Portfolio optimization under convex incentive schemes

Portfolio optimization under convex incentive schemes

We consider the terminal wealth utility maximization problem from the point of view of a portfolio manager who is paid by an incentive scheme, which is given as a convex function g of the terminal wealth. The manager’s own utility function U is assumed to be smooth and strictly concave, however the resulting utility function U ◦ g fails to be concave. As a consequence, the problem considered he...

Robustness-based portfolio optimization under epistemic uncertainty

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

Convex Duality in Constrained Portfolio Optimization

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On utility maximization under convex portfolio constraints

Do Convex Incentive Schemes Attract Overconfident Employees? Experimental Evidence*

Convex incentive schemes, which pay employees an increasing percentage of output as their output increases, are commonly used by companies, especially in sales environments. Research has demonstrated these schemes carry large costs as employees “game” them, yet they are still persistently used. Using a set of experiments where subjects have the choice of incentive scheme, we examine whether a c...