Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices
By Eran Raviv, Kees E. Bouwman, Dick Van Dijk. 2013
129 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/a82cd42ad219f82f1be9cee4dc64d23638fc51e3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Jakub Nowotarski
- Rafal Weron
- Katarzyna Maciejowska
- Florian Huber
- Florian Ziel
- John M. Maheu
- Anastasios Panagiotelis
- Ruben Loaiza-Maya
In Electrical and Electronic Engineering
- Jakub Nowotarski
- Rafal Weron
- Katarzyna Maciejowska
- Florian Ziel
- Anastasios Panagiotelis
- Ljupco Kocarev
- Sonja Filiposka
- Aleksandar Dedinec
Citations in the corpus
- Bayesian forecasting in economics and finance: A modern review (2022, result): “…the early literature cited before found somewhat ambiguous results when comparing Bayesian VARs to classical alternatives, more recent work finds evidence in favour of a Bayesian approach; see Raviv et al. (2015) for point forecasts and Gianfreda et al. (2020) for both point and density forecasts.”
- Electricity price forecasting: A review of the state-of-the-art with a look into the future (2014, unknown): “To simplify this task even more, in some studies the forecasts are performed separately across the hours, eliminating the need for explicit modeling of the daily price profile but leading to 24 (or 48) sets of parameters (see e.g. Karakatsani and Bunn, 2008, 2010; Misiorek et al., 2006; Raviv et al.”
- Deep belief network based electricity load forecasting: An analysis of Macedonian case (2016, methodology): “[16] the day-ahead electricity prices are forecasted using data at hourly level and in Ref.”
- Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging (2016, methodology): “Indeed, as Bordignon et al. (2013), Nowotarski et al. (2013) and Raviv et al. (2013) report, combining does lead to more accurate (on average) and more robust electricity price point forecasts.”
- An empirical comparison of alternate schemes for combining electricity spot price forecasts (2013, unknown): “These findings complement results from Raviv et al. (2013) who also document favorable performance of constrained least squares estimation for Nord Pool data.”