Probabilistic forecasting of electricity spot prices using Factor Quantile Regression Averaging

By Katarzyna Maciejowska, Jakub Nowotarski, Rafal Weron. 2016

163 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/74a62a3fa105041420eb7e522571ee3ed8affe86

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

1. Florian Ziel
2. Jakub Nowotarski
3. Rafal Weron
4. Grzegorz Marcjasz
5. R. Steinert
6. Bartosz Uniejewski
7. Tao Hong
8. Ladislav Kristoufek

In Electrical and Electronic Engineering

1. Rafal Weron
2. Florian Ziel
3. Grzegorz Marcjasz
4. Bartosz Uniejewski
5. Jakub Nowotarski
6. R. Steinert
7. Tao Hong
8. Bidong Liu

In Management Science and Operations Research

1. Florian Ziel
2. Rafal Weron
3. Jakub Nowotarski
4. R. Steinert
5. Bartosz Uniejewski
6. Grzegorz Marcjasz
7. Tao Hong
8. Bidong Liu

Citations in the corpus

• Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure (2015, methodology): “As mentioned in many applications, like in [14] or [15], simple autoregressive models with a fixed regression structure are used.”
• Probabilistic Load Forecasting via Quantile Regression Averaging on Sister Forecasts (2017, background): “So far it has been only applied to electricity price forecasting [22]–[24].”
• On the importance of the long-term seasonal component in day-ahead electricity price forecasting (2016, methodology): “The very good forecasting performance of QRA has been verified by a number of authors (Gaillard et al., 2016; Maciejowska and Nowotarski, 2016; Maciejowska et al., 2016), not only in the area of EPF (Liu et al., 2017; Zhang et al., 2016).”
• Electricity price forecasting using sale and purchase curves: The X-Model (2015, methodology): “The considered model is a simple regression approach and similar to the basic autoregressive model as used in Weron and Misiorek (2008), Maciejowska et al. (2016) or Ziel (2016a) for modeling the electricity price.”
• Recent advances in electricity price forecasting: A review of probabilistic forecasting (2016, methodology): “A number of methods can be used for this purpose, the most popular take into account both the point forecast and the corresponding error [24, 29]: the center of the PI at the (1 − α) confidence level is set equal to P̂t and its bounds are defined by the α2 th and (1 − α 2 )th quantiles of the cumula”