We investigate and axiomatize preferences that display indifference between deterministic states, but exhibit strict orderings over lotteries over these states. Such preferences might be due to the ability to adopt to states, or a (dis)taste for uncertainty. We derive a representation theorem...

Portfolio models typically ignore precautionary transactions demands for liquid assets, and models of precautionary demands typically ignore asset rate-of-return risk. If asset-holders are risk-averse, however, both transactions risk and rate-of-return risk affect demands for both liquid and...

This article describes the main historical facts concerning the Saint Petersburg paradox, the most important solutions proposed thus far, and the results of new experimental evidence and a simulation of the game that shed light on a solution for this paradox. The Saint Petersburg paradox has...

Expected utility theory is critical for modeling rational decision making under uncertainty, guiding economic agents as they seek to optimize outcomes. Traditional methods often require restrictive assumptions about underlying stochastic processes, limiting their applicability. This paper...

We directly optimize portfolio weights as a function of firm characteristics via deep neural networks by generalizing the parametric portfolio policy framework. Our results show that network-based portfolio policies result in an increase of investor utility of between 30 and 100 percent over a...

We consider parametric portfolio policies of any complexity using deep neural networks to optimize investor utility. Risk aversion acts as an economic regularization mechanism, with higher risk aversion constraining model complexity. Empirically, Deep Parametric Portfolio Policies (DPPP)...

Portfolio models typically ignore precautionary transactions demands for liquid assets, and models of precautionary demands typically ignore asset rate-of-return risk. If asset-holders are risk-averse, however, both transactions risk and rate-of-return risk affect demands for both liquid and...

Comonotonicity (''same variation'') of random variables minimizes hedging possibilities and has been widely used, e.g., in Gilboa and Schmeidler's ambiguity models. This paper investigates anticomonotonicity (''opposite variation''; abbreviated ''AC''), the natural counterpart to comonotonicity....

We study how the separation of time and risk preferences relates to a property called Stochastic Impatience. We show that, within a broad class of models, Stochastic Impatience holds if and only if risk aversion and the inverse elasticity of intertemporal substitution are sufficiently close. In...

We introduce a novel experimental framework, the two-ball Ellsberg gamble, which allows us to explore a wider range of possible drivers of ambiguity attitudes than usually considered by the literature. In an incentivized experiment on a representative sample from the US with 708 participants, we...

We introduce and analyze expected balanced uncertain utility (EBUU) theory. A prior and a balanced outcome-set utility characterize an EBUU decision maker. Conditional on a reference or "balancing value," the latter assigns a utility to each outcome-set. The decision maker associates with each...

Promoting household-level adaptation measures is an important part of climate change adaptation policies to reduce vulnerability to droughts for (agro-)pastoral communities in sub-Saharan Africa. To develop effective supportive policies, it is important to get a better understanding of the needs...

We elicit subjects' beliefs over opponents' behavior multiple times for a given game without feedback. A large majority of subjects have stochasticity in their belief reports, which we argue cannot be explained by learning or measurement error, suggesting significant noise in subjects'...

We consider the problem where a modeller conducts sensitivity analysis of a model consisting of random input factors, a corresponding random output of interest, and a baseline probability measure. The modeller seeks to understand how the model (the distribution of the input factors as well as...

We present a novel characterization of random rank-dependent expected utility for finite datasets and finite prizes. As a byproduct, we obtain a characterization of random expected utility that works for finite datasets. The test lends itself to statistical testing. We apply our test to an...