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The Behaviours of Flippers, Rental Investors and
Owner-occupiers in the Singapore Private
Housing Market
TU Yong, ZHANG Yanjiang & DENG Yongheng (2016)
Presenter: ZHANG Yanjiang
Prepared for ERES
NUS
Department of Real Estate
School of Design and Environment
Structure
1|
New Source of Fluctuation: flippers trigger the market up but not down.
Investors?
Owner-occupier
Market Fundamental:
GDP, Income, Employment, etc.
1) The existence of flippers makes occupiers pay high
prices;
Contagion effect:
Positive feedback
2) Facing with flippers’ realized return, occupiers pay
higher prices;
Panic, expectation, more eager to buy
Flippers;
Motivation and Significance
2|

Literature Gap

1. Literature explaining mispricing ignore the interaction between
different trading patterns (Fama, 1965; Gromb & Vayanos, 2010; Rubinstein & Wolinsky,
1987; De Long, Shleifer, Summers & Waldmann, 1990, et al.);

2. Overlooks the difference between housing and financial market (Fu,
Qian & Yeung, 2013; Fu & Qian, 2014; Bayer, Geissler & Roberts, 2013; et al.);

a) housing market is highly illiquid with high transaction costs;

b) financial market only has investors but housing market has owneroccupiers, rental investors and flippers;
Motivation and Significance
3|

Empirical Anomaly

3. Flippers (as in Fu, Qian & Yeung, 2013; Fu & Qian, 2014) takes tiny portion (10% in
Singapore) of market but influence the whole market.


4. Flippers more experienced than the rest, more likely to take good trading
patterns (arbitrageur and intermediary) rather than the bad ones (positive
feedback);
Significance: New understanding on housing market; Policy
implications.
Research problems and research questions
4|

Research Problem (argument)
Housing flippers are better informed than rental investors who out-perform owneroccupiers, and flippers lead owner-occupiers who adopt momentum trading
pattern.
Since owner-occupiers are the dominant market participants, their momentum
behaviours triggered by flippers finally add to the market over fluctuation.
Research problems and research questions
5|

Research Questions

Research Question 1: Are flippers the “smartest”, while rental
investors outperform the owner-occupiers in terms of buying at a
discount and selling at a premium?

Research Question 2: During different stages market cycles, how do
flippers lead a housing market to mispricing and what are the roles
of rental investors and owner-occupiers in the formation of housing
market fluctuations?

Research Question 3: What is the positive feedback process in
housing market?
Data and Identification
6|

1. Comprehensive Singapore Private housing transaction data:
covering 2006Q1-2013Q4;

2. Identification of different participants:



Flipper: Buy and sell within a short time (1 year)
Rental investor: buy and sublet within 1 year;
Owner-occupier: hold the property for more than 1 year (after TOP);
No.
1
2
3
Full Address
1 ESSEX * #**-02
1 ESSEX * #**-02
1 ESSEX * #**-02
Rent/Sale Type of Sale
Sale
NEW SALE
Sale
SUB SALE
Rent
TOP
2006
2006
2006
Contract date
8/29/2003
9/25/2006
12/26/2007
4
5
6
1 ESSEX * #**-02
1 ESSEX * #**-02
1 ESSEX * #**-02
Rent
Sale
Rent
2006
2006
2006
8
1 ESSEX * #**-02
Sale
2006
RESALE
Identi Buyer
Flipper
Rental Investor
Identi Seller
N.A.
Flipper
12/16/2008
9/28/2009
1/4/2010
Rental Investor
Rental Investor
6/18/2010
Owner Occupier
Rental Investor
Empirical Design
7|

For Research Question 1: Smartness of 3 participants


Hedonic method with dummies representing the transaction is by Flipper, Rental
investor, or owner-occupiers (omitted as base): both supply and demand sides.
For Research Question 2: Flipper’s leadership

Construct the monthly buying or selling volumes of different participants within
each project, and use Poisson Dynamic Generalized Methods of Moments (GMM)
model (Hausman, Hall & Griliches, 1984; Windmeijer, 2006; Cameron & Trivedi 2013;);
An example:
Voccupier _ bit  exp( 1Voccupier _ bit 1  2Voccupier _ bit 2  3Voccupier _ bit 3  4Voccupier _ bit 4
 1Vflip _ bit 1   2Vflip _ bit  2  3Vflip _ bit 3   4Vflip _ bit  4
 Pit' * δ  GDPt  Coni )   it
Empirical Design
8|



