In panel data econometrics the Hausman test is of central importance to select an e±cient estimator of the models' slope parameters. When testing the null hypothesis of no correlation between unobserved heterogeneity and observable explanatory variables by means of the Hausman test model...

In this note a Monte Carlo approach is suggested to determine critical values for diagnostic tests of Value-at-Risk models that rely on binary random variables. Monte Carlo testing offers exact significance levels in finite samples. Conditional on exact critical values the dynamic quantile test...

This paper reviews important concepts and methods that are useful for hypothesis testing. First, we discuss the Neyman-Pearson framework. Various approaches to optimality are presented, including finite-sample and large-sample optimality. Then, some of the most important methods are summarized,...

Fund-of-funds (FoF) managers face the task of selecting a (relatively) small number of hedge funds from a large universe of candidate funds. We analyse whether such a selection can be successfully achieved by looking at the track records of the available funds alone, using advanced statistical...

Return event studies generally involve several firms but there are also cases when only one firm is involved. This makes the relevant testing problems, abnormal return (AR) and cumulative abnormal return (CAR), more difficult since one cannot exploit the multitude of firms (by using a relevant...

There has been a recent interest in reporting p-values adjusted for resampling-based stepdown multiple testing procedures proposed in Romano and Wolf (2005a,b). The original papers only describe how to carry out multiple testing at a fixed significance level. Computing adjusted p-values instead...