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Forecasting of volatility and risk premia in electricity markets

Thomas K. Kloster, Fred Espen Benth

arXiv 4 Jun 2026 · Finance — General

arXiv:2606.05991 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study forecasting of the realized covariation in electricity markets. The realized covariation in this context is a matrix-valued representation of the latent infinite-dimensional covariance operator and a parsimonious matrix-HAR type model is constructed to facilitate estimation. We test the model on one-week ahead forecasts of the weekly realized covariation and find that the inclusion of longer time horizons and renewable generation information adds important predictive power. We also investigate the prediction of risk premia in electricity forward markets and find that our variance forecasts provide substantially improved forecasts of spread risk premia compared to standard methods relying on backward looking volatility.

Citation extraction

16
references
35
in-text mentions
16
distinct cited
4
self-citations
8,404
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Kloster, Thomas K. and Benth, Fred Espen (2026) The fine structure of electricity price volatility self1.000115100%
2Hendrik Bessembinder and Michael L. Lemmon (2002) Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets1.00063100%
3Matias Quiroz and Laleh Tafakori and Hans Manner (2024) Forecasting realized covariances using HAR-type models0.73732100%
4Kloster, Thomas K (2026) An ambit field framework for the full panel of day-ahead electricity prices self0.64422100%
5Christian Redl and Reinhard Haas and Claus Huber and Bernhard Böhm (2009) Price formation in electricity forward markets and the relevance of systematic forecast errors0.51121100%
6Archakov, Ilya and Hansen, Peter Reinhard (2021) A New Parametrization of Correlation Matrices0.40511100%
7Fred Espen Benth and Dennis Schroers and Almut E.D. Veraart (2022) A weak law of large numbers for realised covariation in a Hilbert space setting self0.40511100%
8Benth, Fred Espen and Schroers, Dennis and Veraart, Almut E. D (2024) A feasible central limit theorem for realised covariation of SPDEs in the context of functional data self0.40511100%
9Bollerslev, Tim and Patton, Andrew J. and Quaedvlieg, Rogier (2016) Exploiting the errors: A simple approach for improved volatility forecasting0.40511100%
10Christensen, Kim and Siggaard, Mathias and Veliyev, Bezirgen (2023) A Machine Learning Approach to Volatility Forecasting0.40511100%

Showing the top 10 of 16 scored citations.