Since the 2008 Financial Crisis, stress tests based on extreme-yet-plausible scenarios have become a preferred method of assessing risk for large financial institutions, yet scenario choice has largely been ad-hoc. We propose a principled methodology to choose scenarios by minimizing the...

A new method for computing the standard errors of returns-based risk and performance estimators for serially correlated returns is developed. The method uses the fact that any such estimator can be represented as the sum of returns that are transformed using the estimator's influence function,...

We use influence functions as a basic tool to study unconditional non-parametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence. Non-parametric ES estimators have a monotonically decreasing influence function of returns. ES...

The Azzalini skew-t distributions are popular because of their theoretical foundation and the availability of computational methods in the R package sn. One difficulty with this skew-t family is that the elements of the expected information matrix do not have closed form analytic formulas. Thus,...

We develop a fundamental law of active management based on cross-section factor models for residual returns where the latter have unconditional mean zero and the factor exposures have zero mean and unit variance. Under our model framework the factor returns are cross-sectional information...

We first provide a brief introduction to influence functions and their use for computing standard errors of risk and performance estimators. We then derive the influence functions for a number of risk estimators and a number of performance estimators, and use the formulas to graphically display...