Download ppt - Global Real Estate Markets Cycles and Fundamentals

Yale School of Management

Global Real Estate Markets Cycles and Fundamentals

Bradford Case

William Goetzmann

K. Geert Rouwenhorst


Pension Plans and Real Estate

“Pension-plan investment in real estate is extremely limited and much smaller than one would expect based on most mean-variance models” – Ciochetti et al. (1999)

Target based on MV models: 15-20%Actual allocation: 3-4%


Arguments for Real Estate

Low correlation with other asset classes Stocks and Bonds (Titman and Quan, 1999)

Regional Diversification (Goetzmann and Ibbotson 1990)

International Diversification (Eichholz 1996, Eichholz and Harzell,

1996), Liu and Mei, 1998, and others)

Relatively high average return Goetzmann and Ibbotson (1990),

Provides a good hedge against inflation Goetzmann and Ibbotson (1990), Titman and Quan (1999), Anari and Kolari (2002)


Forms of Real Estate Investment

Direct holdings in properties Office Industrial Residential

Investment though REITS – stock market


Direct Investment versus Property Shares

Returns on direct investment difficult to measure due to: Appraisals Taxes Transactions Costs

By comparison, share price data: Behavioral biases


Real Estate Market Integration

Real estate is spacially immobile Expect regional factors to predominate Evidenced by diversification benefits

1991-1992: “Global” real estate crash Important common component to real estate

returns


Global versus local factors

Separate global from local factors in real estate returns

Are national real estate markets correlated through a global or local GDP factor?

Role for Shiller’s “macro futures”?


Preview

World real estate markets are correlated through common GDP effects

A global real estate portfolio is a bet on trends in global production

After controlling for global GDP, local effects are generally small.


Data

International Commercial Property Associates Yields and cap-rates Approximate effective rents

Prime industrial, office, and retail real estate in 22 cities around the world,1987-1997

Converted to U.S. real dollars


Total Returns

Y = going in cap rateR = effective rentAssumes perpetuity formula holds


A Decent Approximation?

U.S. Industrial property; .84 correlation to NCREIF

U.S. Office .54 correlation to NCREIFLittle correlation to NAREITAn instrument for appraisal index


Time

Return Values

Dec1987

Dec1997

Dec1987

Dec1988

Dec1989

Dec1990

Dec1991

Dec1992

Dec1993

Dec1994

Dec1995

Dec1996

0.00

-0.62

1.48

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

0.00

-0.20

-0.40

Australia I Belgium I Denmark I Finland I France I G-Dusseldorf I G-Frankfurt I HongKong IIreland I Italy I Malaysia I Netherlands I Portugal I Singapore I Spain I Sweden ISwitzerland I Thailand I UnKingdom I USA I Australia O Belgium O Canada O Denmark OFinland O France O G-Dusseldorf O G-Frankfurt O HongKong O Ireland O Italy O Japan OMalaysia O Netherlands O Portugal O Singapore O Spain O Sweden O Switzerland O Thailand OUnKingdom O USA O Australia R Belgium R Denmark R Finland R France R G-Dusseldorf RG-Frankfurt R HongKong R Ireland R Italy R Netherlands R Portugal R Singapore R Spain RSweden R Switzerland R Thailand R UnKingdom R

F i g u r e 1: A n n u a l R e t u r n s F o r a l l M a r k e t s a n d P r o p e r t y T y p e s : 1 9 8 7 - 1 9 9 7


Time

Return Values

Dec1987

Dec1997

Dec1987

Dec1988

Dec1989

Dec1990

Dec1991

Dec1992

Dec1993

Dec1994

Dec1995

Dec1996

0.00

-0.36

0.34

0.00

0.04

0.08

0.12

0.16

0.20

0.24

0.28

0.00

-0.04

-0.08

-0.12

-0.16

-0.20

-0.24

-0.28

-0.32

Australia G Belgium G Canada G Denmark G Finland G France G Germany G HongKong G Ireland GItaly G Japan G Malaysia G Netherlands G Portugal G Singapore G Spain G Sweden G Switzerland GThailand G UnKingdom G USA G

Figure 1: Dollar-Denominated changes in GDP deflated by the U.S. CPI, 1987 - 1997


CorrelationTest

Test 1: Remove own GDP effect via regression. Examine change in avg. correlation

Test 2: Remove global EW GDP effect via regression. Examine change in average correlation

GDP factor = real $-valued percent change in annual GDP


Removing GDP factors

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

Industrial Office Retail

Return correlation

Residual correlation,removing own GDPfactorResidual corelation,removing EW worldGDP factor


Global vs. Local Factors

R2 from TS regression on global vs. local & global (Chow test)

Ratio: R2/global R2 Measures incremental value of local over

globalWhat countries are driven by local GDP


Local Factor Variance Ratio

0.01

0.1

1

10

100

Australia

Belgium

Canada

Denmark

Finland

France

G-Dusseldorf

G-Frankfurt

Hong K

ong

Ireland

ItalyJapan

Malaysia

Netherlands

Portugal

Singapore

Spain

Sweden

Switzerland

Thailand

UK USA

Industrial

Office

Retail


Time-Series Regressions

Country-by-country regressions GDP change, lagged GDP change and lagged return Contemporaneous GDP factor significant

U.S. regression three lags of GDP change three lags of returns Current GDP and lag-2 value significant


Diversification

Average percentage risk reduction by adding countries to portfolio

Benefits to real estate diversification similar to equity markets

Industrial has greatest benefitOffice has least benefit


10 20

40

60

80

10

0

Benefits of Global Diversification in Real Estate by Property-Type

IndustrialOfficeRetailStock Markets


GDP-Hedged Diversification

How well does international diversification work if you could hedge GDP risk?

Diversification limits: Unhedged: 29.8%. (70.2% reduction) Hedged against GDP risk: 8.6%. (>90%

reduction)

Robert Shiller: “Macro Markets”


5 10 15 20

20

40

60

80

10

0Diversification Benefits for Unhedged and GDP-Hedged Industrial Real Estate

UnhedgedHedged


Conclusions

Cross-border correlations of real estate captured by common exposure to world GDP

Real estate is fundamentally local, but its covariance is global