8 citations · 8 across the 5 of their papers we have counts for
5 papers
Data-driven Calibration Sample Selection and Forecast Combination in Electricity Price Forecasting: An Application of the ARHNN Method
Tomasz Serafin, Weronika Nitka
Calibration sample selection and forecast combination are two simple yet powerful tools used in forecasting. They can be combined with a variety of models to significantly improve…
Probabilistic intraday electricity price forecasting using generative machine learning
Jieyu Chen, Sebastian Lerch, Melanie Schienle +2
The growing importance of intraday electricity trading in Europe calls for improved price forecasting and tailored decision-support tools. In this paper, we propose a novel generat…
Ranking probabilistic forecasting models with different loss functions
Tomasz Serafin, Bartosz Uniejewski
In this study, we introduced various statistical performance metrics, based on the pinball loss and the empirical coverage, for the ranking of probabilistic forecasting models. We…
Probabilistic forecasting with a hybrid Factor-QRA approach: Application to electricity trading
Katarzyna Maciejowska, Tomasz Serafin, Bartosz Uniejewski
This paper presents a novel hybrid approach for constricting probabilistic forecasts that combines both the Quantile Regression Averaging (QRA) method and the factor-based averagin…
Note on simulation pricing of -options
Zbigniew Palmowski, Tomasz Serafin
In this work, we adapt a Monte Carlo algorithm introduced by Broadie and Glasserman (1997) to price a -option. This method is based on the simulated price tree that comes from d…