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  • The business structure of the electricity generating sector is relatively easy to predict, if the environment is regulated. After the successful deregulation of some sectors, there has been movement toward deregulation and liberalization in many European countries. This process has important impact on the most market participants, from the electricity generators, distributing utilities to the final consumers. As a consequence of power sector liberalization, price modeling and forecasting has emerged as an important input to a wide range of decision problems in the electricity sector. Electricity prices have become extremely volatile compared to prices in other commodity markets and choices of appropriate model for modeling and forecasting have a large effect on the solution to many decision problems. To find the most suitable model including deriving its parameters, the choice of appropriate set of input data that includes relevant information about behavior of electricity prices is important, as wel
  • The business structure of the electricity generating sector is relatively easy to predict, if the environment is regulated. After the successful deregulation of some sectors, there has been movement toward deregulation and liberalization in many European countries. This process has important impact on the most market participants, from the electricity generators, distributing utilities to the final consumers. As a consequence of power sector liberalization, price modeling and forecasting has emerged as an important input to a wide range of decision problems in the electricity sector. Electricity prices have become extremely volatile compared to prices in other commodity markets and choices of appropriate model for modeling and forecasting have a large effect on the solution to many decision problems. To find the most suitable model including deriving its parameters, the choice of appropriate set of input data that includes relevant information about behavior of electricity prices is important, as wel (en)
  • Cílem příspěvku je je analýza a možnosti aplikace vybraných modelů pro predikci denních cen elektřiny na evropském trhu. Pro predikci denních cen jsou aplikovány difuzní a ekonometrické modely. Studie vychází z denních průměrných cen elektřiny v letech 2006-2007, predikce je provedena pro leden roku 2008. Výsledky predikce použitých modelů jsou porovnány a diskutovány. (cs)
Title
  • ELECTRICITY PRICE FORECASTING AND SIMULATION
  • ELECTRICITY PRICE FORECASTING AND SIMULATION (en)
  • Predikce a simulace cen elektřiny (cs)
skos:prefLabel
  • ELECTRICITY PRICE FORECASTING AND SIMULATION
  • ELECTRICITY PRICE FORECASTING AND SIMULATION (en)
  • Predikce a simulace cen elektřiny (cs)
skos:notation
  • RIV/61989100:27510/08:00018583!RIV09-GA0-27510___
http://linked.open...avai/riv/aktivita
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  • P(GP402/07/P121)
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http://linked.open...aciTvurceVysledku
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  • 365756
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  • RIV/61989100:27510/08:00018583
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  • Electricity price; forecasting; confidence interval; Geometric Brownian Motion; mean-reversion process. (en)
http://linked.open.../riv/klicoveSlovo
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  • [CC0255F1BDE5]
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  • Liberec
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  • Mathematical Methods in Economics
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http://linked.open...vavai/riv/projekt
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http://linked.open...iv/tvurceVysledku
  • Valecký, Jiří
  • Čulík, Miroslav
number of pages
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  • Technická univerzita v Liberci
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  • 978-80-7372-387-3
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  • 27510
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