bootstrap to achieve valid inference in a time series setting. The test statistics and the estimators are computed using linear …

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk. Depending on both … distribution specifications or historical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation …, component VaR and incremental VaR readily follow. The proposed estimation approach pairs intuitive appeal with computational …

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …

This paper determines coverage probability errors of both delta method and parametric bootstrap confidence intervals … are included. The results establish that the bootstrap provides higher-order improvements over the delta method. Analogous …-likelihood. The magnitudes of the coverage probability errors for one-sided bootstrap CIs for covariance parameters for long …

In this paper we analyse bootstrap procedures for systems cointegration tests with a prior adjustment for deterministic … the bootstrap test procedures are derived and their small sample properties are studied. The simulation study also …

confidence intervals based on inverting bootstrap tests are presented and commented. Monte Carlo results assessing the … have very poor performances, even the percentile-t interval, whereas confidence intervals based on inverting bootstrap …

In the context of long memory, the finite-sample distortion of statistic distributions is so large, that bootstrap … asymptotic confidence interval. In this paper, we propose confidence intervals based on inverting bootstrap tests for the long … percentile-t interval, whereas confidence intervals based on inverting bootstrap tests have quite satisfactory performance. For …

their quantile breakdown point. For the block bootstrap and the sub- sampling, we find a very low quantile breakdown point …, which can ren- der inferences based on standard resampling methods useless already in simple estimation and testing settings …

samples than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz …