Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models
In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a princip...
Ausführliche Beschreibung
Autor*in: |
Kun Li [verfasserIn] Joseph D. Cursio [verfasserIn] Yunchuan Sun [verfasserIn] Zizheng Zhu [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Übergeordnetes Werk: |
In: Ekonomska Istraživanja - Taylor & Francis Group, 2019, 32(2019), 1, Seite 2404-2421 |
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Übergeordnetes Werk: |
volume:32 ; year:2019 ; number:1 ; pages:2404-2421 |
Links: |
Link aufrufen |
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DOI / URN: |
10.1080/1331677X.2019.1645712 |
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Katalog-ID: |
DOAJ028754654 |
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10.1080/1331677X.2019.1645712 doi (DE-627)DOAJ028754654 (DE-599)DOAJf47d9b69503349b2a2c56f78ed22cf67 DE-627 ger DE-627 rakwb eng HD72-88 Kun Li verfasserin aut Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making. price fluctuation principal component analysis nardl electricity market spike price negative price Economic growth, development, planning Regional economics. Space in economics HT388 Joseph D. Cursio verfasserin aut Yunchuan Sun verfasserin aut Zizheng Zhu verfasserin aut In Ekonomska Istraživanja Taylor & Francis Group, 2019 32(2019), 1, Seite 2404-2421 (DE-627)521479487 (DE-600)2262643-8 18489664 nnns volume:32 year:2019 number:1 pages:2404-2421 https://doi.org/10.1080/1331677X.2019.1645712 kostenfrei https://doaj.org/article/f47d9b69503349b2a2c56f78ed22cf67 kostenfrei http://dx.doi.org/10.1080/1331677X.2019.1645712 kostenfrei https://doaj.org/toc/1331-677X Journal toc kostenfrei https://doaj.org/toc/1848-9664 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_152 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2129 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4046 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_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 32 2019 1 2404-2421 |
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Kun Li misc HD72-88 misc price fluctuation misc principal component analysis misc nardl misc electricity market misc spike price misc negative price misc Economic growth, development, planning misc Regional economics. Space in economics misc HT388 Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models |
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Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models |
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In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making. |
abstractGer |
In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making. |
abstract_unstemmed |
In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making. |
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Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models |
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