Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market
Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard...
Ausführliche Beschreibung
Autor*in: |
Rainer Baule [verfasserIn] Michael Naumann [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2021 |
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Übergeordnetes Werk: |
In: Energies - MDPI AG, 2008, 14(2021), 22, p 7531 |
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Übergeordnetes Werk: |
volume:14 ; year:2021 ; number:22, p 7531 |
Links: |
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DOI / URN: |
10.3390/en14227531 |
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Katalog-ID: |
DOAJ079170277 |
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10.3390/en14227531 doi (DE-627)DOAJ079170277 (DE-599)DOAJ84a2846eafbe48aaa6b8aaa2416aabfd DE-627 ger DE-627 rakwb eng Rainer Baule verfasserin aut Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. intraday electricity market renewable energies electricity price volatility electricity price dispersion Technology T Michael Naumann verfasserin aut In Energies MDPI AG, 2008 14(2021), 22, p 7531 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:22, p 7531 https://doi.org/10.3390/en14227531 kostenfrei https://doaj.org/article/84a2846eafbe48aaa6b8aaa2416aabfd kostenfrei https://www.mdpi.com/1996-1073/14/22/7531 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 22, p 7531 |
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10.3390/en14227531 doi (DE-627)DOAJ079170277 (DE-599)DOAJ84a2846eafbe48aaa6b8aaa2416aabfd DE-627 ger DE-627 rakwb eng Rainer Baule verfasserin aut Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. intraday electricity market renewable energies electricity price volatility electricity price dispersion Technology T Michael Naumann verfasserin aut In Energies MDPI AG, 2008 14(2021), 22, p 7531 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:22, p 7531 https://doi.org/10.3390/en14227531 kostenfrei https://doaj.org/article/84a2846eafbe48aaa6b8aaa2416aabfd kostenfrei https://www.mdpi.com/1996-1073/14/22/7531 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 22, p 7531 |
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10.3390/en14227531 doi (DE-627)DOAJ079170277 (DE-599)DOAJ84a2846eafbe48aaa6b8aaa2416aabfd DE-627 ger DE-627 rakwb eng Rainer Baule verfasserin aut Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. intraday electricity market renewable energies electricity price volatility electricity price dispersion Technology T Michael Naumann verfasserin aut In Energies MDPI AG, 2008 14(2021), 22, p 7531 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:22, p 7531 https://doi.org/10.3390/en14227531 kostenfrei https://doaj.org/article/84a2846eafbe48aaa6b8aaa2416aabfd kostenfrei https://www.mdpi.com/1996-1073/14/22/7531 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 22, p 7531 |
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10.3390/en14227531 doi (DE-627)DOAJ079170277 (DE-599)DOAJ84a2846eafbe48aaa6b8aaa2416aabfd DE-627 ger DE-627 rakwb eng Rainer Baule verfasserin aut Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. intraday electricity market renewable energies electricity price volatility electricity price dispersion Technology T Michael Naumann verfasserin aut In Energies MDPI AG, 2008 14(2021), 22, p 7531 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:14 year:2021 number:22, p 7531 https://doi.org/10.3390/en14227531 kostenfrei https://doaj.org/article/84a2846eafbe48aaa6b8aaa2416aabfd kostenfrei https://www.mdpi.com/1996-1073/14/22/7531 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2021 22, p 7531 |
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Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market |
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Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. |
abstractGer |
Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. |
abstract_unstemmed |
Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted <inline-formula<<math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"<<semantics<<msup<<mi<R</mi<<mn<2</mn<</msup<</semantics<</math<</inline-formula< of 0.479 for volatility and around 0.3 for the dispersion measures. |
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Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market |
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