@article{aastveit2014nowcasting,
  title     = {Nowcasting GDP in real time: A density combination approach},
  author    = {Aastveit, Knut Are and Gerdrup, Karsten R and Jore, Anne Sofie and Thorsrud, Leif Anders},
  journal   = {Journal of Business \& Economic Statistics},
  volume    = {32},
  number    = {1},
  pages     = {48--68},
  year      = {2014},
  publisher = {Taylor \& Francis}
}
@article{berrisch2023modeling,
  title     = {Modeling volatility and dependence of European carbon and energy prices},
  author    = {Berrisch, Jonathan and Pappert, Sven and Ziel, Florian and Arsova, Antonia},
  journal   = {Finance Research Letters},
  volume    = {52},
  pages     = {103503},
  year      = {2023},
  publisher = {Elsevier}
}
@incollection{aastveit2019evolution,
  title     = {The Evolution of Forecast Density Combinations in Economics},
  author    = {Aastveit, Knut Are and Mitchell, James and Ravazzolo, Francesco and van Dijk, Herman K},
  booktitle = {Oxford Research Encyclopedia of Economics and Finance},
  year      = {2019}
}
@article{marcjasz2022distributional,
  title     = {Distributional neural networks for electricity price forecasting},
  author    = {Marcjasz, Grzegorz and Narajewski, Micha{\l} and Weron, Rafa{\l} and Ziel, Florian},
  journal   = {Energy Economics},
  volume    = {125},
  pages     = {106843},
  year      = {2023},
  doi       = {10.1016/j.eneco.2023.106843},
  publisher = {Elsevier}
}
@article{atiya2020does,
  title     = {Why does forecast combination work so well?},
  author    = {Atiya, Amir F},
  journal   = {International Journal of Forecasting},
  volume    = {36},
  number    = {1},
  pages     = {197--200},
  year      = {2020},
  publisher = {Elsevier}
}
@article{atsalakis2016using,
  title     = {Using computational intelligence to forecast carbon prices},
  author    = {Atsalakis, George S},
  journal   = {Applied Soft Computing},
  volume    = {43},
  pages     = {107--116},
  year      = {2016},
  publisher = {Elsevier}
}
@article{bai2020does,
  title     = {Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting},
  author    = {Bai, Lan and Li, Xiafei and Wei, Yu and Wei, Guiwu},
  journal   = {International Journal of Finance \& Economics},
  year      = {2020},
  publisher = {Wiley Online Library}
}
@article{benz2009modeling,
  title     = {Modeling the price dynamics of CO2 emission allowances},
  author    = {Benz, Eva and Tr{\"u}ck, Stefan},
  journal   = {Energy Economics},
  volume    = {31},
  number    = {1},
  pages     = {4--15},
  year      = {2009},
  publisher = {Elsevier}
}
@article{biau2011sequential,
  title     = {Sequential quantile prediction of time series},
  author    = {Biau, G{\'e}rard and Patra, Beno{\^\i}t},
  journal   = {IEEE Transactions on Information Theory},
  volume    = {57},
  number    = {3},
  pages     = {1664--1674},
  year      = {2011},
  publisher = {IEEE}
}
@inproceedings{bousquet2001tracking,
  title        = {Tracking a small set of experts by mixing past posteriors},
  author       = {Bousquet, Olivier and Warmuth, Manfred K},
  booktitle    = {International Conference on Computational Learning Theory},
  pages        = {31--47},
  year         = {2001},
  organization = {Springer}
}
@article{bregere2020online,
  title   = {Online hierarchical forecasting for power consumption data},
  author  = {Br{\'e}g{\`e}re, Margaux and Huard, Malo},
  journal = {arXiv preprint arXiv:2003.00585},
  year    = {2020}
}
@article{busetti2017quantile,
  title     = {Quantile aggregation of density forecasts},
  author    = {Busetti, Fabio},
  journal   = {Oxford Bulletin of Economics and Statistics},
  volume    = {79},
  number    = {4},
  pages     = {495--512},
  year      = {2017},
  publisher = {Wiley Online Library}
}
@book{cesa2006prediction,
  title     = {Prediction, learning, and games},
  author    = {Cesa-Bianchi, Nicolo and Lugosi, G{\'a}bor},
  year      = {2006},
  publisher = {Cambridge university press}
}
