A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken ‘directly’ from the observed data. The procedure is useful when one wants to summarize the test results for several...

See also C. Diks: <A href="http://www1.fee.uva.nl/cendef/upload/6/ecss_diks_r1.pdf">'Nonparametric tests for independence'</A>. In R. Meyers (Ed.), Encyclopedia of Complexity and Systems Science. Berlin: Springer Verlag, 2009. <P> Tests for serial independence and goodness-of-fit based on divergence notions between probability distributions, such as the...</p></a>

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the degree of non-linearity of the instruments comprised in the portfolio and thewillingness to make restrictive assumptions on the underlying statistical distributions, a...

Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these...

We consider the question whether top tennis players in a top tournament (Wimbledon) employ an optimal (efficient) service strategy. We show that top players do not, in general, follow an optimal strategy, and we provide a lower bound of the inefficiency. The inefficiency regarding winning a...

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

This discussion paper resulted in a chapter in: (K. Bocker (Ed.)) 'Rethinking Risk Measurement and Reporting - Volume II: Examples and Applications from Finance', 2010, London: Riskbooks.<P> This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of...</p>

Publication in the 'Journal of Business & Economic Statistics' forthcoming.<A> We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and...</a>

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...

By combining two alternative formulations of a test statistic with two alternative resamplingschemes we obtain four different bootstrap tests. In the context of static linear regression modelstwo of these are shown to have serious size and power problems, whereas the remaining two areadequate...