The power of weather

DOI10.1016/j.csda.2010.06.021zbMath1254.86026OpenAlexW3121154541MaRDI QIDQ1927158

Christian Huurman, Chen Zhou, Francesco Ravazzolo

Publication date: 30 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.06.021

zbMATH Keywords

GARCH modelselectricity pricesweather forecastspoint and density forecasts

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Geostatistics (86A32)

Related Items (3)

Pricing electricity day-ahead cap futures with multifactor skew-t densities ⋮ Long‐term prediction intervals with many covariates ⋮ Are multifractal processes suited to forecasting electricity price volatility? Evidence from Australian intraday data

Cites Work

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• Forecasting electricity demand in Japan: a Bayesian spatial autoregressive ARMA approach
• Combining inflation density forecasts
• Periodic Seasonal Reg-ARFIMA–GARCH Models for Daily Electricity Spot Prices
• Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models

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