Prospect Theory : For Risk and Ambiguity /
by Wakker, Peter P [author.].
Material type:
BookPublisher: Cambridge : Cambridge University Press, 2010.Description: 1 online resource (518 pages) : digital, PDF file(s).ISBN: 9780511779329 (ebook).Subject(s): Decision making | Risk | Uncertainty | ProbabilitiesOnline resources: Click here to access online Summary: Prospect Theory: For Risk and Ambiguity, first published in 2010, provided the first comprehensive and accessible textbook treatment of the way decisions are made both when we have the statistical probabilities associated with uncertain future events (risk) and when we lack them (ambiguity). The book presents models, primarily prospect theory, that are both tractable and psychologically realistic. A method of presentation is chosen that makes the empirical meaning of each theoretical model completely transparent. Prospect theory has many applications in a wide variety of disciplines. The material in the book has been carefully organized to allow readers to select pathways through the book relevant to their own interests. With numerous exercises and worked examples, the book is ideally suited to the needs of students taking courses in decision theory in economics, mathematics, finance, psychology, management science, health, computer science, Bayesian statistics, and engineering.
Title from publisher's bibliographic system (viewed on 09 Oct 2015).
Prospect Theory: For Risk and Ambiguity, first published in 2010, provided the first comprehensive and accessible textbook treatment of the way decisions are made both when we have the statistical probabilities associated with uncertain future events (risk) and when we lack them (ambiguity). The book presents models, primarily prospect theory, that are both tractable and psychologically realistic. A method of presentation is chosen that makes the empirical meaning of each theoretical model completely transparent. Prospect theory has many applications in a wide variety of disciplines. The material in the book has been carefully organized to allow readers to select pathways through the book relevant to their own interests. With numerous exercises and worked examples, the book is ideally suited to the needs of students taking courses in decision theory in economics, mathematics, finance, psychology, management science, health, computer science, Bayesian statistics, and engineering.
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