european real estate society 20 th annual conference vienna, austria july 3-6, 2013
DESCRIPTION
Masaki Mori Seow Eng Ong Joseph T. L. Ooi. Do investors pay attention to rare disaster risk? Evidence from earthquake risk in Japanese real estate investment trust market. European Real Estate Society 20 th Annual Conference Vienna, Austria July 3-6, 2013. Data & Methods. Results. - PowerPoint PPT PresentationTRANSCRIPT
DO INVESTORS PAY ATTENTION TO RARE DISASTER RISK?
EVIDENCE FROM EARTHQUAKE RISK IN JAPANESE REAL ESTATE
INVESTMENT TRUST MARKET
European Real Estate Society 20th Annual ConferenceVienna, AustriaJuly 3-6, 2013
Masaki MoriSeow Eng OngJoseph T. L. Ooi
050
100
150
abov
e_4
-.2-.1
0.1
.2JR
EIT
inde
x re
turn
2004m12005m12006m12007m12008m12009m12010m12011m12012m1
JREIT index return above_4
Background
2
Research Framework
Data & Methods Results ConclusionsIntroduction
Mid Niigata Prefecture
Earthquake, 2004
Great East Japan Earthquake, 2011
05
1015
20ab
ove_
4
-.2-.1
0.1
.2JR
EIT
inde
x re
turn
2004m12005m12006m12007m12008m12009m12010m12011m12012m1
JREIT index return above_4
Background (without extremes)
3
Research Framework
Data & Methods Results ConclusionsIntroduction
Research Framework
Data & Methods Results ConclusionsIntroduction
Research question Does earthquake risk perception affect return
of J-REIT stocks?
Do investors alter their attention allocation once earthquake events provoke their fear and awareness toward earthquake?
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Research Framework
Data & Methods Results ConclusionsIntroduction
Motivation from finance literature
Rare events and asset pricing A small probability of very bad things happening
affects asset pricing dynamics (e.g., Rietz, 1988 and Barro, 2005)
Limited attention Investors show limited attention to relevant
information Investors shift attention when faced with greater
uncertainty (e.g., Hirshleifer and Teoh, 2003)
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Research Framework
Data & Methods Results ConclusionsIntroduction
Why earthquake risk? Unpredictable, exogenous, and immediate
6(Japan Meteorological Agency)
Year/Seismic
intensity5+ 6- 6+ 7 Total
2004 11 2 2 1 16 2005 5 2 0 0 7 2006 0 0 0 0 0 2007 2 1 2 0 5 2008 0 1 1 0 2 2009 0 1 0 0 1 2010 0 0 0 0 0 2011 17 4 4 1 26 Total 36 16 10 2 64
Research Framework
Data & Methods Results ConclusionsIntroduction
Why J-REITs? Portfolio level earthquake resistance measure
in semi-annual financial reports (PML: Probable Maximum Loss)
Price informationWe can examine dynamic effects of earthquake
event on prices
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Research Framework
Data & Methods Results ConclusionsIntroduction
Contributions Implications for limited attention finance
literature Hopefully, will shed new light on the impacts of investors’ limited
attention and attention allocation on asset price dynamics
Implications for REIT marketsHow earthquake risk is priced in REITsREIT markets are being developed in some
earthquake prone countries
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Data Study period from Jan. 2004 to Apr. 2012
Earthquake event data from the Japan Meteorological Agency
43 REITs Price data from DataStream and Association
for Real Estate Securitization in JapanPML and financial information from REIT DB
and semi-annual financial reports9
Research Framework
Data & Methods Results ConclusionsIntroduction
Methods Outlier Robust regression (MM-estimation)
Dependent variable○ J-REIT Index total return
Independent variable○ # of earthquake equal to or greater than 5 strong in a month (log)
○ Google score as a robustness check
Sub portfolio analysis (1: low 2: middle 3: high)PML scoreFinancial institution ownershipForeign investor ownership 10
Research Framework
Data & Methods Results ConclusionsIntroduction
Methods Event study
Earthquakes in Japan from Jan. 2004 to April. 2012○ “LARGE” --- 5-strong (26) and 6-weak (9)○ “HUGE” --- 6-strong (3) and 7 (2)
