This chapter discusses estimation, specification testing, and model selection of predictive density models. In particular, predictive density estimation is briefly discussed, and a variety of different specification and model evaluation tests due to various authors including Christoffersen and...

Our objectives in this paper are twofold. First, we introduce block bootstrap techniques that are (first order) valid in recursive estimation frameworks. Thereafter, we present two examples where predictive accuracy tests are made operational using our new bootstrap procedures. In one...

This paper proposes a Kolmogorov-type test for the shortfall order (also known in the literature as the right-spread or excess-wealth order) against parametric alternatives. In the case of the null hypothesis corresponding to the Negative Exponential distribution, this provides a test for the...

Double bootstrap methods are used to control the overall significance level of a battery of diagnostic tests applied to a regression model estimated by ordinary least squares. Monte Carlo evidence on the finite sample performance of the bootstrap methods is reported and discussed

This letter evaluates the performance of auxiliary regression-based specification tests for parametric duration models estimated with censored data. The test using asymptotic critical values has poor size. Bootstrapping corrects the size problem but results in a biased power curve

For bootstrap sample means resulting from a sequence fXn; n 1g of random variables, very general weak laws of large numbers are established.The random variables fXn; n 1g do not need to be independent or identically distributed or to be of any particular dependence structure.In general, no...

Purpose – In general, the insurance industry accepts large risks due to the frequency and severity of extreme events. Because of the short record on hazard data for such events, a large amount of uncertainty has to be dealt with. Given this large uncertainty it is important to better quantify...

Purpose – In general, the insurance industry accepts large risks due to the frequency and severity of extreme events. Because of the short record on hazard data for such events, a large amount of uncertainty has to be dealt with. Given this large uncertainty it is important to better quantify...