Two types of unit root tests which accommodate a structural level shift at a known point in time are extended to the situation where the break date is unknown. It is shown that for any estimator for the break date the tests have the same asymptotic distribution as the corresponding tests under...

It is common practice to identify the number and sources of shocks that move implied volatilities across space and time by applying Principal Components Analysis (PCA) to pooled covariance matrices of changes in implied volatilities. This approach, however, is likely to result in a loss of...

The annual structure of the real GDP in the UK, France, Germany and Italy is examined in this article by means of fractionally integrated techniques. Using a version of a testing procedure due to Robinson (1994), we show that the series can be specified in terms of I(d) statistical models with d...

We propose in this article a joint test for testing simultaneously a deterministic trend component and the degree of integration of the cyclical component in a given time series. The test is directly derived from Robinson's (1994) procedure, which is based on the Lagrange Multiplier (LM)...

The analysis of diffusion processes in financial models is crucially dependent on the form of the drift and diffusion coefficient functions. A methodology is proposed for estimating and testing coefficient functions for ergodic diffusions that are not directly observable. It is based on...

We show in this article that fractionally integrated univariate models for GDP may lead to a better replication of business cycle characteristics. We firstly show that the business cycle features are clearly affected by the degree of integration as well as by the other short run components of...

A bootstrap methodology for the periodogram of a stationary process is proposed which is based on a combination of a time domain parametric and a frequency domain nonparametric bootstrap. The parametric fit is used to generate periodogram ordinates and imitate the essential features of the data...

The bootstrap is a method for estimating the distribution of an estimator or test statistic by resampling one’s data or a model estimated from the data. The methods that are available for implementing the bootstrap and the accuracy of bootstrap estimates depend on whether the data are a random...