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Krzysztof Drachal and Michal Pawlowski
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa...
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Silvia Golia, Luigi Grossi and Matteo Pelagatti
In this paper we assess how intra-day electricity prices can improve the prediction of zonal day-ahead wholesale electricity prices in Italy. We consider linear autoregressive models with exogenous variables (ARX) with and without interactions among pred...
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Sumathi Kumaraswamy, Yomna Abdulla and Shrikant Krupasindhu Panigrahi
Recurrent stock market fall and rise sequel by COVID-19, rising global inflation, increase in Fed interest rates, the unprecedented meltdown of technology stocks, fear of trade wars, tightening of governments? fiscal policies call for a new trend in inte...
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Denis E. Baskan, Daniel Meyer, Sebastian Mieck, Leonhard Faubel, Benjamin Klöpper, Nika Strem, Johannes A. Wagner and Jan J. Koltermann
In recent years, energy prices have become increasingly volatile, making it more challenging to predict them accurately. This uncertain market trend behavior makes it harder for market participants, e.g., power plant dispatchers, to make reliable decisio...
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Tugçin Kirant Mitic and Karsten Voss
Electricity generation from renewable energy reduces greenhouse gas emissions and, in the long term, the cost of electricity in power grids. However, there is currently no strong positive correlation between greenhouse gas intensity and electricity spot ...
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Georgios Chantzis, Effrosyni Giama and Agis M. Papadopoulos
The EU energy and climate policy has set quantitative goals for decarbonization based on the energy efficiency and the evolution of energy systems. The utilization of demand side flexibility can help towards this direction and achieve the target of highe...
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Anna Szczepanska-Przekota
Mutual interactions between the agricultural commodities futures market and the spot market are some of the most important relationships that can be observed between the financial market and the real economy. The process of the flow of price impulses bet...
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Stefan Claus and Massimo Stella
The ability to spot key ideas, trends, and relationships between them in documents is key to financial services, such as banks and insurers. Identifying patterns across vast amounts of domain-specific reports is crucial for devising efficient and targete...
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Julien Chevallier, Dominique Guégan and Stéphane Goutte
This paper focuses on forecasting the price of Bitcoin, motivated by its market growth and the recent interest of market participants and academics. We deploy six machine learning algorithms (e.g., Artificial Neural Network, Support Vector Machine, Rando...
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Congxin Wu, Xinyu Wang, Shan Luo, Jing Shan and Feng Wang
This article takes into account the form of mixed data as well as the peak and thick tail characteristics contained in the data characteristics, expands the GARCH-MIDAS (Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling) model...
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