Long‐term prediction intervals with many covariates
Author
Abstract
Suggested Citation
DOI: 10.1111/jtsa.12629
Download full text from publisher
References listed on IDEAS
- Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015.
"Forecasting day-ahead electricity prices: Utilizing hourly prices,"
Energy Economics, Elsevier, vol. 50(C), pages 227-239.
- Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
- Hyndman, Rob J. & Khandakar, Yeasmin, 2008.
"Automatic Time Series Forecasting: The forecast Package for R,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
- Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
- Kitsul, Yuriy & Wright, Jonathan H., 2013.
"The economics of options-implied inflation probability density functions,"
Journal of Financial Economics, Elsevier, vol. 110(3), pages 696-711.
- Jonathan Wright & Yuriy Kitsul, 2012. "The Economics of Options-Implied Inflation Probability Density Functions," 2012 Meeting Papers 174, Society for Economic Dynamics.
- Yuriy Kitsul & Jonathan H. Wright, 2012. "The Economics of Options-Implied Inflation Probability Density Functions," NBER Working Papers 18195, National Bureau of Economic Research, Inc.
- Yuriy Kitsul & Jonathan H. Wright, 2012. "The Economics of Options-Implied Inflation Probability Density Functions," Economics Working Paper Archive 600, The Johns Hopkins University,Department of Economics.
- Bansal, Ravi & Kiku, Dana & Yaron, Amir, 2016.
"Risks for the long run: Estimation with time aggregation,"
Journal of Monetary Economics, Elsevier, vol. 82(C), pages 52-69.
- Ravi Bansal & Dana Kiku & Amir Yaron, 2012. "Risks For the Long Run: Estimation with Time Aggregation," NBER Working Papers 18305, National Bureau of Economic Research, Inc.
- Alvaro Cartea & Marcelo Figueroa, 2005.
"Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality,"
Applied Mathematical Finance, Taylor & Francis Journals, vol. 12(4), pages 313-335.
- Alvaro Cartea & Marcelo Gustavo Figueroa, 2005. "Pricing in Electricity Markets: a Mean Reverting Jump Diffusion Model with Seasonality," Birkbeck Working Papers in Economics and Finance 0507, Birkbeck, Department of Economics, Mathematics & Statistics.
- Alvaro Cartea & Marcelo_Gustavo Figueroa, 2005. "Pricing in Electricity Markets: a Mean Reverting Jump Diffusion Model with Seasonality," Finance 0501011, University Library of Munich, Germany, revised 12 Sep 2005.
- Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
- Taylor, James W., 2010. "Reply to the discussion of: Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles," International Journal of Forecasting, Elsevier, vol. 26(4), pages 658-660, October.
- Dehling, Herold & Fried, Roland & Sharipov, Olimjon Sh. & Vogel, Daniel & Wornowizki, Max, 2013. "Estimation of the variance of partial sums of dependent processes," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 141-147.
- Bierbrauer, Michael & Menn, Christian & Rachev, Svetlozar T. & Truck, Stefan, 2007. "Spot and derivative pricing in the EEX power market," Journal of Banking & Finance, Elsevier, vol. 31(11), pages 3462-3485, November.
- Weron, Rafal & Misiorek, Adam, 2008.
"Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models,"
International Journal of Forecasting, Elsevier, vol. 24(4), pages 744-763.
- Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," MPRA Paper 10428, University Library of Munich, Germany.
- Pesaran, M. Hashem & Pick, Andreas & Pranovich, Mikhail, 2013. "Optimal forecasts in the presence of structural breaks," Journal of Econometrics, Elsevier, vol. 177(2), pages 134-152.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018.
"On the Comparison of Interval Forecasts,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 953-965, November.
- Ross Askanazi & Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2018. "On the Comparison of Interval Forecasts," PIER Working Paper Archive 18-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 02 Aug 2018.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
- Taylor, James W., 2010. "Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles," International Journal of Forecasting, Elsevier, vol. 26(4), pages 627-646, October.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Huurman, Christian & Ravazzolo, Francesco & Zhou, Chen, 2012. "The power of weather," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3793-3807.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Kejin Wu & Sayar Karmakar & Rangan Gupta, 2023.
"GARCHX-NoVaS: A Model-free Approach to Incorporate Exogenous Variables,"
Papers
2308.13346, arXiv.org, revised Sep 2024.
- Kejin Wu & Sayar Karmakar & Rangan Gupta, 2024. "GARCHX-NoVaS: A Model-Free Approach to Incorporate Exogenous Variables," Working Papers 202425, University of Pretoria, Department of Economics.
- Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
- Paul Ghelasi & Florian Ziel, 2024. "From day-ahead to mid and long-term horizons with econometric electricity price forecasting models," Papers 2406.00326, arXiv.org, revised Aug 2024.
