Preference reversals occur when different (but formally equivalent) elicitation methods reveal conflicting preferences over two alternatives. This paper shows that when people have fuzzy preferences i.e. when they choose in a probabilistic manner, their observed decisions can generate systematic...

Standard models of Bayesian updating predict a stronger investor reaction to new information when those investors are more uncertain about the firm. However, prior empirical literature has struggled to find widespread evidence in support of this prediction. This paper tests two explanations for...

We analyze the effect of ambiguous loss probabilities on competitive insurance markets with asymmetric information. We characterize equilibria under actuarially fair pricing with preferences that are second-order ambiguity averse (have smooth indifference curves). We also show existence of...

The UK's decision to leave the EU in the 2016 referendum created substantial uncertainty for UK businesses. The nature of this uncertainty is different from that of a typical uncertainty shock because of its length, breadth and political complexity. Consequently, a new firm-level survey, the...

The principle of indifference states that events should be assigned equal probabilities if no reason can be given for regarding one event as more likely than another. This paper provides a normative argument for the principle of indifference based on a new formal model of decision under...

This paper proposes a model of expected utility maximization which accounts for the Ellsberg paradox and Machina's extension of it. In the model, decision makers use a ring of hypercomplex numbers, and they do so in order to decompose their beliefs into ‘ambiguous' or ‘unambiguous' parts –...

Models can be wrong and recognising their limitations is important in financial and economic decision making under uncertainty. Robust strategies, which are least sensitive to perturbations of the underlying model, take uncertainty into account. Finding the explicit set of alternative models...

We address the problem of decision making under “deep uncertainty,” introducing an approach we call Robust Portfolio Decision Analysis. We introduce the idea of Belief Dominance as a prescriptive operationalization of a concept that has appeared in the literature under a number of names. We...

We develop a model of unforeseen contingencies. These are contingencies that are understood by economic agents ' their consequences and probabilities are known' but are such that every description of such events necessarily leaves out relevant features that have a non-negligible impact on the...

Upon observing a signal, a Bayesian decision maker updates her probability distribution over the state space, chooses an action, and receives a payoff that depends on the state and the action taken. An information structure determines the set of possible signals and the probability of each...