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THINK Global: Risk and return
Changing context of real estate returns in a globalised world
Data generating art
This document is solely for the use of professionals and is not for general public distribution.
Using data from Fig.1 in this report, the image is an abstract
representation of market size and aggregated property risk
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Introduction: The need for a global risk benchmarking in real estate
Risk comparability across the globe is the objective for the
TH Real Estate Global Risk Model and the content of this
report. It covers markets in Europe, Asia and North America
to benchmark real estate risk against expected performance.
The model provides a method to understand real estate
investment opportunities globally.
We analyse risk as local as possible, usually on the smallest
level – the city market. Fig.1 provides an example of the type
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Fig.1: Risk and market size
9
8
Shenzhen
Shanghai
7
Risk premium
Real estate has become a globalised asset class. For an
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global perspective is a paradigm change. Traditionally, risks
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can also inform risk management and allocation strategies.
Budapest
Osaka
Madrid
Oslo
6
Dublin
Brussels
Milano
5
4
Sydney
3
Tokyo
Amsterdam Berlin
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Hamburg
Lyon
Munich
Manchester
Seattle
Dallas-Fort Worth
Melbourne
Chicago Washington, DC
0
Paris
1HZ<RUN
London
25,000
50,000
75,000
100,000
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Source: TH Real Estate Risk Model, JLL, 2015
THINK Global: Risk and return
2
Our rational: Measuring global real estate with the same yardstick
To address the need of a rapid globalising industry, global
benchmarks and market comparisons across continents are
paramount in steering decision making. TH Real Estate has
analysed more than 2,000 data points to create a global risk
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retail and industrial sectors.
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that calculates real estate risk premiums over and above the
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volatility, income security and transparency.
Central
London
Seattle
Chicago
Miami
Stockholm
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targets for each market. The results highlight stark differences
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premium (eg. US and core Europe), and the nascent markets
characterised by much higher real estate risk (eg. China).
Oslo
Brussel
Amsterdam
Paris
Dallas
Zürich
Washington, DC
Milano
Dublin
Boston
München
Helsinki
Düsseldorf
Frankfurt
am Main
Praha
Madrid
:DUV]DZD
Perth
Brisbane
Houston
Kuala
Lumpur
Lisboa
Budapest
Guangzhou
Shenzhen
San
Francisco
Berlin
Shanghai
Osaka
Seoul
Beijing
Københaun Nagoya
Hamburg
Wien
Melbourne
Los Angeles
Sydney
Tokyo
/RZ
High
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Source: TH Real Estate, 2015
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THINK Global: Risk and return
3
Our method: The building blocks of risk
The model has been designed to assess the relative riskadjusted returns across selected global real estate markets.
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free interest rate, country real estate transparency, local
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relative to the global traded sector, local market volatility of
returns, and income security generated by lease terms and
international corporate presence.
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sector expected return in order to compensate for the risk.
It is important not to be too prescriptive, as the estimated
parameters set for the individual building blocks for real estate
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incorporate value judgements about risk premium; the
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market risk relativities.
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recalibrate the risk premium accordingly. The risk model is
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countries and sectors, and in providing market risk rankings
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Liquidity
Transparency
The ability to sell at any point in the real estate cycle is the
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Model. There are only a handful of markets that remained
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facing severe challenges at the time.
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culture, the level of transparency of the real estate operating
environment becomes a key risk element. Decision making at
a local authority level and availability of market information
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V
global real estate Transparency Index.
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the length of time that a property is introduced to the market
until completion of a deal, and comparing the length of the
sale process across markets. This information has been
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We have decided to use a transaction volume based approach
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market share. We have done this analysis on a sector level.
Within our risk model, the UK
is leading the transparency
rankings, and Chinese and
Malaysian cities are the most
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the other end of the spectrum,
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are struggling markets like
Athens and emerging markets
such as Kuala Lumpur.