@article{cesa2012mirror,
  title   = {Mirror descent meets fixed share (and feels no regret)},
  author  = {Cesa-Bianchi, Nicolo and Gaillard, Pierre and Lugosi, G{\'a}bor and Stoltz, Gilles},
  journal = {Advances in Neural Information Processing Systems},
  volume  = {25},
  pages   = {980--988},
  year    = {2012}
}
@article{cheng2015forecasting,
  title     = {Forecasting with factor-augmented regression: A frequentist model averaging approach},
  author    = {Cheng, Xu and Hansen, Bruce E},
  journal   = {Journal of Econometrics},
  volume    = {186},
  number    = {2},
  pages     = {280--293},
  year      = {2015},
  publisher = {Elsevier}
}
@article{chernozhukov2010quantile,
  title     = {Quantile and probability curves without crossing},
  author    = {Chernozhukov, Victor and Fern{\'a}ndez-Val, Iv{\'a}n and Galichon, Alfred},
  journal   = {Econometrica},
  volume    = {78},
  number    = {3},
  pages     = {1093--1125},
  year      = {2010},
  publisher = {Wiley Online Library}
}
@article{devaine2013forecasting,
  title     = {Forecasting electricity consumption by aggregating specialized experts},
  author    = {Devaine, Marie and Gaillard, Pierre and Goude, Yannig and Stoltz, Gilles},
  journal   = {Machine Learning},
  volume    = {90},
  number    = {2},
  pages     = {231--260},
  year      = {2013},
  publisher = {Springer}
}
@article{dutta2018modeling,
  title     = {Modeling and forecasting the volatility of carbon emission market: The role of outliers, time-varying jumps and oil price risk},
  author    = {Dutta, Anupam},
  journal   = {Journal of Cleaner Production},
  volume    = {172},
  pages     = {2773--2781},
  year      = {2018},
  publisher = {Elsevier}
}
@article{eddelbuettel2014rcpparmadillo,
  title     = {RcppArmadillo: Accelerating R with high-performance C++ linear algebra},
  author    = {Eddelbuettel, Dirk and Sanderson, Conrad},
  journal   = {Computational Statistics \& Data Analysis},
  volume    = {71},
  pages     = {1054--1063},
  year      = {2014},
  publisher = {Elsevier}
}
@article{fragoso2018bayesian,
  title     = {Bayesian model averaging: A systematic review and conceptual classification},
  author    = {Fragoso, Tiago M and Bertoli, Wesley and Louzada, Francisco},
  journal   = {International Statistical Review},
  volume    = {86},
  number    = {1},
  pages     = {1--28},
  year      = {2018},
  publisher = {Wiley Online Library}
}
@inproceedings{gaillard2014second,
  title        = {A second-order bound with excess losses},
  author       = {Gaillard, Pierre and Stoltz, Gilles and Van Erven, Tim},
  booktitle    = {Conference on Learning Theory},
  pages        = {176--196},
  year         = {2014},
  organization = {PMLR}
}
@incollection{gaillard2015forecasting,
  title     = {Forecasting electricity consumption by aggregating experts; how to design a good set of experts},
  author    = {Gaillard, Pierre and Goude, Yannig},
  booktitle = {Modeling and stochastic learning for forecasting in high dimensions},
  pages     = {95--115},
  year      = {2015},
  publisher = {Springer}
}
@inproceedings{gaillard2018efficient,
  title     = {Efficient online algorithms for fast-rate regret bounds under sparsity},
  author    = {Gaillard, Pierre and Wintenberger, Olivier},
  booktitle = {Advances in Neural Information Processing Systems},
  pages     = {7026--7036},
  year      = {2018}
}
@article{garcia2020short,
  title   = {Short-term European Union Allowance price forecasting with artificial neural networks},
  author  = {Garc{\'\i}a, Agust{\'\i}n and Jaramillo-Mor{\'a}n, Miguel A},
  journal = {Entrepreneurship and Sustainability Issues},
  volume  = {8},
  number  = {1},
  pages   = {261},
  year    = {2020}
}
@article{gneiting2007strictly,
  title     = {Strictly proper scoring rules, prediction, and estimation},
  author    = {Gneiting, Tilmann and Raftery, Adrian E},
  journal   = {Journal of the American statistical Association},
  volume    = {102},
