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Краткосрочное Прогнозирование Цены Электроэнергии На Российском Рынке С Использованием Класса Моделей Scarx

Author

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  • Д.О. Афанасьев1
  • *
  • Е.А. Федорова2
  • **

Abstract

1 Аспирант департамента анализа данных, принятия решений и финансовых технологий, Финансовый университет при Правительстве РФ, Москва 2 Финансовый университет при Правительстве РФ, НИУ ВШЭ, Москва * dmafanasyev@gmail.com **ecolena@mail.ru Исследование выполнено при финансовой поддержке Российского фонда фундаментальных исследований (проект 16-06-00237 A). Аннотация. В данном исследовании для двух ценовых зон российского оптового рынка электроэнергии выполнена апробация класса прогнозных моделей авторегрессии с сезонной компонентой и экзогенными факторами SCARX, включающей экстраполяцию долгосрочной тренд-сезонной компоненты и отдельное прогнозирование краткосрочной сезонно-стохастической составляющей. Для заданного широкого набора параметров сглаживания временных рядов цен проведено сравнение моделей SCARX на базе вейвлет-разложения (SCARX-W) и фильтра Ходрика-Прескотта (SCARX-HP) с обычной авторегрессионной моделью ARX и "наивным" подходом (основанном на предположении равенства цен в идентичные дни недели). Оценка эффективности рассматриваемых моделей проводилась с использованием средневзвешенных недельных и дневных ошибок, а также формальной статистической процедуры сравнения прогностических способностей моделей - теста Диболда-Мариано (DM). Численный эксперимент был выполнен на исторических данных о цене и плановом потребление в зонах Европа-Урал и Сибирь российской электроэнергетической биржи. Тестовый период составил 104 недели или 728 дней. В результате проведенного исследования показано, что на российском рынке модель SCARX-W позволяет получить более высокую точность прогноза, по сравнению с SCARX-HP и ARX. При этом минимальная недельная ошибка, которую удалось достичь для ценовой зоны Европа-Урал, составила 4,932%, дневная ошибка - 4,997%. Для зоны Сибирь аналогичные показатели равны 9,144 и 10,051%, соответственно. Эти же результаты подтверждаются формальным DM-тестом, выполненным отдельно для каждого часа суток. Для преодоления проблемы априорного выбора параметров сглаживания в работе предложено использовать различные методы комбинирования прогнозов.

Suggested Citation

  • Д.О. Афанасьев1 & * & Е.А. Федорова2 & **, 2019. "Краткосрочное Прогнозирование Цены Электроэнергии На Российском Рынке С Использованием Класса Моделей Scarx," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 55(1), pages 68-84, январь.
    • Handle: RePEc:scn:cememm:v:55:y:2019:i:1:p:68-84
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