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FLOWER AUCTIONS IN AMSTERDAM. Ad Auctions. October 17, 2008. Overture slide. Motivation. Market inherently interesting 98% of Google’s and ~50% of Yahoo’s revenues “Future of advertising” Unusual auction rules Multiple units, but only one bid. Continuous time. Structured market

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ad auctions

Ad Auctions

October 17, 2008

motivation
Motivation
  • Market inherently interesting
    • 98% of Google’s and ~50% of Yahoo’s revenues
    • “Future of advertising”
  • Unusual auction rules
    • Multiple units, but only one bid. Continuous time.
  • Structured market
    • Rules. Almost like a lab. Good data.
  • Purely electronic market
    • No goods ever shipped anywhere.
  • Flexibility to change auction rules from time to time
generalized first price auctions
Generalized first price auctions

Problem: Generalized first price auctions are unstable.

No pure strategy equilibrium, and bids can be adjusted dynamically. Bidders want to revise their bids as often as possible.

edelman and ostrovsky 2007
Edelman and Ostrovsky, 2007

Yahoo data from June 15, 2002 to June 14, 2003

1000 top markets

10,475 bidders

18,634,347 bids

Observe bids at the quarter-hour

cycling
Cycling

Time Market Bidder Bid

6/17/2002 6:30 AM 24 13 $5.91

6/17/2002 6:30 AM 24 810 $5.92

6/17/2002 6:30 AM 24 14 $5.93

6/17/2002 6:30 AM 24 13 $5.94

6/17/2002 6:30 AM 24 60 $5.95

6/17/2002 6:30 AM 24 14 $5.96

6/17/2002 6:45 AM 24 810 $5.97

6/17/2002 6:45 AM 24 13 $5.97

6/17/2002 11:30 PM 24 13 $9.98

6/17/2002 11:30 PM 24 14 $9.98

6/17/2002 11:45 PM 24 14 $10.00

6/17/2002 11:45 PM 24 60 $10.00

6/17/2002 11:45 PM 24 13 $10.00

6/17/2002 11:45 PM 24 810 $10.01

6/17/2002 11:45 PM 24 14 $10.02

6/17/2002 11:45 PM 24 13 $5.12

6/17/2002 11:45 PM 24 14 $5.13

alternative mechanisms
Alternative mechanisms
  • Generalized first-price
  • Generalized second-price
    • Pay the bid of the next-highest bidder
    • First implemented by Google (2002), later adopted by Yahoo
  • VCG
    • Each bidder pays the externality he imposes on others
generalized second price auctions
Generalized second-price auctions

Position Bidder Bid

1 A $7

2 B $6

3 C $5

Payment

$6.01

$5.01

$0.10

computing vcg payments example
Computing VCG payments: example

Position # clicks

1 100

2 80

Bidder Valuation

C $10

A $8

B $5

C’s payment:

C pushes A from 1 to 2

C pushes B out completely

So C should pay $160+$400=$560

 loss of surplus (100-80)*$8=$160

 loss of surplus 80*$5=$400

gsp in use
GSP in use

Adv Bid Payment

A $3.01 $3.01

B $3.00 $2.81

C $2.80 $1.11

D $1.10

gsp versus vickrey and vcg
GSP versus Vickrey and VCG

“[Google’s] unique auction model uses Nobel Prize-winning economic theory to eliminate … that feeling that you’ve paid too much.”

  • With only one slot, GSP is identical to standard second price auctions (Vickrey, VCG)
  • With multiple slots, the mechanisms differ
    • GSP charges bidder i the bid of bidder i+1
    • VCG charges bidder i for his externality

- Google marketing materials

truth telling is not a dominant strategy under gsp
Truth-telling is not a dominant strategy under GSP

Intuition: Sometimes, bid below your true valuation. You may get less traffic, but you’ll earn greater profits.

Suppose there are 3 bidders but 2 positions.Positions have click-through rates 100 and 80.

C’s valuation: $10

bidder bid

A $8

B $5

C bids $10, pays $8 → payoff ($10-$8)*100 =$200

C bids $6, pays $5 → payoff ($10-$5)*80 =$400

$400>$200. So C should place a bid below its valuation.