  number    = {477},
  pages     = {359--378},
  year      = {2007},
  publisher = {Taylor \& Francis}
}
@article{gneiting2011comparing,
  title     = {Comparing density forecasts using threshold-and quantile-weighted scoring rules},
  author    = {Gneiting, Tilmann and Ranjan, Roopesh},
  journal   = {Journal of Business \& Economic Statistics},
  volume    = {29},
  number    = {3},
  pages     = {411--422},
  year      = {2011},
  publisher = {Taylor \& Francis}
}
@article{gneiting2011making,
  title     = {Making and evaluating point forecasts},
  author    = {Gneiting, Tilmann},
  journal   = {Journal of the American Statistical Association},
  volume    = {106},
  number    = {494},
  pages     = {746--762},
  year      = {2011},
  publisher = {Taylor \& Francis}
}
@article{gneiting2011quantiles,
  title     = {Quantiles as optimal point forecasts},
  author    = {Gneiting, Tilmann},
  journal   = {International Journal of forecasting},
  volume    = {27},
  number    = {2},
  pages     = {197--207},
  year      = {2011},
  publisher = {Elsevier}
}
@article{hansen2008least,
  title     = {Least-squares forecast averaging},
  author    = {Hansen, Bruce E},
  journal   = {Journal of Econometrics},
  volume    = {146},
  number    = {2},
  pages     = {342--350},
  year      = {2008},
  publisher = {Elsevier}
}
@article{hao2020modelling,
  title     = {Modelling of carbon price in two real carbon trading markets},
  author    = {Hao, Yan and Tian, Chengshi and Wu, Chunying},
  journal   = {Journal of Cleaner Production},
  volume    = {244},
  pages     = {118556},
  year      = {2020},
  publisher = {Elsevier}
}
@article{he1997quantile,
  title     = {Quantile curves without crossing},
  author    = {He, Xuming},
  journal   = {The American Statistician},
  volume    = {51},
  number    = {2},
  pages     = {186--192},
  year      = {1997},
  publisher = {Taylor \& Francis}
}
@article{herbster1998tracking,
  title     = {Tracking the best expert},
  author    = {Herbster, Mark and Warmuth, Manfred K},
  journal   = {Machine learning},
  volume    = {32},
  number    = {2},
  pages     = {151--178},
  year      = {1998},
  publisher = {Springer}
}
@article{hsiao2014there,
  title     = {Is there an optimal forecast combination?},
  author    = {Hsiao, Cheng and Wan, Shui Ki},
  journal   = {Journal of Econometrics},
  volume    = {178},
  pages     = {294--309},
  year      = {2014},
  publisher = {Elsevier}
}
@book{hyndman2018forecasting,
  title     = {Forecasting: principles and practice},
  author    = {Hyndman, Rob J and Athanasopoulos, George},
  year      = {2018},
  publisher = {OTexts}
}
@article{jore2010combining,
  title     = {Combining forecast densities from VARs with uncertain instabilities},
  author    = {Jore, Anne Sofie and Mitchell, James and Vahey, Shaun P},
  journal   = {Journal of Applied Econometrics},
  volume    = {25},
  number    = {4},
  pages     = {621--634},
  year      = {2010},
  publisher = {Wiley Online Library}
}
@inproceedings{kakade2008generalization,
  title     = {On the Generalization Ability of Online Strongly Convex Programming Algorithms.},
  author    = {Kakade, Sham M and Tewari, Ambuj},
  booktitle = {NIPS},
  pages     = {801--808},
  year      = {2008}
}
@article{kapetanios2015generalised,
  title     = {Generalised density forecast combinations},
  author    = {Kapetanios, G and Mitchell, James and Price, Simon and Fawcett, Nicholas},
  journal   = {Journal of Econometrics},
  volume    = {188},
  number    = {1},
  pages     = {150--165},
  year      = {2015},
  publisher = {Elsevier}
}
@inproceedings{koolen2015second,
  title     = {Second-order quantile methods for experts and combinatorial games},
  author    = {Koolen, Wouter M and Van Erven, Tim},
  booktitle = {Conference on Learning Theory},
  pages     = {1155--1175},
  year      = {2015}
}
@article{koop2013forecasting,
  title     = {Forecasting the European carbon market},
  author    = {Koop, Gary and Tole, Lise},