For Research Question 3: Positive feedback process (De Long, Shleifer,
Summers & Waldmann, 1990)
1) Owner-occupiers’ buying to flippers’ selling: Poisson dynamic GMM
method.
2) Owner-occupiers’ buying prices in responses to flippers’ realized
return rate: Hedonic method
ln( priceojit )  Con ji  1Flip _ Realized _ Rit
 1Size jit   2 Size _ sq jit  3 Floorjit   4 Floor _ sq jit  5 Property Tenure jit
  6 Property Type jit   7 Property Age jit  D'jit * θ   ji
Note: Also Exam the responses of rental investors and flippers in terms of their buying prices
Empirical Results
9|
For Research Q1: Flippers are the smartest while rental investors

outperform the owner-occupiers.
•
At demand side
Dependent VARIABLE: ln(Price)
Presale Market
Whole Period
Rinvest_b
Flip_b
06Q1-13Q4
-0.0105***
(0.00131)
-0.0316***
(0.00145)
Booming
Bust
Booming & Policy
06Q1-07Q4
-0.00666***
(0.00225)
-0.0273***
(0.00208)
08Q1-08Q4
-0.0115***
(0.00408)
-0.0243***
(0.00419)
09Q1-13Q4
-0.00930***
(0.00159)
-0.0232***
(0.002)
0.00133
-0.0178***
(0.003)
(0.00454)
-0.0424***
-0.0508***
(0.00328)
(0.0114)
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
-0.00858***
(0.00108)
-0.0213***
(0.00389)
Resale Market
Rinvest_b
Flip_b
•
-0.00665***
(0.00112)
-0.0294***
(0.00254)
Consistent results at supply side
Empirical Results
10 |

For Research Q2: Flippers lead the buying of owner-occupiers and
rental investors but not selling.
Booming Period
Bust Period
Panel A: Relative roles when buying
Flippers
Occupier
Rental Investor
Occupier
Rental Investor
+
+
++
+
++
Occupier
Rental Investor
Occupier
Rental Investor
Rental investors
Panel B: Relative roles when selling
Flippers
--
-
Rental investors
Note: "+" indicates positive effects and "-" is negative; number of "+" or "-" indicates the scale of the influence,
e.g. the strength of "+ +" is stronger than "+"; No sign means no influences.
Empirical Results
11 |

For Research Q3: Owner-occupiers take positive feedback pattern
following flippers during the booming period, but not in the bust period.

1) During the booming period, the selling of flippers triggers the buying of owneroccupiers.
Dependent VARIABLE: Voccupier_b
Booming Period: 2006Q1-2007Q4
Bust Period: 2008Q1-2008Q4
Vflip_s-1
0.1378488
0.0059915
Vflip_s-2
0.2375498***
-0.0749738**
Vflip_s-3
-0.3987605*
-0.047311*
Vflip_s-4
-0.2794386***
-0.013795
*** p<0.01, ** p<0.05, * p<0.1

2) During the booming period, owner-occupiers would pay a higher price facing
with flippers’ higher realized return.
Dependent VARIABLE: ln(Price), the purchasing price of the three participants
Booming Period: 2006Q1-2007Q4
Bust Period: 2008Q1-2008Q4
(1)
(2)
(3)
(4)
(5)
(6)
Occupier
R_Investor
Flipper
Occupier
R_Investor
Flipper
Flippers' Return
0.0227***
0.00392
-0.00246
0.00218 -0.0746*** -0.00352
Rate
*** p<0.01, ** p<0.05, * p<0.1
Summary of market fluctuation
12|
Given the economic fundamentals controlled:

Flippers lead the positive-feedback trading of owner-occupiers during the booming
period;

Flippers lead the market high but do not beat the market down.
Thank You!
ZHANG YANJIANG
Ph.D. candidate in Real Estate
Email: [email protected]
NUS
Department of Real Estate
School of Design and Environment
Motivation and Significance

The interaction
Informed or
experienced Investors
(or flippers, etc.)
“Good” trading patterns:
arbitrage and intermediary
Trade towards
fundamental: Stabilize
market
Interaction between the two
is ignored
Non-Informed investors
(non-flippers, noise
traders, etc.)
“Bad” trading patterns:
positive feedback or
momentum
Trade away from
fundamental:
Destabilize market
Back
Motivation and Significance

