Search results
Results from the WOW.Com Content Network
A possible solution is to calculate n one-dimensional cardinal utility functions - one for each attribute. For example, suppose there are two attributes: apples and bananas (), both range between 0 and 99. Using VNM, we can calculate the following 1-dimensional utility functions:
Exponential utility implies constant absolute risk aversion (CARA), with coefficient of absolute risk aversion equal to a constant: ″ ′ =. In the standard model of one risky asset and one risk-free asset, [1] [2] for example, this feature implies that the optimal holding of the risky asset is independent of the level of initial wealth; thus on the margin any additional wealth would be ...
The isoelastic utility function is a special case of hyperbolic absolute risk aversion and at the same time is the only class of utility functions with constant relative risk aversion, which is why it is also called the CRRA (constant relative risk aversion) utility function. In statistics, the same function is called the Box-Cox transformation ...
This category is for specific utility functions, properties or classes of utility functions. Pages in category "Utility function types" The following 43 pages are in this category, out of 43 total.
Standard utility functions represent ordinal preferences. The expected utility hypothesis imposes limitations on the utility function and makes utility cardinal (though still not comparable across individuals). Although the expected utility hypothesis is standard in economic modeling, it is violated in psychological experiments.
E.g., the commodity is a heterogeneous resource, such as land. Then, the utility functions are not functions of a finite number of variables, but rather set functions defined on Borel subsets of the land. The natural generalization of a linear utility function to that model is an additive set function.
The term E-utility for "experience utility" has been coined [2] to refer to the types of "hedonistic" utility like that of Bentham's greatest happiness principle. Since morality affects decisions, a VNM-rational agent's morals will affect the definition of its own utility function (see above).
A single-attribute utility function maps the amount of money a person has (or gains), to a number representing the subjective satisfaction he derives from it. The motivation to define a utility function comes from the St. Petersburg paradox: the observation that people are not willing to pay much for a lottery, even if its expected monetary gain is infinite.