  journal   = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
  volume    = {176},
  number    = {3},
  pages     = {723--741},
  year      = {2013},
  publisher = {Wiley Online Library}
}
@article{korotin2019integral,
  title   = {Integral Mixabilty: a Tool for Efficient Online Aggregation of Functional and Probabilistic Forecasts},
  author  = {Korotin, Alexander and V'yugin, Vladimir and Burnaev, Evgeny},
  journal = {arXiv preprint arXiv:1912.07048},
  year    = {2019}
}
@inproceedings{korotin2020mixing,
  title        = {Mixing past predictions},
  author       = {Korotin, Alexander and V’yugin, Vladimir and Burnaev, Evgeny},
  booktitle    = {Conformal and Probabilistic Prediction and Applications},
  pages        = {171--188},
  year         = {2020},
  organization = {PMLR}
}
@article{lichtendahl2013better,
  title     = {Is it better to average probabilities or quantiles?},
  author    = {Lichtendahl Jr, Kenneth C and Grushka-Cockayne, Yael and Winkler, Robert L},
  journal   = {Management Science},
  volume    = {59},
  number    = {7},
  pages     = {1594--1611},
  year      = {2013},
  publisher = {INFORMS}
}
@article{lin2018multi,
  title     = {A multi-model combination approach for probabilistic wind power forecasting},
  author    = {Lin, You and Yang, Ming and Wan, Can and Wang, Jianhui and Song, Yonghua},
  journal   = {IEEE Transactions on Sustainable Energy},
  volume    = {10},
  number    = {1},
  pages     = {226--237},
  year      = {2018},
  publisher = {IEEE}
}
@article{littlestone1994weighted,
  title     = {The weighted majority algorithm},
  author    = {Littlestone, Nick and Warmuth, Manfred K},
  journal   = {Information and computation},
  volume    = {108},
  number    = {2},
  pages     = {212--261},
  year      = {1994},
  publisher = {Elsevier}
}
@article{lu2015jackknife,
  title     = {Jackknife model averaging for quantile regressions},
  author    = {Lu, Xun and Su, Liangjun},
  journal   = {Journal of Econometrics},
  volume    = {188},
  number    = {1},
  pages     = {40--58},
  year      = {2015},
  publisher = {Elsevier}
}
@article{maciejowska2020pca,
  title     = {PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices},
  author    = {Maciejowska, Katarzyna and Uniejewski, Bartosz and Serafin, Tomasz},
  journal   = {Energies},
  volume    = {13},
  number    = {14},
  pages     = {3530},
  year      = {2020},
  publisher = {Multidisciplinary Digital Publishing Institute}
}
@article{mhammedi2019lipschitz,
  title   = {Lipschitz adaptivity with multiple learning rates in online learning},
  author  = {Mhammedi, Zakaria and Koolen, Wouter M and Van Erven, Tim},
  journal = {arXiv preprint arXiv:1902.10797},
  year    = {2019}
}
@article{nowotarski2018recent,
  title     = {Recent advances in electricity price forecasting: A review of probabilistic forecasting},
  author    = {Nowotarski, Jakub and Weron, Rafa{\l}},
  journal   = {Renewable and Sustainable Energy Reviews},
  volume    = {81},
  pages     = {1548--1568},
  year      = {2018},
  publisher = {Elsevier}
}
@article{opschoor2017combining,
  title     = {Combining density forecasts using focused scoring rules},
  author    = {Opschoor, Anne and Van Dijk, Dick and van der Wel, Michel},
  journal   = {Journal of Applied Econometrics},
  volume    = {32},
  number    = {7},
  pages     = {1298--1313},
  year      = {2017},
  publisher = {Wiley Online Library}
}
@article{petropoulos2020forecasting,
  title   = {Forecasting: theory and practice},
  author  = {Petropoulos, Fotios and Apiletti, Daniele and Assimakopoulos, Vassilios and Babai, Mohamed Zied and Barrow, Devon K and Bergmeir, Christoph and Bessa, Ricardo J and Boylan, John E and Browell, Jethro and Carnevale, Claudio and others},
  journal = {arXiv preprint arXiv:2012.03854},
  year    = {2020}
}
@article{raftery2005using,
  title   = {Using Bayesian model averaging to calibrate forecast ensembles},
