Testing for a Forecast Accuracy Breakdown under Long Memory
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914947220373504 |
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| author | Kreye, Jannik Sibbertsen, Philipp |
| author_facet | Kreye, Jannik Sibbertsen, Philipp |
| contents | 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 out-of-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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_07087 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Testing for a Forecast Accuracy Breakdown under Long Memory Kreye, Jannik Sibbertsen, Philipp Econometrics Applications 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 out-of-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. |
| title | Testing for a Forecast Accuracy Breakdown under Long Memory |
| topic | Econometrics Applications |
| url | https://arxiv.org/abs/2409.07087 |