3. Overlooks the difference between housing and financial market
financial market only has investors but housing market has owner-occupiers, rental investors and
flippers, holding different motivations;
Trading Motivation
Decision Making
Trading Pattern
Role in Market
Flippers
Rental Investors
Owner-occupiers
Short-term capital gain
Long-term capital gain
Long-term revenues
Finance constraint
Holding cost
Transaction cost
Finance constraint
Holding cost
Transaction cost
Most experienced
Arbitrage
Intermediary
Leader
Experienced
Long-term capital gain
Consumption
Social & psychological utilities
Finance constraint
Holding cost
Transaction cost
Moving cost
Idiosyncratic preferences
Less experienced
Positive Feedback
Follower
Source: Summarized from a comprehensive literature review on housing market participants.
Back
Motivation and Significance

4. Flippers (as in Fu, Qian & Yeung, 2013; Fu & Qian, 2014) takes tiny portion (10% in
Singapore) of market but influence the whole market.
Back
Source: composed based on REALIS and StreetSine: 2006Q1-2013Q4
Motivation and Significance

5. Flippers more experienced than the rest, more likely to take good trading
patterns (arbitrageur and intermediary) rather than the bad ones (positive
feedback);
Participants at buying side
Quarters
Owner-occupiers Rental Investors Flippers
Property Cycle
2007Q3-2008Q1
68.03
21.39
10.58
Peak
2008Q4-2009Q2
66.89
15.54
17.5
Trough
2007Q1-2009Q2
67.19
17.25
15.55
Whole Cycle
Participants at selling side
Quarters
Owner-occupiers Rental Investors Flippers
Property Cycle
2007Q3-2008Q1
34.36
0.69
20.31
Peak
2008Q4-2009Q2
34.08
1.98
11.59
Trough
2007Q1-2009Q2
33.54
0.95
15.12
Whole Cycle
Unidentified
0
0.07
0.01
Total
100
100
100
Unidentified
44.64
52.35
50.39
Total
100
100
100
Source: composed based on REALIS and StreetSine: 2006Q1-2013Q4
Back
Empirical Results

Back
Flippers lead the buying of owner-occupiers in transaction volume:
Panel A: Booming Period: 2006Q1-2007Q4
Dependent VARIABLE:
Voccupier_b
(1)
Voccupier_b-1
Voccupier_b-2
Voccupier_b-3
Voccupier_b-4
Vflip_b-1
Vflip_b-2
Vflip_b-3
Vflip_b-4
Observations
Controlled Variables
-0.0026533
(0.004367)
0.005371
(0.0036953)
0.0100548***
(0.0019499)
0.0135213***
(0.0030894)
0.0477766***
(0.0075433)
0.0000637
(0.0059562)
-0.0061309
(0.0040743)
-0.0094717**
(0.0046708)
19024
Vrinvest_b-1
Vrinvest_b-2
Vrinvest_b-3
Vrinvest_b-4
Vflip_b-1
Vflip_b-2
Vflip_b-3
Vflip_b-4
Observations
Vrinvest_b
Voccupier_b
(2)
0.0718668***
(0.0210043)
0.0601103***
(0.0150633)
-0.0022403
(0.0053072)
-0.0260861***
(0.0082136)
0.061722***
(0.013935)
-0.0275802**
(0.0131395)
0.0151112***
(0.0044042)
0.0276708***
(0.0050866)
19024
(3)
Voccupier_b-1
Voccupier_b-2
Voccupier_b-3
Voccupier_b-4
Vrinvest_b-1
Vrinvest_b-2
Vrinvest_b-3
Vrinvest_b-4
Observations
Project stylized factors including Project Tenure, Total units of project, Location,
Project type and project age; GDP rate
Standard errors in parentheses and adjusted for clusters in Project
*** p<0.01, ** p<0.05, * p<0.1
0.0097988**
(0.004257)
0.0080345**
(0.0039212)
0.009217***
(0.0021087)
0.0115665***
(0.0018949)
0.0122925
(0.0131206)
0.0096404
(0.0095235)
0.0000935
(0.0047407)
-0.0208092***
(0.0085811)
19024