Multivariate probabilistic forecasting of electricity prices with trading applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10491160" target="_blank" >RIV/00216208:11320/25:10491160 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=AzDiI1-yf5" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=AzDiI1-yf5</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.eneco.2024.108008" target="_blank" >10.1016/j.eneco.2024.108008</a>
Alternative languages
Result language
angličtina
Original language name
Multivariate probabilistic forecasting of electricity prices with trading applications
Original language description
This study extends recently introduced neural networks approach, based on a regularized distributional multilayer perceptron (DMLP) technique fora multivariate case electricity price forecasting. The performance of a fully connected architecture and a LSTM architecture of neural networks are tested. Different from previous studies we incorporate dependence between multiple exchanges (EPEX and Nord Pool). The empirical data application analyzes two auctions in the day-ahead electricity market for the United Kingdom market. Along with statistical evaluation of probabilistic forecasts we develop a flexible bidding strategy based on risk-adjusted investor utility function. The trading application leverages the differences of the two exchanges by having long/short positions in both. Our findings demonstrate while DMLP shows similar performance compared to the benchmarks, the algorithm is considerably less computationally costly. LASSO Quantile Regression is better in terms if statistical evaluation of distributional fit, while DMLP outperforms in terms of Sharpe ratio (by 18%) in the trading application.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50201 - Economic Theory
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Energy Economics
ISSN
0140-9883
e-ISSN
1873-6181
Volume of the periodical
141
Issue of the periodical within the volume
Jan 2025
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
24
Pages from-to
108008
UT code for WoS article
001360612500001
EID of the result in the Scopus database
2-s2.0-85209084463