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