Bidding Strategies at Residential
House Auctions
Clare Branigan, Paul Ryan
University College Dublin
Introduction
• This paper examines bidding strategies at
auctions for residential property market sales
in Dublin.
• The period under examination was September
2004 to December 2005 which was close to
the peak of the property boom in Ireland
• At that time, sales of properties through the
auction mechanism was more common for
premium properties
Examples
• In 2005, houses on Shrewsbury Road were among the most
expensive in Europe after 12 years of almost uninterrupted
nationwide rises.
• For example, in 2005, a 4,000 sq ft (372 sq m) house on Shrewsbury
Road (Dublin 4) set an Irish record when a buyer paid more than
€58m for a home with extensive land to the rear that remains
undeveloped.
• Despite having a guide price of €35 million, the house eventually
reached €58 million due to a rumoured six potential buyers vying to
purchase the property.
• In September 2011 the house went on the market again for a price
of €15 million, down €43 million from its sale value in 2005, but was
withdrawn presumably because it never met the guide price
Example: Walford Shrewsbury Road
Dublin Second-hand House Prices
€800,000
€700,000
€600,000
€500,000
€400,000
€300,000
€200,000
€100,000
€0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Source: Sherry Fitzgerald Research (2007)
Bidding Strategies and Open English
Auctions
• Optimal Bidding strategies for sellers and bidders
depend on the auction’s rules
• Open English auctions are a popular form of sale
mechanism in Ireland, particularly at the premium end
of the market.
• Open English Auction
– The auctioneer calls the bid, and the willing bidder
indicates his assent by some slight gesture
– The auctioneer raises the price incrementally or a bidder
can offer a higher bid
– Eventually only one bidder is left who wins the auction
Bidding Strategies
• Actual bids can signal that an item’s true value
has not been reached (Kagel, 1995) and
increased bids by others can cause other to
copy.
• Bidders use traffic as an indication of value,
and more traffic implies higher value.
• This is consistent to Shiller’s (1990) theory on
a shortage illusion.
Escalation of Commitment
• With escalation of commitment, a person
allocates a resource –search costs, finance or
intangibles (e.g., perception, self-identify) to
further a goal.
• When the result is not achieved, they are
disappointed, and therefore more committed
to achieving the goal at the next opportunity.
Escalation of Commitment
• A Dublin property auction requires the successful
bidder to pay a ten per cent deposit for the
property immediately after the auction, which is
non-refundable.
• Thus, a potential bidder is likely to have spent
funds on a property survey and a title check prior
to the auction.
• When the guide price is low, many bidders will
have sunk costs before the auction, and will be
committed to winning.
Endowment Effect
• Lower guide prices encourage more bidders to
have sunk costs in terms of property surveys
and legal checks
• This encourages participation in the auction
which results in the endowment effect
• All of which results in higher sales prices
Sunk Cost Effect
• “The sunk-cost effect is an escalation of
commitment & has been defined as the
greater tendency to continue an endeavor
once an investment in money, time or effect
has been made,”(Arkes, Blumer,1985).
Sunk Cost Effect
• Although economic rationality states that sunk
costs should be ignored and decisions be
made on the basis of future benefits and
costs, individuals tend to be retrospectively
rational, justifying prior decisions (Shaw,
1981).
Types of Bidders
• Neophytes: get in early and fade away
• Sniper: the guy who sits in the back row and
jumps in at the end when all bidding is finished
• Jump Bidding: Jump Bids in high increments to
discourage competition
• Flamboyant Bidders: Those who attract the
auctioneer’s attention by calling bids loudly or
waving a paddle
Shina and Greenleaf (2000)
Bidder Aggressiveness
• Shina and Greenleaf (2000) results indicate
that bidders at Open English Auctions need to
be concerned about the aggressiveness of
other bidders
Sniper
• A “sniper” is defined to be a late bidder at the
auction; who does not bid until only one
remaining bidder is left.
• Popular in online auctions; e.g., there is an
active exchange in eBay’s chat rooms about
how to snipe effectively; even bidding
software that will bid for you at the last
minute
• A sniper strategy can serve the purpose of
signalling an aggressive strategy, sending the
message “Don’t continue bidding as I am going to
keep bidding higher”.
• This message discourages competition for two
related reasons:
– it suggests that the sniper bidder values the property
more than anyone else, and
– & if the aggressive bidder drops out at any stage it
implies that you have overbid for the item.
• When a sniper influences competitors to drop
out quickly, he wins the auction at a relatively
low price & does not have to carry out the
threat of bidding to a high level
• This reason suggests that auctioneers should
maintain strict control of the bidding
sequence in order to promote competition
(Avery, 1997)
Data Gathered
• Data for all available auctions in Dublin area
was collected between Sept 2004 and Nov
2005.
Summary: 1565 Auctions
Methodology
• Observed over 200 auctions in this time
period
• 105 were sold at auction, by an average of
44% over the guide price
• Proposition: The more bids a person makes,
the more committed he becomes to winning
the auction.