- Kejin Wu & Sayar Karmakar & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Stock Market Volatility Over a Century in an Emerging Market Economy: The Case of South Africa," Working Papers 202326, University of Pretoria, Department of Economics.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Sayar Karmakar & Marek Chudy & Wei Biao Wu, 2020. "Long-term prediction intervals with many covariates," Papers 2012.08223, arXiv.org, revised Sep 2021.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- G P Girish & Aviral Kumar Tiwari, 2016. "A comparison of different univariate forecasting models forSpot Electricity Price in India," Economics Bulletin, AccessEcon, vol. 36(2), pages 1039-1057.
- Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020.
"Comparing the forecasting performances of linear models for electricity prices with high RES penetration,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Papers 1801.01093, arXiv.org, revised Nov 2019.
- Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016.
"Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads,"
Energy Economics, Elsevier, vol. 60(C), pages 79-96.
- Yunus Emre Ergemen & Niels Haldrup & Carlos Vladimir Rodríguez-Caballero, 2015. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," CREATES Research Papers 2015-58, Department of Economics and Business Economics, Aarhus University.
- Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2019. "Forecasting daily electricity prices with monthly macroeconomic variables," Working Paper Series 2250, European Central Bank.
- M. Chudý & S. Karmakar & W. B. Wu, 2020. "Long-term prediction intervals of economic time series," Empirical Economics, Springer, vol. 58(1), pages 191-222, January.
- Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022.
"Forecasting: theory and practice,"
International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
- Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
- Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023.
"Forecasting electricity prices with expert, linear, and nonlinear models,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
- Anna Gloria Billé & Angelica Gianfreda & Filippo Del Grosso & Francesco Ravazzolo, 2021. "Forecasting Electricity Prices with Expert, Linear and Non-Linear Models," Working Paper series 21-20, Rimini Centre for Economic Analysis.
- Afanasyev, Dmitriy O. & Fedorova, Elena A., 2019. "On the impact of outlier filtering on the electricity price forecasting accuracy," Applied Energy, Elsevier, vol. 236(C), pages 196-210.
- Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015.
"Forecasting day-ahead electricity prices: Utilizing hourly prices,"
Energy Economics, Elsevier, vol. 50(C), pages 227-239.
- Eran Raviv & Kees E. Bouwman & Dick van Dijk, 2013. "Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices," Tinbergen Institute Discussion Papers 13-068/III, Tinbergen Institute.
- Umut Ugurlu & Ilkay Oksuz & Oktay Tas, 2018. "Electricity Price Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 11(5), pages 1-23, May.
- Alexandre Lucas & Konstantinos Pegios & Evangelos Kotsakis & Dan Clarke, 2020. "Price Forecasting for the Balancing Energy Market Using Machine-Learning Regression," Energies, MDPI, vol. 13(20), pages 1-16, October.
- Auer, Benjamin R., 2016. "How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models," Energy Policy, Elsevier, vol. 98(C), pages 621-628.
- Jakub Nowotarski & Rafał Weron, 2015.
"Computing electricity spot price prediction intervals using quantile regression and forecast averaging,"
Computational Statistics, Springer, vol. 30(3), pages 791-803, September.
- Jakub Nowotarski & Rafal Weron, 2013. "Computing electricity spot price prediction intervals using quantile regression and forecast averaging," HSC Research Reports HSC/13/12, Hugo Steinhaus Center, Wroclaw University of Technology.
- Rafal Weron & Florian Ziel, 2018.
"Electricity price forecasting,"
HSC Research Reports
HSC/18/08, Hugo Steinhaus Center, Wroclaw University of Technology.
- Katarzyna Maciejowska & Rafal Weron, 2019. "Electricity price forecasting," HSC Research Reports HSC/19/01, Hugo Steinhaus Center, Wroclaw University of Technology.
- Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023.
"Are low frequency macroeconomic variables important for high frequency electricity prices?,"
Economic Modelling, Elsevier, vol. 120(C).
- Claudia Foroni & Francesco Ravazzolo & Luca Rossini, 2020. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Papers 2007.13566, arXiv.org, revised Dec 2022.
- Segnon Mawuli & Lau Chi Keung & Wilfling Bernd & Gupta Rangan, 2022.
"Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data,"
Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(1), pages 73-98, February.
- Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data," CQE Working Papers 6117, Center for Quantitative Economics (CQE), University of Muenster.
- Mawuli Segnon & Chi Keung Lau & Bernd Wilfling & Rangan Gupta, 2017. "Are Multifractal Processes Suited to Forecasting Electricity Price Volatility? Evidence from Australian Intraday Data," Working Papers 201739, University of Pretoria, Department of Economics.
- Mauro Bernardi & Francesco Lisi, 2020. "Point and Interval Forecasting of Zonal Electricity Prices and Demand Using Heteroscedastic Models: The IPEX Case," Energies, MDPI, vol. 13(23), pages 1-34, November.
- Michail I. Seitaridis & Nikolaos S. Thomaidis & Pandelis N. Biskas, 2021. "Fundamental Responsiveness in European Electricity Prices," Energies, MDPI, vol. 14(22), pages 1-14, November.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jtsera:v:43:y:2022:i:4:p:587-609. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.