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Atheoretical regression trees (ART) are applied to detect changes in the mean of a stationary long memory time series when location and number are unknown. It is shown that the BIC, which is almost always used as a pruning method, does not operate well in the long memory framework. A new method...
Persistent link: https://www.econbiz.de/10003930919
Detecting the number of breaks in the mean can be challenging when it comes to the long memory framework. Tree-based procedures can be applied to time series when the location and number of mean shifts are unknown and estimate the breaks consistently though with possible overfitting. For pruning...
Persistent link: https://www.econbiz.de/10010294423
We consider the detection of a change in persistence of a long range dependent time series. The usual approach is to use one-shot tests to detect a change in persistence a posteriori in a historical data set. However, as breaks can occur at any given time and data arrives steadily it is...
Persistent link: https://www.econbiz.de/10010294446
We show that the CUSUM-squared based test for a change in persistence by Leybourne et al. (2007) is not robust against shifts in the mean. A mean shift leads to serious size distortions. Therefore, adjusted critical values are needed when it is known that the data generating process has a mean...
Persistent link: https://www.econbiz.de/10010270042
Atheoretical regression trees (ART) are applied to detect changes in the mean of a stationary long memory time series when location and number are unknown. It is shown that the BIC, which is almost always used as a pruning method, does not operate well in the long memory framework. A new method...
Persistent link: https://www.econbiz.de/10010270050
We show that the CUSUM-squared based test for a change in persistence by Leybourne et al. (2007) is not robust against shifts in the mean. A mean shift leads to serious size distortions. Therefore, adjusted critical values are needed when it is known that the data generating process has a mean...
Persistent link: https://www.econbiz.de/10003857663
Persistent link: https://www.econbiz.de/10009612474
Persistent link: https://www.econbiz.de/10009739414
Persistent link: https://www.econbiz.de/10009739440
We consider the detection of a change in persistence of a long range dependent time series. The usual approach is to use one-shot tests to detect a change in persistence a posteriori in a historical data set. However, as breaks can occur at any given time and data arrives steadily it is...
Persistent link: https://www.econbiz.de/10009291786