In this paper, we derive central limit and bootstrap theorems for probabilities that centered high-dimensional vector sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the probabilities that a root-n rescaled sample average of Xi is...

We investigate covariance matrix estimation in vast-dimensional spaces of 1,500 up to 2,000 stocks using fundamental factor models (FFMs). FFMs are the typical benchmark in the asset management industry and depart from the usual statistical factor models and the factor models with observed...

In this paper, we derive central limit and bootstrap theorems for probabilities that centered high-dimensional vector sums hit rectangles and sparsely convex sets. Specifically, we derive Gaussian and bootstrap approximations for the probabilities that a root-n rescaled sample average of Xi is...

Recently proposed models of risky choice imply systematic violations of transitivity of preference. Five studies explored whether people show patterns of intransitivity predicted by four descriptive models. To distinguish ?true? violations from those produced by ?error,? a model was fit in which...

From the viewpoint of the independence axiom of expected utility theory, an interesting empirical dynamic choice problem involves the presence of a “global risk,” that is, a chance of losing everything whichever safe or risky option is chosen. In this experimental study, participants have to...

We propose a model of instrumental belief choice under loss aversion. When new information arrives, an agent is prompted to abandon her prior. However, potential posteriors may induce her to take actions that generate a lower utility in some states than actions induced by her prior. These losses...

A learning rule is uncoupled if a player does not condition his strategy on the opponent's payoffs. It is radically uncoupled if a player does not condition his strategy on the opponent's actions or payoffs. We demonstrate a family of simple, radically uncoupled learning rules whose...