Portfolio optimization problems involving Value-at-Risk (VaR) are often computationally intractable and require complete information about the return distribution of the portfolio constituents, which is rarely available in practice. These difficulties are further compounded when the portfolio...

Despite portfolio construction based on expected utility theory and Markowitz mean-variance optimization having been the foundation of financial economic theory for more than 50 years, its practical application by financial advisors has been limited. Particularly troubling are the lack of a...

The least squares estimator is probably the most frequently used estimation method in regression analysis. Unfortunately, it is also quite sensitive to data contamination and model misspecification. Although there are several robust estimators designed for parametric regression models that can...

Multivariate time series may contain outliers of different types. In presence of such outliers, applying standard multivariate time series techniques becomes unreliable. A robust version of multivariate exponential smoothing is proposed. The method is affine equivariant, and involves the...

This paper investigates the extent to which rationalizable implementation depends on the implicit common knowledge restrictions usually embodied in traditional models. It is shown that such restrictions are largely without loss of generality: under fairly general conditions, a mechanism...

A collaborative filtering system recommends to users products that similar users like. Collaborative fi ltering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide theoretical and empirical results demonstrating that while...

This paper presents a new data-driven bandwidth selector compatible with the small bandwidth asymptotics developed in Cattaneo, Crump, and Jansson (2009) for density-weighted average derivatives. The new bandwidth selector is of the plug-in variety, and is obtained based on a mean squared error...

This paper is concerned with robust estimation under moment restrictions. A moment restriction model is semiparametric and distribution-free, therefore it imposes mild assumptions. Yet it is reasonable to expect that the probability law of observations may have some deviations from the ideal...

Inference for mixture models based on likelihood estimates suffers from lack of robustness. The presence of a few spurious observations may lead to incorrect decisions. In this paper we consider robust alternatives to the likelihood inference for finite Poisson mixtures based on the minimum...