Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/307743 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
Hannover Economic Papers (HEP) No. 729
Verlag: 
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Hannover
Zusammenfassung: 
We propose a test to detect a forecast accuracy breakdown in a long memory time series and provide theoretical and simulation evidence on the memory transfer from the time series to the forecast residuals. The proposed method uses a double sup-Wald test against the alternative of a structural break in the mean of an outof-sample loss series. To address the problem of estimating the long-run variance under long memory, a robust estimator is applied. The corresponding breakpoint results from a long memory robust CUSUM test. The finite sample size and power properties of the test are derived in a Monte Carlo simulation. A monotonic power function is obtained for the fixed forecasting scheme. In our practical application, we find that the global energy crisis that began in 2021 led to a forecast break in European electricity prices, while the results for the U.S. are mixed.
Schlagwörter: 
Electricity prices
Forecast failure
Local power
Out-of-sample forecast
Structural change
Dokumentart: 
Working Paper

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