  author  = {Raftery, Adrian E and Gneiting, Tilmann and Balabdaoui, Fadoua and Polakowski, Michael},
  journal = {Monthly weather review},
  volume  = {133},
  number  = {5},
  pages   = {1155--1174},
  year    = {2005}
}
@article{segnon2017modeling,
  title     = {Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models},
  author    = {Segnon, Mawuli and Lux, Thomas and Gupta, Rangan},
  journal   = {Renewable and Sustainable Energy Reviews},
  volume    = {69},
  pages     = {692--704},
  year      = {2017},
  publisher = {Elsevier}
}
@article{thorey2017online,
  title     = {Online learning with the Continuous Ranked Probability Score for ensemble forecasting},
  author    = {Thorey, Jean and Mallet, Vivien and Baudin, Paul},
  journal   = {Quarterly Journal of the Royal Meteorological Society},
  volume    = {143},
  number    = {702},
  pages     = {521--529},
  year      = {2017},
  publisher = {Wiley Online Library}
}
@article{thorey2018ensemble,
  title     = {Ensemble forecast of photovoltaic power with online CRPS learning},
  author    = {Thorey, Jean and Chaussin, Christophe and Mallet, Vivien},
  journal   = {International Journal of Forecasting},
  volume    = {34},
  number    = {4},
  pages     = {762--773},
  year      = {2018},
  publisher = {Elsevier}
}
@article{tu2011markowitz,
  title     = {Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies},
  author    = {Tu, Jun and Zhou, Guofu},
  journal   = {Journal of Financial Economics},
  volume    = {99},
  number    = {1},
  pages     = {204--215},
  year      = {2011},
  publisher = {Elsevier}
}
@article{v2020online,
  title     = {Online Aggregation of Probabilistic Forecasts Based on the Continuous Ranked Probability Score},
  author    = {V’yugin, VV and Trunov, VG},
  journal   = {Journal of Communications Technology and Electronics},
  volume    = {65},
  number    = {6},
  pages     = {662--676},
  year      = {2020},
  publisher = {Springer}
}
@article{van2018probabilistic,
  title     = {Probabilistic forecasting of solar power, electricity consumption and net load: Investigating the effect of seasons, aggregation and penetration on prediction intervals},
  author    = {Van der Meer, DW and Munkhammar, Joakim and Wid{\'e}n, Joakim},
  journal   = {Solar Energy},
  volume    = {171},
  pages     = {397--413},
  year      = {2018},
  publisher = {Elsevier}
}
@article{vovk1990aggregating,
  title   = {Aggregating strategies},
  author  = {Vovk, Volodimir G},
  journal = {Proc. of Computational Learning Theory, 1990},
  year    = {1990}
}
@book{wahba1990spline,
  title     = {Spline models for observational data},
  author    = {Wahba, Grace},
  year      = {1990},
  publisher = {SIAM}
}
@book{wang2011smoothing,
  title     = {Smoothing splines: methods and applications},
  author    = {Wang, Yuedong},
  year      = {2011},
  publisher = {CRC Press}
}
@article{wang2019jackknife,
  title   = {Jackknife Model Averaging for Composite Quantile Regression},
  author  = {Wang, Miaomiao and Zou, Guohua},
  journal = {arXiv preprint arXiv:1910.12209},
  year    = {2019}
}
@article{wintenberger2017optimal,
  title     = {Optimal learning with Bernstein online aggregation},
  author    = {Wintenberger, Olivier},
  journal   = {Machine Learning},
  volume    = {106},
  number    = {1},
  pages     = {119--141},
  year      = {2017},
  publisher = {Springer}
}
@article{zamo2020sequential,
  title   = {Sequential Aggregation of Probabilistic Forecasts--Applicaton to Wind Speed Ensemble Forecasts},
  author  = {Zamo, Micha{\"e}l and Bel, Liliane and Mestre, Olivier},
  journal = {arXiv preprint arXiv:2005.03540},
  year    = {2020}
}
@article{zhang2020load,
  title     = {Load probability density forecasting by transforming and combining quantile forecasts},
  author    = {Zhang, Shu and Wang, Yi and Zhang, Yutian and Wang, Dan and Zhang, Ning},
  journal   = {Applied Energy},
  volume    = {277},
  pages     = {115600},
  year      = {2020},
  publisher = {Elsevier}
}