Das / Ostrovsky / Pennock Auctions, Market Mechanisms and Their Applications

First International ICST Conference, AMMA 2009, Boston, MA, USA, May 8-9, 2009, Revised Selected Papers
1. Auflage 2009
ISBN: 978-3-642-03821-1
Verlag: Springer
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 116 Seiten

This book constitutes the thoroughly refereed post-conference proceedings of the First International ICST Conference on Auctions, Market Mechanisms and Their Applications, AMMA 2009, held in Boston, MA, USA, in May 2009. The 16 revised papers presented were carefully reviewed and selected from 38 submissions. The contents range from fundamental theory on auctions and markets to empirical design and analysis of matching mechanisms, peer-to-peer-systems, and prediction markets. This includes an understanding of the economic and gametheoretic issues, the ability to design protocols and algorithms for realizing desired outcomes, and the knowledge of specific institutional details that are important in practical applications. This volume aims at economists, computer scientists, theorists and empiricists as well as academics and practitioners.

Autoren/Hrsg.

Das, Sanmay

Ostrovsky, Michael

Pennock, David

Sz, Boleslaw

Inhaltsverzeichnis

1;Preface;5
2;Organization;6
3;Table of Contents;8
4;Effects of Suboptimal Bidding in Combinatorial Auctions;10
4.1;References;11
5;Using Prediction Markets to Track Information Flows: Evidence from Google;12
6;A Copula Function Approach to Infer Correlation in Prediction Markets;13
6.1;Introduction;13
6.2;Correlation Methods Based on Copulas;14
6.2.1;Copula Functions;15
6.2.2;Kendall Function;17
6.3;An Empirical Analysis of Saddam Market and Oil;18
6.4;Conclusions;21
6.5;References;21
7;Manipulating Scrip Systems: Sybils and Collusion;22
7.1;Introduction;22
7.2;Model;24
7.3;Sybils;26
7.4;Collusion;31
7.5;References;33
8;A Centralized Auction Mechanism for the Disability and Survivors Insurance in Chile;34
9;Information Feedback and Efficiency in Multiattribute Double Auctions;35
9.1;Introduction;35
9.2;Auction Preliminaries;36
9.3;Allocation with Complement-Free Valuations;37
9.3.1;Syntactic Valuation Classes;38
9.3.2;OXS Valuations;38
9.3.3;Gross Substitutes;38
9.4;Call Market Implementation;39
9.4.1;Bidding Language;39
9.4.2;Clearing;40
9.4.3;Information Feedback;41
9.5;Multiattribute Valuations;43
9.6;A New Valuation Metric;44
9.6.1;Gross Substitutes Revisited;44
9.6.2;Gross Substitutes Violation;44
9.7;Testing the EGSV-Efficiency Relationship;45
9.7.1;Valuation Generation;45
9.7.2;Market Simulation;45
9.7.3;Simulation Results;46
9.8;Conclusions;47
9.9;References;47
10;Impact of Misalignment of Trading Agent Strategy across Multiple Markets;49
10.1;Introduction;49
10.1.1;CAT Background;50
10.1.2;Biased k-Pricing Policy;50
10.2;Related Work;51
10.3;Problem Description;53
10.3.1;Alignment of Trading Strategy and Market Selection Strategy;53
10.3.2;Modifications in Trading Strategy under Biased K-Pricing Policy;54
10.4;Experimental Setup;55
10.4.1;ZIP Strategy and ZIPK9Aware Strategy;56
10.5;Experimental Results;56
10.5.1;Truth-Teller Case;56
10.5.2;ZIP Trader Case;57
10.5.3;ZIPK9Aware Case;58
10.5.4;Comparison of Total Profit;61
10.6;Conclusion and Future Work;61
10.7;References;62
11;Market Design for a P2P Backup System;64
11.1;Introduction: A P2P Backup System;64
11.2;Research Contributions;65
11.3;Future Work;65
11.4;References;66
12;School Choice: The Case for the Boston Mechanism;67
12.1;References;68
13;Turing Trade: A Hybrid of a Turing Test and a Prediction Market;70
13.1;Introduction;70
13.2;GameOverview;73
13.2.1;Bot Targets;73
13.2.2;Questions and Answers;74
13.2.3;The End of the Game;75
13.2.4;Betting;75
13.3;Evidence for the Accuracy of Prediction Markets;77
13.4;Example Logs;78
13.5;Calibration and Sharpness;79
13.6;Conclusions;81
13.7;References;81
14;A Market-Based Approach to Multi-factory Scheduling;83
14.1;Introduction;83
14.2;The Multi-factory Scheduling Problem;85
14.3;The Market-Based Solution;88
14.3.1;The Market Protocol;88
14.3.2;The Bidding Strategy;90
14.4;Empirical Analysis;91
14.5;Conclusions and Future Work;93
14.6;References;94
15;Auctions with Dynamic Populations: Efficiency and Revenue Maximization;96
16;Revenue Submodularity;98
16.1;Revenue Submodularity;98
16.2;Applications;99
16.3;References;100
17;Fair Package Assignment;101
18;Solving Winner Determination Problems for Auctions with Economies of Scope and Scale;102
18.1;Introduction;102
18.2;Bid Language;102
18.3;Computational Complexity of the Supplier Selection;103
18.4;Reference;103
19;Running Out of Numbers: Scarcity of IP Addresses and What to Do about It;104
19.1;Introduction;104
19.2;The Technology and Institutions of IP Addressing;105
19.3;Relieving v4 Scarcity through Central Planning;105
19.4;Sharing IP Addresses to Reduce v4 Demand;106
19.5;IPv6: The Solution to v4 Scarcity?;107
19.5.1;Transition to IPv6;107
19.5.2;Individual Incentives in IPv6 Transition;108
19.6;A Market Mechanism for Transfer and Reuse of IPv4 Addresses;109
19.6.1;The Historic Prohibition on IPv4 Transfers;109
19.6.2;Paid Transfers to Achieve Allocative Efficiency;110
19.6.3;Hybrid Markets to Prevent Speculation;110
19.6.4;Preventing Unreasonable Growth of the Routing Table;111
19.6.5;Avoiding Transferring Addresses from Poor Regions to Rich Regions;113
19.7;The Decision at Hand;114
19.8;References;114
19.9;Appendix: Full-Fill Plus Permissive Disaggregation Guarantees Convex Prices;115
20;Author Index;116