THINK Global: Risk and return
4
Our method: The building blocks of risk (continued)
Income security
Volatility
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also a key element for investors. We have captured income
security in a global comparison of standard lease length as
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perspective of a global investor, the availability of multinational
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generally preferred to smaller, local occupiers, based on their
usually higher covenants strengths.
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a fourth cornerstone of our Global Risk Model is the
measurement of volatility of income.
The UK and the US have the
best combination of long lease
length structure and a high
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good covenant structure. China
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Japanese second tier cities are
performing among the bottom.
Cities such as Washington, DC,
or German cities are typically
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scoring ahead of places like
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higher volatility.
This is an especially interesting indicator, since some of the
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receive a higher risk premium on this score.
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15
12
9
6
3
Malaysia
China
Hungary
Singapore
Poland
Portugal
Hong Kong
South Korea
Spain
Norway
Italy
Czech Republic
Luxembourg
Ireland
Volatility
Denmark
Austria
Finland
/LTXLGLW\
Belgium
Australia
Switzerland
Transparency
Sweden
Netherlands
United States
Japan
Key
Bond yield
United Kingdom
France
Germany
0
Income security
Source: TH Real Estate Risk Model, 2015
THINK Global: Risk and return
5
Global results
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America
Europe
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of good convened tenants, and a high market transparency,
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The three core markets - France, Germany and the UK - are
the centre of European commercial activity and also the three
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than the others.
Australia scores ahead of its neighbours, due to a transparent
market and high density of international corporates being
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relative high trading volumes. An obstacle for Japan is still the
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compared to other mature markets.
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Tour Areva, Paris
699 Bourke Street, Melbourne
THINK Global: Risk and return
7
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Key
/RZ
/RZWRPHGLXP
Medium
Medium to high
High
Source: TH Real Estate Risk Model, 2015
THINK Global: Risk and return
8
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America
Europe
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global average, due to the typically long holding periods
of REITs.
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in a relatively high risk premium. Portugal, particularly,
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recorded transactions.
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centres, and Malaysia remains the riskiest of the markets
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the market size is limited, and not as many international
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Ala Moana Center, Honolulu
Bullring, Birmingham
China is found in the higher risk category, despite a large
number of international retailers operating in China.
Florentia Village Jingjin, Beijing
THINK Global: Risk and return
9
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Key
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Medium
Medium to high
High
Source: TH Real Estate Risk Model, 2015
THINK Global: Risk and return
10
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The key application of the risk model is the comparison to expected returns. Current market conditions, such as bond yields and
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example of the industrial sector, highlighting selective opportunities based on the risk model. This result has to be interpreted in the
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reference point for global comparison purposes.
America
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high
high
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in terms of volumes of trade. In recent years, expected total
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Europe
Returns
Europe is looking exceptionally positive on this measure.
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It is only China and Singapore that have expected return
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Singapore
China
Hong Kong
Greece
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United States
Japan
Australia
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Poland
United Kingdom
Volatility premium
Income security premium
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Austria
Belgium
Germany
Portugal
Luxembourg
Hungary
Finland
Netherlands
Denmark
Czech Republic
Key
Transparency premium
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France
Italy
Spain
Ireland
ORZ
Bond yield
Expected return
Source: TH Real Estate, 2015
THINK Global: Risk and return
11
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Key
Outperformance
Outperformance likely
Risks covered
Possibility of underperformance
Underperformance
Source: TH Real Estate Risk Model, 2015
THINK Global: Risk and return
12
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other markets, including those in Southern Europe, offer better risk-adjusted returns. The previous section describing the opportunity
gap in the industrial sector is a good example.
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targeting optimal risk-adjusted returns for investors.
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makes market risk transparent and ensures consistency across
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Torsten Steiner
Research Analyst
THINK Global: Risk and return
13
Contact us
Torsten Steiner
Research Analyst
T: +442037278248
(WRUVWHQVWHLQHU#WKUHDOHVWDWHFRP
[email protected]
threalestate.com
@THRealEstate14
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