Local utility and multivariate risk aversion

Arthur Charpentier, Alfred Galichon, Marc Henry

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

We revisit Machina's local utility as a tool to analyze attitudes to multivariate risks. We show that for nonexpected utility maximizers choosing between multivariate prospects, aversion to multivariate mean preserving increases in risk is equivalent to the concavity of the local utility functions, thereby generalizing Machina's result [Machina M (1982) "Expected utility" analysis without the independence axiom. Econometrica 50:277-323]. To analyze comparative risk attitudes within the multivariate extension of rank dependent expected utility of Galichon and Henry [Galichon A, Henry M (2012) Dual theory of choice with multivariate risks. J. Econom. Theory 147:1501-1516], we extend Quiggin's monotone mean and utility preserving increases in risk and show that the useful characterization given in Landsberger and Meilijson [Landsberger M, Meilijson I (1994) Comonotone allocations, Bickel-Lehmann dispersion and the Arrow-Pratt measure of risk aversion. Ann. Oper. Res. 52:97-106] still holds in the multivariate case.

Original languageEnglish (US)
Pages (from-to)466-476
Number of pages11
JournalMathematics of Operations Research
Volume41
Issue number2
DOIs
StatePublished - May 2016

Fingerprint

Risk Aversion
Henry
Expected Utility
Concavity
Axiom
Utility Function
Risk aversion
Multivariate risk
Monotone
Dependent
Increase in risk

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Computer Science Applications
  • Management Science and Operations Research

Cite this

Charpentier, Arthur ; Galichon, Alfred ; Henry, Marc. / Local utility and multivariate risk aversion. In: Mathematics of Operations Research. 2016 ; Vol. 41, No. 2. pp. 466-476.
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Local utility and multivariate risk aversion. / Charpentier, Arthur; Galichon, Alfred; Henry, Marc.

In: Mathematics of Operations Research, Vol. 41, No. 2, 05.2016, p. 466-476.

Research output: Contribution to journalArticle

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