introduction to auctions

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Introduction to Auctions David M. Pennock

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Introduction to Auctions. David M. Pennock. Going once, … going twice,. Auctions: yesterday. Ebay: 4 million auctions 450k new/day >800 others auctionrover.com biddersedge.com. Auctions: today. Auctions: yesterday vs. today. What is an auction?. - PowerPoint PPT Presentation

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Page 1: Introduction to Auctions

Introduction to Auctions

David M. Pennock

Page 2: Introduction to Auctions

Auctions: yesterday

Going once, …going twice, ...

Page 3: Introduction to Auctions

Auctions: today

Ebay:– 4 million auctions

– 450k new/day

>800 others– auctionrover.com

– biddersedge.com

Page 4: Introduction to Auctions

Auctions: yesterday vs. today

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Market Capitalization (billions)

Sotheby's (1744)Ebay (1995)

Page 5: Introduction to Auctions

What is an auction?

Definition [McAfee & McMillan, JEL 1987]: – a market institution with an

– explicit set of rules

– determining resource allocation and prices

– on the basis of bids from the market participants.

Examples:

Page 6: Introduction to Auctions

B2B auctions and ecommerce

Online B2B marketplaces have been established recently for more than a dozen major industries, including the automotive; pharmaceuticals; scientific supplies; asset management; building and construction; plastics and chemicals; steel and metals; computer; credit and financing; energy; news and information; and livestock sectors.

– Reuters March 29, 2000

Page 7: Introduction to Auctions

Why auctions?

For object of unknown value Flexible Dynamic Mechanized

– reduces complexity of negotiations– ideal for computer implementation

Economically efficient!

Page 8: Introduction to Auctions

Taxonomy of common auctions

Open auctions– English– Dutch

Sealed-bid auctions– first price– second price (Vickrey)– Mth price, M+1st price– continuous double auction

Page 9: Introduction to Auctions

English auction

Open One item for sale Auctioneer begins low;

typically with seller’s reserve price Buyers call out bids to beat the current price Last buyer remaining wins;

pays the price that (s)he bid

Page 10: Introduction to Auctions

Dutch auction

Open One item for sale Auctioneer begins high;

above the maximum foreseeable bid Auctioneer lowers price in increments First buyer willing to accept price wins;

pays last announced price less information

Page 11: Introduction to Auctions

Sealed-bid first price auction

All buyers submit their bids privately buyer with the highest bid wins;

pays the price (s)he bid

$150$120

$90

$50

Page 12: Introduction to Auctions

Sealed-bid second price auction (Vickrey) All buyers submit their bids privately buyer with the highest bid wins;

pays the price of the second highest bid

$150$120

$90

$50

Only pays $120

Page 13: Introduction to Auctions

Incentive compatibility Telling the truth is optimal in second-price auction Suppose your value for the item is $100;

if you win, your net gain (loss) is $100 - price If you bid more than $100:

– you increase your chances of winning at price >$100

– you do not improve your chance of winning for < $100

If you bid less than $100:– you reduce your chances of winning at price < $100

– there is no effect on the price you pay if you do win

Dominant optimal strategy: bid $100– Key: the price you pay is out of your control

Page 14: Introduction to Auctions

Collusion

Notice that, if some bidders collude, they might do better by lying (e.g., by forming a ring)

In general, essentially all auctions are subject to some sort of manipulation by collusion among buyers, sellers, and/or auctioneer.

Page 15: Introduction to Auctions

Revenue equivalence

Which auction is best for the seller? In second-price auction, buyer pays < bid In first-price auction, buyers “shade” bids Theorem:

– expected revenue for seller is the same!– requires technical assumptions on buyers,

including “independent private values”– English = 2nd price; Dutch = 1st price

Page 16: Introduction to Auctions

Mth price auction

English, Dutch, 1st price, 2nd price:N buyers and 1 seller

Generalize to N buyers and M sellers Mth price auction:

– sort all bids from buyers and sellers

– price = the Mth highest bid

– let n = # of buy offers >= price

– let m = # of sell offers <= price

– let x = min(n,m)

– the x highest buy offers and x lowest sell offers win

Page 17: Introduction to Auctions

Mth price auction

$150

$120

$90

$50

$300

$170

$130

$110

Buy offers (N=4) Sell offers (M=5)

$80

Page 18: Introduction to Auctions

$50$80

$90$110

$120$130

Mth price auction

$150$170$300

Buy offers (N=4) Sell offers (M=5)

12345

Winning buyers/sellers

price = $120

Page 19: Introduction to Auctions

$50$80

$90$110

$120$130

M+1st price auction

$150$170$300

Buy offers (N=4) Sell offers (M=5)

12345

Winning buyers/sellers

6 price = $110

Page 20: Introduction to Auctions

Incentive compatibility

M+1st price auction is incentive compatible for buyers– buyers’ dominant strategy is to bid truthfully– M=1 is Vickrey second-price auction

Mth price auction is incentive compatible for sellers– sellers’ dominate strategy is to make offers

truthfully

Page 21: Introduction to Auctions

Impossibility

Essentially no auction whatsoever can be simultaneously incentive compatible for both buyers and sellers!– if buyers are induce to reveal their true values,

then sellers have incentive to lie, and vice versa– the only way to get both to tell the truth is to

have some outside party subsidize the auction

Page 22: Introduction to Auctions

$50$80

$90$110

$120$130

k-double auction

$150$170$300

Buy offers (N=4) Sell offers (M=5)

12345

Winning buyers/sellers

6

price = $110 + $10*k

Page 23: Introduction to Auctions

Continuous double auction

k-double auction repeated continuously over time

buyers and sellers continually place offers as soon as a buy offer > a sell offer, a

transaction occurs At any given time, there is no overlap btw

highest buy offer & lowest sell offer

Page 24: Introduction to Auctions

Continuous double auction

Page 25: Introduction to Auctions

Winner’s curse

Common, unknown value for item (e.g., potential oil drilling site)

Most overly optimistic bidder wins; true value is probably less

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$ valuation of item

pro

ba

bil

ity

Page 26: Introduction to Auctions

Combinatorial auctions

E.g.: spectrum rights, computer system, … n goods bids allowed 2n combinations

Maximizing revenue: NP-hard (set packing) Enter computer scientists (hot topic)...

Page 27: Introduction to Auctions

http://www.biz.uiowa.edu/iem

Prediction auctionsIowa Electronic Markets

$1 if Rudy Giuliani wins

$1 if Hillary Clinton wins

$1 if Rick Lazio wins

Page 28: Introduction to Auctions

Prediction auction gamesHollywood Stock Exchange

http://www.hsx.com/

Page 29: Introduction to Auctions

Prediction auction gamesForesight Exchange

$1 iff Cancer curedby 2010

Machine Go championby 2020

Canada breaks upby 2020

http://www.ideosphere.com/

http://www.us.newsfutures.com/http://www.100world.com/

Page 30: Introduction to Auctions

Prediction markets