Stochastic dominance theory for location-scale family

Stochastic dominance theory for location-scale family

Meyer (1987) extended the theory of mean-variance criterion to include the comparison among distributions that differ only by location and scale parameters and to include general utility functions with only convexity or concavity restrictions. In this paper, we make some comments on Meyer’s paper and extend the results from Tobin (1958) that the indifference curve is convex upwards for risk ave...

Preferences over location-scale family

Spaces for agreement: a theory of Time-Stochastic Dominance

Many investments involve both a long time-horizon and risky returns. Making investment decisions thus requires assumptions about time and risk preferences. Such assumptions are frequently contested, particularly in the public sector, and there is no immediate prospect of universal agreement. Motivated by these observations, we develop a theory and method of finding ‘spaces for agreement’. These...

Preferences over Meyer’s Location-Scale Family

This paper extends Meyer’s (1987) location-scale family with general n random seed sources. Firstly, we clarify and generalize existing results to this multivariate setting. Some useful geometrical and topological properties of the location-scale expected utility functions are obtained. Secondly, we introduce and study some general non-expected utility functions defined over the location-scale ...

Stochastic Dominance

The concept of Stochastic Dominance (SD) appeared in Economics in the context of the study of income distribution, where it provided various criteria for ranking income distributions according to classes of social welfare functions. Although stochastic dominance is still much in use for studies of income distribution and of poverty, more recently it has also found uses in financial economics, w...