This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

This paper studies the local robustness of estimators and tests for the conditional location and scale parameters in a strictly stationary time series model. We first derive optimal bounded-influence estimators for such settings under a conditionally Gaussian reference model. Based on these...

[Update: Within four weeks of the original publication of this research report, Risk Magazine reported in its 28th February 2012 issue story titled 'Goodbye VaR? Basel to Consider Other Risk Metrics': "A review of trading book capital rules, due to be launched in March by the Basel Committee on...

In aftermath of the Financial Crisis, some risk management practitioners advocate wider adoption of Bayesian inference to replace Value-at-Risk (VaR) models for minimizing risk failures (Borison & Hamm, 2010). They claim reliance of Bayesian inference on subjective judgment, the key limitation...

In the aftermath of the Global Financial Crisis, some risk management practitioners have advocated wider adoption of Bayesian inference to replace Value- at-Risk (VaR) models in order to minimize risk failures. Despite its limitations, the Bayesian methodology has significant advantages. Just...

This paper focuses on the robust Efficient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

Data Envelopment Analysis (DEA) is a widely applied nonparametric method for comparative evaluation of firms’ efficiency. A deficiency of DEA is that the efficiency scores assigned to each firm are sensitive to sampling variations, particularly when small samples are used. In addition, an...

This paper presents a method to characterize the typical path of a stochastic process, which I refer to as the Median Path. The paper describes how to estimate the Median Path in simulation and compares it to a different estimate of the typical path that is defined as the median value at each...

A class of composite estimators of small area quantities that exploit spatial (distancerelated) similarity is derived. It is based on a distribution-free model for the areas, but the estimators are aimed to have optimal design-based properties. Composition is applied also to estimate some of the...

In this paper, we derive simple point-optimal sign-based tests in the context of linear and nonlinear regression models with fixed regressors. These tests are exact, distribution-free, robust against heteroskedasticity of unknown form, and they may be inverted to obtain confidence regions for...