Bid Progression
•
1
950
1100
1200 1230 1240
2
1000
1150
1225
3
1050
1235
1245 1255 1265
1250 1260 1270 1275
1272
• For each auction, the number of bids for each
bidder was counted, and the winning bidder
was highlighted
• In 68% of the cases, the person who made the
most bids was the auction winner, i.e., the
bidder that is most committed to winning,
places the most bids.
• This agrees with the theory that actual bids can
signal that an items true value has not been
reached (Kagel, 1995) and increased bids by
others can cause other to copy (herding affect).
• Bidders use traffic as an indication of value, and
high traffic implies greater value.
• Traffic influences the estimated value of an item,
i.e., traffic often begets more traffic and infers
value (Shiller, 1990; Simonsohn & Ariely, 2005).
Best Bidding Strategy – The Sniper
Winner
Winner
Other
Winner
1st Bidder
2nd Bidder
Bidder
Sniper
No. of Auctions
18
14
12
22
% Winner
27%
21%
18%
39%
% Over Guide
42%
47%
57%
36%
Samples
27 Belmont Ave, Donnybrook
Apr 05
Guide 700,000
27 Belmont Ave, Donnybrook
Apr 05
Guide 700,000
Sold 1.36 m,
4 bidders
94% over guide price
8 Temple Cresent, Blackrock
May 05
Guide 650,000
8 Temple Cresent, Blackrock
May 05
Guide 650,000
Sold, 1.3 m,
5 bidders
100% over guide
Samples: Priory Grove, Blackrock
March 05, €730,000
Priory Grove, Blackrock
•
April 06
?
Priory Grove, Blackrock
•
April 06
?
Initial: 730,000
15%
109,000
Upgrades: 90,000
Total:
929,000
Priory Grove, Blackrock
•
April 06
€1.8m
References
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•
•
•
•
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Arkes, H., Blumer, C. (1985). "The Psychology of Sunk Costs." Organizational Behaviour and Human
Decision Process 35: 124-140.
Avery (1997), “Strategic Jump Bidding in English Auctions,” Review of Economic Studies 65, 185-210
Bazerman, M., Sameulson, W. (1983). "I Won the Auction but Don't Want the Prize." The Journal of
Conflict Resolution 27(4): 618-634.
Diaz III, G. P., Levy, D. (2002). "Residential valuation behaviour in the United States, the United
Kingdom, and New Zealand." Journal of Property Research 19(4): 313-326.
Diaz III, H., A. (2001). "Behavioural Research into Real Estate Valuation Process: Progress Toward a
Descriptive Model." Research Issues in Real Estate 8: 3-30.
Diaz III, J., Hansz, A. (1997). "How valuers use the value opinions of others." Journal of Property
Valuation & Investment 15(3): 256-260.
Filiz-Ozbay, E., and Ozbay, Erkut (2007). "Auctions with Anticipated Regret." American Economic
Review 97(4).
Galinsky, A., Mussweiler, T. (2001). "First offers as anchors: The role of perspective-taking and
negotiator focus." Journal of Personality and Social Psychology 81: 657-669.
Kagel, J. H., Levin, D (1986). "The winner's curse and public information in common value auctions."
American Economic Review 76: 894-920.
Kagel, J. (1995). “Auctions: A survey of experimental research in J.H. Kagel & A. E. Roth (Eds.), The
handbook of experimental economics (pp.501-585). Princeton, NJ:Princeton University Press
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References
•
•
•
•
•
•
•
•
•
Arkes, H., Blumer, C. (1985). "The Psychology of Sunk Costs." Organizational Behaviour and Human Decision Process 35: 124140.
Avery (1997), “Strategic Jump Bidding in English Autions,” Review of Economic Studies 65, 185-210
Bazerman, M., Sameulson, W. (1983). "I Won the Auction but Don't Want the Prize." The Journal of Conflict Resolution 27(4):
618-634.
Diaz III, G. P., Levy, D. (2002). "Residential valuation behaviour in the United States, the United Kingdom, and New Zealand."
Journal of Property Research 19(4): 313-326.
Diaz III, H., A. (2001). "Behavioural Research into Real Estate Valuation Process: Progress Toward a Descriptive Model."
Research Issues in Real Estate 8: 3-30.
Diaz III, J., Hansz, A. (1997). "How valuers use the value opinions of others." Journal of Property Valuation & Investment
15(3): 256-260.
Filiz-Ozbay, E., and Ozbay, Erkut (2007). "Auctions with Anticipated Regret." American Economic Review 97(4).
Galinsky, A., Mussweiler, T. (2001). "First offers as anchors: The role of perspective-taking and negotiator focus." Journal of
Personality and Social Psychology 81: 657-669.
Kagel, J. H., Levin, D (1986). "The winner's curse and public information in common value auctions." American Economic
Review 76: 894-920.
•
Kagel, J. (1995). “Auctions: A survey of experimental research in J.H. Kagel & A. E. Roth (Eds.), The handbook of
experimental economics (pp.501-585). Princeton, NJ:Princeton University Press
•
Sinha A., Greenleaf, E, (2000)“The Impact of discrete Bidding and Bidder Aggressiveness on Sellers’ Strategies on Open
English Auctions: reserves and Covert Shilling,” Marketing Science, Vol 19, No. 3 Summer 2000.