Risk averse preference models for normalised lotteries based on simulation

Khwazbeen Saida Fatah, Peng Shi, Jamal Ameen, Ron Wiltshire

Research output: Contribution to journalArticlepeer-review

2 Downloads (Pure)

Abstract

In this paper, we propose a new risk-preference model for ranking pairs of normalised lotteries, random variables, each represents a risk factor obtained by converting the outcomes of the lottery into its mean multiplied by a risk factor. With the existence of an expected utility model, the preference ordering over a pair of such lotteries is converted into a risk-preference ranking over their risk factors. The proposed model is an efficient approximation model based on cumulative distribution functions using simulation. It can be used for analysing preferences between pairs of uncertain alternatives representing financial investment for risk-averse investors. Furthermore, unlike other models, it can be applied to a variety of randomly distributed variables with different utility functions.
Original languageEnglish
Pages (from-to)189 - 207
Number of pages18
JournalInternational Journal of Operational Research
Volume8
Issue number2
DOIs
Publication statusPublished - 9 May 2010

Keywords

  • cumulative-function
  • expected-utility theory
  • mean-variance theory
  • normalised lotteries
  • ranking preferences
  • simulation
  • operations research

Fingerprint

Dive into the research topics of 'Risk averse preference models for normalised lotteries based on simulation'. Together they form a unique fingerprint.

Cite this