Many men invest in their sisters’ children instead of their wives’. Existing theories addressing such behavior depend on the level of paternity probability in such men’s societies being implausibly low. I link this anthropologically observed investment behavior with the experimentally observed phenomenon that some individuals are ambiguity averse. Arguing that men’s decisions are made under amb...

We consider the problem of designing policies for Markov decision processes (MDPs) with dynamic coherent risk objectives and constraints. begin by formulating in a Lagrangian framework. Under assumption that constraints can be represented transition mapping, we propose an optimization-based method to synthesize Markovian lower-bound constrained risk-averse problem. demonstrate formulated optimi...

This paper investigates continuous-time optimal portfolio and consumption problems under loss aversion in an infinite horizon. The investor’s goal is to choose optimal portfolio and consumption policies to maximize total discounted S-shaped utility from consumption. The consumption rate process is subject to a downside constraint. The optimal consumption and portfolio policies are obtained thro...

We study a principal-agent problem with multiple identical agents, where the action-dependent stochastic relationship between actions and output is perceived to be ambiguous, and agents are ambiguity averse. We argue that ambiguity, and particularly ambiguity aversion, make it more attractive for the principal to choose a tournament. If agents are risk neutral, but ambiguity averse, we show tha...

In this paper we conduct a series of field experiments in rural India in order to measure preferences related to risk, loss, and ambiguity. Disaggregating by data, we find that on average women are significantly more risk averse and loss averse than men, though the higher average risk aversion arises due to a greater share of women who are extremely risk averse. Through a series of two empirica...

Risk averse stochastic optimization is investigated in the context of elastic shape optimization, allowing for microstructures in the admissible shapes. In particular, a two-stage model for shape optimization under stochastic loading with risk averse cost functionals is combined with a two-scale approach for the simulation of microstructured materials. The microstructure is composed of an elast...

Stochastic domains often involve risk-averse decision makers. While recent work has focused on how to model risk in Markov decision processes using risk measures, it has not addressed the problem of solving large risk-averse formulations. In this paper, we propose and analyze a new method for solving large risk-averse MDPs with hybrid continuous-discrete state spaces and continuous action space...

We introduce the concept of a Markov risk measure and we use it to formulate risk-averse control problems for two Markov decision models: a finite horizon model and a discounted infinite horizon model. For both models we derive risk-averse dynamic programming equations and a value iteration method. For the infinite horizon problem we also develop a risk-averse policy iteration method and we pro...