Estimation period = -60 to -30 days Event window = 0 to +10 days Robust test
Abnormal return serial correlationEvent-induced volatility (Kolari & Pynnonen, 2010)
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Research Framework
Data & Methods Results ConclusionsIntroduction
Panel A:Overall J-REIT index (PML: 5.46)
Estimate z -valueConstant 0.015 2.65# of earthquakes -0.019 -2.36 **
Panel B:Low PML portfolio (safe: 2.96) High PML portfolio (dangerous: 8.36)
Estimate z -value Estimate z -valueConstant 0.014 2.27 Constant 0.005 0.67# of earthquakes -0.018 -2.23 ** # of earthquakes -0.010 -1.21
Total return vs. # of quakes
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Research Framework
Data & Methods Results ConclusionsIntroduction
***, **, *, for 1%, 5%, and 10% significance, respectively
Panel C:Low financial (28%) High financial (62%)
Estimate z -value Estimate z -valueConstant -0.002 -0.35 Constant 0.014 2.82# of earthquakes -0.003 -0.32 # of earthquakes -0.021 -2.18 **
Low foreign (11%) High foreign (37%)
Estimate z -value Estimate z -valueConstant 0.013 1.91 Constant 0.002 0.27# of earthquakes -0.014 -1.41 # of earthquakes -0.009 -1.25
Total return vs. # of quakes
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Research Framework
Data & Methods Results ConclusionsIntroduction
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Research Framework
Data & Methods Results ConclusionsIntroduction
Daily abnormal return
Reaction • Gradual price drop from day 2
• Moderate size
• Immediate price drop on day 0 and day 1
• Large size
Recovery • Very slow• Not significant
• Quick from Day 2• Significant
<Large earthquakes (35)> <Huge earthquakes (5)>
Coef. t Coef. trank_pml rank_pml2 0.007 1.05 2 -0.005 -1.003 -0.007 -1.01 3 -0.011 -2.06 **
rank_fin rank_foreign2 -0.007 -1.09 2 -0.002 -0.243 -0.007 -1.04 3 -0.001 -0.21
rank_pml#rank_fin rank_pml#rank_foreign2 2 -0.004 -0.50 2 2 0.009 1.082 3 -0.011 -1.28 2 3 0.026 3.19 ***
3 2 0.008 0.86 3 2 0.008 0.893 3 -0.001 -0.07 3 3 0.018 2.26 **
_cons 0.069 12.76 _cons 0.064 17.34
PML x Fin PML x Foreign
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Research Framework
Data & Methods Results ConclusionsIntroduction
Range of cumulative abnormal return <5+ and 6->
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Research Framework
Data & Methods Results ConclusionsIntroduction
Range of cumulative abnormal return <6+ and 7>
Coef. t Coef. trank_pml rank_pml2 -0.009 -0.42 2 -0.026 -1.553 -0.020 -0.96 3 -0.015 -0.84
rank_fin rank_foreign2 -0.027 -1.28 2 -0.016 -0.883 -0.030 -1.49 3 -0.015 -0.92
rank_pml#rank_fin rank_pml#rank_foreign2 2 0.000 0.01 2 2 0.037 1.482 3 0.003 0.10 2 3 0.049 2.00 **
3 2 0.035 1.28 3 2 0.034 1.293 3 0.029 1.07 3 3 0.030 1.25_cons 0.107 6.15 _cons 0.092 8.43
PML x Fin PML x Foreign
Summary of results Sensitivity of REIT return to gradual change in earthquake
risk perception is high Low PMLHigh financial institution ownership
Rational price reaction after “large” earthquakes
Panic reaction after “huge” earthquakes
Sensitivity of REIT return to quick change in earthquake risk perception is highHigh PMLHigh foreign investor ownership
Research Framework
Data & Methods Results ConclusionsIntroduction
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Implications Probability of rare events happening affects
asset pricing dynamics
Investors shift attention allocation to rare event risk
Different types of investors show different processes of attention allocation to rare event risk
Research Framework
Data & Methods Results ConclusionsIntroduction
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Directions for future research Longer-term effects of huge earthquakes
Demand of tenantsAcquisition/disposition of properties by REITs
Impacts of financial institution ownershipWhy do they respond more slowly than foreign
investors?
Research Framework
Data & Methods Results ConclusionsIntroduction
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