Forecast evaluation improving using the simplest methods of individual forecasts’ combination
DOI:
https://doi.org/10.22394/1993-7601-2024-74-78-103Keywords:
комбинирование прогнозов, объединение прогнозов, цены на нефть, цены на алюминий, цены на золото, цены на никель, цены на медьAbstract
Combining forecasts is considered the easiest way to improve the forecast quality compared to individual models. In this paper, we test the capabilities of the simplest methods of combination, such as simple averages and estimates based on the standard error of previous forecasts, to improve the performance of short-run forecasts of five resource price indicators (oil and metals). The basis of the work is the Gaidar Institute forecasts database, which provides the database of primary forecasts and allows you to calculate their combinations in real time. Based on the obtained results we conclude that even the simplest methods of combination are a way to improve the accuracy of forecasts. In addition, in the case of resource prices, one can even single out a group of methods (namely, combining with weights inversely proportional to the squared errors of individual forecasts) that provide the maximum gain in quality for the most periods.Agencies
Статья подготовлена в рамках НИР Государственного задания РАНХиГС 2024 г.Downloads
References
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Claeskens G., Magnus J. R., Vasnev A. L., Wang W. (2016). The forecast combination puzzle: A simple theoretical explanation. International Journal of Forecasting, 32 (3), 754–762. DOI: 10.13140/2.1.2532.2887.
Clemen R. T. (1989). Combining forecasts: A review and annotated bibliography. International Journal
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Elliott G., Timmermann A. (2004). Optimal forecast combinations under general loss functions and forecast
error distributions. Journal of Econometrics, 122 (1), 47–79. DOI: 10.1016/j.jeconom.2003.10.019.
Fritz R. G., Brandon C., Xander J. (1984). Combining time-series and econometric forecast of tourism
activity. Annals of Tourism Research, 11 (2), 219–229. DOI: 10.1016/0160‑7383(84)90071‑9.
Genre V., Kenny G., Meyler A., Timmermann A. (2013). Combining expert forecasts: Can anything beat the simple average? International Journal of Forecasting, 29 (1), 108–121. DOI: 10.1016/j.ijforecast.2012.06.004.
Granger C. W. J. (1989). Combining forecasts — twenty years later. Journal of Forecasting, 8 (3), 167–173. DOI: 10.1002/for.3980080303.
Granger C. W. J., Newbold P. (1974). Experience with forecasting univariate time series and the combination of forecasts. Journal of The Royal Statistical Society: Series A (General), 137 (2), 131–164. DOI: 10.2307/2344546.
Granger C. W. J., Newbold P. (1977). Forecasting economic time series. New York: Academic Press.
Granger C. W. J., Ramanathan R. (1984). Improved methods of combining forecasting. Journal
of Forecasting, 3 (2), 197–204. DOI: 10.1002/for.3980030207.
Greene M. N., Howrey E. P., Hymans S. H. (1985). The use of outside information in econometric forecasting. In: E. Kuh and D. A. Belsley (eds.). Model Reliability. Cambridge: MIT Press.
Lichtendahl Jr. K.C., Winkler R. L. (2020). Why do some combinations perform better than others? International Journal of Forecasting, 36 (1), 142–149. DOI: 10.1016/j.ijforecast.2019.03.027.
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Makridakis S., Spiliotis E., Assimakopoulos V. (2022). The M5 accuracy competition: Results, findings and conclusions. International Journal of Forecasting, 38, 1346–1364. DOI: 10.1016/j.ijforecast.2021.11.013.
Radchenko P., Vasnev A., Wang W. (2023). Too similar to combine? On negative weights in forecast combination. International Journal of Forecasting, 39 (1), 18–38. DOI: 10.1016/j.ijforecast.2021.08.002.
Reid D. J. (1969). A comparative study of time-series prediction techniques on economic data. Ph. D. Thesis, University of Nottingham.
Smith J., Wallis K. F. (2009). A
simple explanation of the forecast combination puzzle. Oxford Bulletin
of Economics and Statistics, 71 (3), 331–355. DOI: 10.1111/j.1468‑0084.2008.00541.x.
Stock J. H., Watson M. W. (1999). Forecasting inflation. Journal of Monetary Economics, 44, 293–375.
DOI: 10.1016/S0304‑3932(99)00027‑6.
Stock J. H., Watson M. W. (2004). Combination forecasts of output growth in a seven- country data set.
Journal of Forecasting, 23, 405–430. DOI: 10.1002/for.928.
Winkler R. L., Clemen R. T. (1992). Sensitivity of weights in combining forecasts. Operations Research, 40 (3), 609–614. DOI: 10.1287/opre.40.3.609.
Winkler R. L., Makridakis S. (1983). The combination of forecasts. Journal of the Royal Statistical Society: Series A (General), 146 (2), 150–157. DOI: 10.2307/2982011.
Wang X., Hyndman R. J., Li F., Kang Y. (2023). Forecast combinations: An over 50‑year review. International Journal of Forecasting, 39 (4), 1518–1547. DOI: 10.1016/j.ijforecast.2022.11.005.
