We characterize the robustness of subsampling procedures by deriving a general formula for the breakdown point of subsampling quantiles. This breakdown point can be very low for moderate subsampling block sizes, which implies the fragility of subsampling procedures, even if they are applied to...

A large literature studies the predictability of stock returns by other lagged nancialvariables in a predictive regression setting. A common feature of widely used testingprocedures is a failing robustness, which may lead to misleading conclusions determinedby the particular features of a small...

We study an equilibrium asset pricing model with several Lucas (1978) trees subject toevent risk, that is, the possibility that trees experience unexpected disasters. We exploit themarket clearing mechanism, in the presence of multiple positive net supply assets, to showthat the implications of...

In this paper, we consider the coherent theory of (epistemic) uncertainty ofWalley, in whichbeliefs are represented through sets of probability distributions, and we focus on the problemof modeling prior ignorance about a categorical random variable. In this setting, it isa known result that a...

We develop a convenient structural framework for the joint model-ing of credit spreads, stock prices, stock options and basket creditderivatives, using a multivariate structural ¯rm value model withskewed asset returns. We show that our setting successfully addressesseveral empirical facts,...

We develop a new completely affine model of the term structure of interest rates, in which the statevariables evolve as a matrix-valued process of stochastically correlated factors. This setting grants a newelement of flexibility in the simultaneous modeling of stochastic volatilities and...

We develop infinitesimally robust statistical procedures for general diffusion pro-cesses. We first prove existence and uniqueness of the times series influence functionof conditionally unbiased M{estimators for ergodic and stationary diffusions, underweak conditions on the (martingale)...

We propose a new multivariate GARCH model with Dynamic Conditional Correlations that extends previous models by admitting multivariate thresholds in conditional volatilitiesand correlations. The model estimation is feasible in large dimensions and the positive definiteness of the conditional...

We propose a multivariate nonparametric technique for generating reliable short-term historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest...

We apply perturbation theory to solve the optimal control problem of an investor with time-additive power utility over intermediate consumption and final wealth. Under general conditions we show existence of a power series representation for the prevailing optimal consumption and investment...