The selection of upper order statistics in tail estimation is notoriously difficult. Methods that are based on asymptotic arguments, like minimizing the asymptotic MSE, do not perform well in finite samples. Here, we advance a data-driven method that minimizes the maximum distance between the...

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast...

This paper measures valuation and strategic uncertainty in an over-the-counter market. The analysis uses a novel data set of price estimates that major financial institutions provide to a consensus pricing service. We model these institutions as Bayesian agents that learn from consensus prices...