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Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices. (2014). Weron, Rafał ; Nowotarski, Jakub.
In: HSC Research Reports.
RePEc:wuu:wpaper:hsc1403.

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  1. A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling. (2023). Musgens, Felix ; Grothe, Oliver ; Mobius, Thomas ; Watermeyer, Mira.
    In: Papers.
    RePEc:arx:papers:2304.09336.

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  2. Conformal prediction interval estimation and applications to day-ahead and intraday power markets. (2021). Ziel, Florian ; Kath, Christopher.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:37:y:2021:i:2:p:777-799.

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  3. Probabilistic mid- and long-term electricity price forecasting. (2018). Ziel, Florian ; Steinert, Rick.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:94:y:2018:i:c:p:251-266.

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  4. Recent advances in electricity price forecasting: A review of probabilistic forecasting. (2018). Weron, Rafał ; Nowotarski, Jakub.
    In: Renewable and Sustainable Energy Reviews.
    RePEc:eee:rensus:v:81:y:2018:i:p1:p:1548-1568.

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  5. Recent advances in electricity price forecasting: A review of probabilistic forecasting. (2016). Weron, Rafał ; Nowotarski, Jakub.
    In: HSC Research Reports.
    RePEc:wuu:wpaper:hsc1607.

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  6. To combine or not to combine? Recent trends in electricity price forecasting. (2016). Weron, Rafał ; Nowotarski, Jakub.
    In: HSC Research Reports.
    RePEc:wuu:wpaper:hsc1601.

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  7. Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging. (2016). Weron, Rafał ; Nowotarski, Jakub ; Maciejowska, Katarzyna.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:3:p:957-965.

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  8. Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging. (2014). Weron, Rafał ; Nowotarski, Jakub ; Maciejowska, Katarzyna.
    In: HSC Research Reports.
    RePEc:wuu:wpaper:hsc1409.

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  9. Fundamental and speculative shocks, what drives electricity prices?. (2014). Maciejowska, Katarzyna.
    In: HSC Research Reports.
    RePEc:wuu:wpaper:hsc1405.

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  10. Electricity price forecasting: A review of the state-of-the-art with a look into the future. (2014). Weron, Rafał.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:30:y:2014:i:4:p:1030-1081.

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References

References cited by this document

  1. Aggarwal, S.K., Saini, L.M., Kumar, A. (2009) Electricity price forecasting in deregulated markets: A review and evaluation, International Journal of Electrical Power and Energy Systems 31, 13-22.
    Paper not yet in RePEc: Add citation now
  2. Andalib, A., Atry, F. (2009) Multi-step ahead forecasts for electricity prices using NARX: A new approach, a critical analysis of one-step ahead forecasts, Energy Conversion and Management 50, 739-747.
    Paper not yet in RePEc: Add citation now
  3. Bai, J. (2003) Inferential theory for factor models of large dimensions, Econometrica 71(1), 135-171.

  4. Bordignon, S., Bunn, D. W., Lisi, F., Nan, F. (2013) Combining dayahead forecasts for British electricity prices, Energy Economics 35, 88-103.

  5. Cao, R., Hart, J.D., Saavedra, A. (2003) Nonparametric maximum likelihood estimators for AR and MA time series, Journal of Statistical Computation and Simulation 73(5), 347-360.
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  6. Christoffersen, P. (1998) Evaluating interval forecasts, International Economic Review 39(4), 841-862.

  7. Koenker R. (2005) Quantile Regression. Cambridge University Press.

  8. Maciejowska, K., Weron, R. (2013) Forecasting of daily electricity spot prices by incorporating intra-day relationships: Evidence form the UK power market. Proceedings of EEM’13, art. no. 6607314.

  9. Misiorek, A., Tr uck, S., Weron, R. (2006) Point and interval forecasting of spot electricity prices: Linear vs. non-linear time series models. Studies in Nonlinear Dynamics and Econometrics 10(3), Article 2.

  10. Nowotarski, J., Raviv, E., Tr uck, S., Weron, R. (2013) An empirical comparison of alternate schemes for combining electricity spot price forecasts. Working Paper, http://ideas.repec.org/p/wuu/wpaper/hsc1307.html.

  11. Nowotarski, J., Weron, R. (2014) Computing electricity spot price prediction intervals using quantile regression and forecast averaging. Working Paper, http://ideas.repec.org/p/wuu/wpaper/hsc1312.html.

  12. Raviv, E., Bouwman, K.E., van Dijk, D. (2013) Forecasting day-ahead electricity prices: Utilizing hourly prices. Tinbergen Institute Discussion Paper 13-068/III. Available at SSRN: http://dx.doi.org/10.2139/ssrn.2266312.

  13. Timmermann, A.G. (2006) Forecast combinations. In: Elliott, G., Granger, C.W., and Timmermann, A., eds., Handbook of Economic Forecasting, Elsevier, 135-196.

  14. Wallis, K.F. (2005) Combining density and interval forecasts: A modest proposal, Oxford Bulletin of Economics and Statistics 67, 983-994.

  15. Weron, R. (2014) A review of electricity price forecasting: The past, the present and the future, International Journal of Forecasting, forthcoming.

  16. Weron, R., Misiorek, A. (2008) Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models, International Journal of Forecasting 24, 744-763. HSC Research Report Series 2014 For a complete list please visit http://ideas.repec.org/s/wuu/wpaper.html 01 Diffusion and adoption of dynamic electricity tariffs: An agent-based modeling approach by Anna Kowalska-Pyzalska, Katarzyna Maciejowska, Katarzyna Sznajd-Weron and Rafał Weron 02 A review of electricity price forecasting: The past, the present and the future by Rafał Weron 03 Merging quantile regression with forecast averaging to obtain more accurate interval forecasts of Nord Pool spot prices by Jakub Nowotarski and Rafał Weron

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