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Adversarial risk analysis for first‐price sealed‐bid auctions
Author(s) -
Ejaz Muhammad,
Joshi Chaitanya,
Joe Stephen
Publication year - 2021
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/anzs.12315
Subject(s) - common value auction , adversarial system , function (biology) , mathematical economics , risk neutral , risk aversion (psychology) , economics , econometrics , microeconomics , mathematical optimization , computer science , mathematics , expected utility hypothesis , artificial intelligence , evolutionary biology , biology
Summary Adversarial risk analysis (ARA) is an upcoming methodology that is considered to have advantages over the traditional decision‐theoretic and game‐theoretic approaches. ARA solutions for first‐price sealed‐bid (FPSB) auctions have been found but only under strong assumptions which make the model somewhat unrealistic. In this paper, we use ARA methodology to model FPSB auctions using more realistic assumptions. We define a new utility function that considers bidders’ wealth, we assume a reserve price and find solutions not only for risk‐neutral but also for risk‐averse as well as risk‐seeking bidders. We model the problem using ARA for non‐strategic play and level‐ k thinking solution concepts.