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We show that tests for a break in the persistence of a time series in the classical I(0) - I(1) framework have serious size distortions when the actual data generating process exhibits long-range dependencies. We prove that the limiting distribution of a CUSUM of squares based test depends on...
Persistent link: https://www.econbiz.de/10003575487
Prediction in time series models with a trend requires reliable estimation of the trend function at the right end of the observed series. Local polynomial smoothing is a suitable tool because boundary corrections are included implicitly. However, outliers may lead to unreliable estimates, if...
Persistent link: https://www.econbiz.de/10011544323
We investigate the behavior of nonparametric kernel M-estimators in the presence of long-memory errors. The optimal bandwidth and a central limit theorem are obtained. It turns out that in the Gaussian case all kernel M-estimators have the same limiting normal distribution. The motivation behind...
Persistent link: https://www.econbiz.de/10011544721
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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...
Persistent link: https://www.econbiz.de/10011715842
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...
Persistent link: https://www.econbiz.de/10011673153
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...
Persistent link: https://www.econbiz.de/10011655296
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The peaks-over-threshold (POT) method has a long tradition in modelling extremes in environmental variables. However, the assumption of independently and identically distributed (iid) data is likely to be violated in practical settings, leading to clustering of high-threshold exceedances. These...
Persistent link: https://www.econbiz.de/10012629924
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