scholarly journals Resolution of St. Petersburg Paradox

2020 ◽  
Author(s):  
Vyacheslav I. Yukalov
Keyword(s):  
Petersburg Paradox

From the St. Petersburg Paradox to the Dismal Theorem

2019 ◽  
Author(s):  
Susumu Cato
Keyword(s):  
Petersburg Paradox

scholarly journals Cumulative prospect theory and the St. Petersburg paradox

2006 ◽  
Vol 28 (3) ◽  
pp. 665-679 ◽  
Author(s):  
Marc Oliver Rieger ◽  
Mei Wang
Keyword(s):  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Petersburg Paradox

St. Petersburg Paradox

2012 ◽  
Keyword(s):  
Petersburg Paradox

St. Petersburg Paradox

2011 ◽  
Keyword(s):  
Petersburg Paradox

ON BERNOULLI, SHARPE, FINANCIAL RISK AND THE ST. PETERSBURG PARADOX

1976 ◽  
Vol 31 (3) ◽  
pp. 960-962 ◽  
Author(s):  
John T. Sennetti
Keyword(s):  
Financial Risk ◽  
Petersburg Paradox

Bounded, Sigmoid Utility for Insurance Applications

2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Siwei Gao ◽  
Michael R. Powers
Keyword(s):  
Decision Maker ◽  
Utility Functions ◽  
Decision Makers ◽  
Logical Necessity ◽  
Empirical Observation ◽  
Von Neumann ◽  
Bid Price ◽  
Bounded Below ◽  
Petersburg Paradox ◽  
Actual Decision

AbstractApplying a well-known argument of Karl Menger to an insurance version of the St. Petersburg Paradox (in which the decision maker is confronted with losses, rather than gains), one can assert that von Neumann-Morgenstern utility functions are necessarily concave upward and bounded below as decision-maker wealth tends to negative infinity. However, this argument is subject to two potential criticisms: (1) infinite-mean losses do not exist in the real world; and (2) the St. Petersburg Paradox derives its force from empirical observation (i. e., that actual decision makers would not agree to an arbitrarily large insurance bid price to transfer an infinite-mean loss), and thus does not impart logical necessity. In the present article, these two criticisms are addressed in turn. We first show that, although infinite-mean insurance losses technically do not exist, they do provide a reasonable model for certain large (i. e., excess and reinsurance) property-liability indemnities. We then employ the Two-Envelope Paradox to demonstrate the logical necessity of concave-upward, lower-bounded utility for arbitrarily small (i. e., negative) values of wealth. Finally, we note that recognizing the bounded, sigmoid nature of utility functions challenges certain fundamental understandings in the economics of insurance demand, and can lead to vastly different conclusions regarding the bid price for insurance.

A Monte Carlo Simulation Related to the St. Petersburg Paradox

1984 ◽  
Vol 15 (4) ◽  
pp. 339 ◽  
Author(s):  
Allan J. Ceasar
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Petersburg Paradox

The St. Petersburg paradox and capital asset pricing

2015 ◽  
Vol 12 (1) ◽  
pp. 1-16
Author(s):  
Assaf Eisdorfer ◽  
Carmelo Giaccotto
Keyword(s):  
Asset Pricing ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Petersburg Paradox

An Empirical Approach to the St. Petersburg Paradox

2011 ◽  
Vol 42 (4) ◽  
pp. 260-264 ◽  
Author(s):  
Dominic Klyve ◽  
Anna Lauren
Keyword(s):  
Empirical Approach ◽  
Petersburg Paradox
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