The paper studies a problem of constructing simultaneous likelihood-based confidence sets. We consider a simultaneous multiplier bootstrap procedure for estimating the quantiles of the joint distribution of the likelihood ratio statistics, and for adjusting the confidence level for multiplicity....

A flexible framework for the analysis of tail events is proposed. The framework contains tail moment measures that allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the quantile and expectile estimation, a platform for risk...

In this paper, we develop and apply Bayesian inference for an extended Nelson-Siegel (1987) term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson-Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. We propose a Markov...

We propose an iterative procedure to efficiently estimate models with complex log-likelihood functions and the number of parameters relative to the observations being potentially high. Given consistent but inefficient estimates of sub-vectors of the parameter vector, the procedure yields...

Complex phenomena in environmental sciences can be conveniently represented by several inter-dependent random variables. In order to describe such situations, copula-based models have been studied during the last year. In this paper, we consider a novel family of bivariate copulas, called...

We present two methods based on functional principal component analysis (FPCA) for the estimation of smooth derivatives of a sample of random functions, which are observed in a more than one-dimensional domain.We apply eigenvalue decomposition to a) the dual covariance matrix of the derivatives,...

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic terms suggested by Saikkonen & Lütkepohl (2000b) and Saikkonen, Lütkepohl & Trenkler (2006). The asymptotic properties of the bootstrap test procedures are derived and their...

Eine große Herausforderung der multivariablen Analyse mit bilanziellen Kennzahlen besteht in der Identifikation derjenigen Kennzahlen, die zur besten Modellperformance führen und dabei möglichst leicht interpretierbar und intuitiv bleiben. Die Menge der in Frage kommenden Kennzahlen ist in...

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids. The Smolyak operator underlying the sparse grids approach frees global approximation from the curse of dimensionality and we apply it to a Chebyshev approximation of the...