus Equal Weighted
Method 3-Specialised 4x Optimised Portfolio
Eview 7 files
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Regression Simulations
19 REIT Samples
8 REIT Samples
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Portfolio Comparison
Tables
Value-weighted
Equal-weighted
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CD Containing All Excel and Eview 7 files
Method 1-Diversified versus Specialised Indices
Method 1-Performance Statistics for individual REITs
Method 2-Regression Models with Dividend (and Results)
Method 2-REIT Monthly Sharpe, Treynor and Jensen’s Alpha
Method 3-Diversified REITs – Property Type Components Value vs Equal
Method 3-Portfolio Construction Spec. Value & Equal
Method 3-Specialised 4x Funds Value versus Equal Weighted
Method 3-Specialised 4x Optimised Portfolio
Eview 7 files