Possibilistic risk aversion with many parameters

نویسندگان

  • Irina Georgescu
  • Jani Kinnunen
چکیده

The study of risk aversion of an agent confronted by a risk situations with several parameters is an important topic of risk theory. It is tackled traditionally with probabilistic methods. When these do not offer an appropriate shaping we can use Zadeh’s possibility theory . In this paper a possibilistic model of risk aversion with several parameters is proposed. The notion of possibilistic risk premium vector is introduced as a measure of an agent’s risk aversion to a situation with several risk parameters. The main result of the paper is an approximate calculation formula of this indicator. The way we can apply this model in risk aversion evaluation in grid computing is sketched out.

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تاریخ انتشار 2011