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Testing for a Forecast Accuracy Breakdown under Long Memory

Jannik Kreye, Philipp Sibbertsen

arXiv 11 Sep 2024 · Econometrics

arXiv:2409.07087 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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.

Citation extraction

22
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appendix boundary found by appendix_titled_section at “Appendix” · 86% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Perron, P. and Y. Yamamoto (2021) Testing for changes in forecasting performance0.9507486%
2Giacomini, R. and B. Rossi (2009) Detecting and predicting forecast breakdowns0.81142100%
3Kruse, R., C. Leschinski, and M. Will (2018) Comparing predictive accuracy under long memory, with an application to volatility forecasting0.64422100%
4Bai, J. and P. Perron (1998) Estimating and testing linear models with multiple structural changes0.64422100%
5Robinson, P. M (1995) Gaussian semiparametric estimation of long range dependence0.64422100%
6Chambers, M. J (1998) Long memory and aggregation in macroeconomic time series0.5113233%
7Leschinski, C (2017) On the memory of products of long range dependent time series0.5113233%
8Abadir, K. M., W. Distaso, and L. Giraitis (2009) Two estimators of the long-run variance: beyond short memory0.51121100%
9Andrews, D. W (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation0.40511100%
10Christoffersen, P. F. and F. X. Diebold (1997) Optimal prediction under asymmetric loss0.40511100%

Showing the top 10 of 22 scored citations.