We consider hypothesis testing in a general linear time series regression framework when the possibly fractional order of integration of the error term is unknown. We show that the approach suggested by Vogelsang (1998a) for the case of integer integration does not apply to the case of...

The focus of the volatility literature on forecasting and the predominance of the conceptually simpler HAR model over long memory stochastic volatility models has led to the fact that the actual degree of memory estimates has rarely been considered. Estimates in the literature range roughly...

We propose a simple test on structural change in long-range dependent time series. It is based on the idea that the test statistic of the standard CUSUM test retains its asymptotic distribution if it is applied to fractionally differenced data. We prove that our approach is asymptotically valid...

It is well known that standard tests for a mean shift are invalid in long-range dependent time series. Therefore, several long memory robust extensions of standard testing principles for a change-in-mean have been proposed in the literature. These can be divided into two groups: those that...

It is well known that intraday volatilities and trading volumes exhibit strong seasonal features. These seasonalities are usually modeled using dummy variables or deterministic functions. Here, we propose a test for seasonal long memory with a known frequency. Using this test, we show that...

We propose a family of self-normalized CUSUM tests for structural change under long memory. The test statistics apply non-parametric kernel-based fixed-b and fixed-m long-run variance estimators and have well-defined limiting distributions that only depend on the long-memory parameter. A Monte...

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo...

We provide a method for distinguishing long-range dependence from deterministic trends such as structural breaks. The method is based on the comparison of standard log-periodogram regression estimation of the memory parameter with its tapered counterpart. The difference of these estimators...

This paper discusses the existence of spurious long memory in common nonlinear time series models, namely Markov switching and threshold models. We describe the asymptotic behavior of the process in terms of autocovariance and autocorrelation function and support the theoretical evidences by...

We have developed a new test against spurious long memory based on the invariance of long memory parameter to aggregation. By using the local Whittle estimator, the statistic takes the supremum among combinations of paired aggregated series. Simulations show that the test performs good in finite...