Сравнение динамики спотовых цен на электричество в европейской и сибирской ценовых зонах России в модели стохастической волатильности

Экономика и математические методы. 2024. Т. 60. № 1. С. 85–96.

Kasianova K.

In the literature on forecasting electricity spot prices, it is noted that the empirical distribution of the
growth rates of equilibrium prices for electricity is characterized by the presence of heavy ‘tails’, so they can be
described as a jump-diffusion process. However, electricity prices are associated with a variety of observable
factors that can be included in the model. Within the framework of this article, a flexible model, that allows
taking into account statistical features of electricity prices (multilevel seasonality, stochastic volatility), as well as fundamental price factors that directly or indirectly affect equilibrium price indices (weather factors, re-
source prices, industrial production index, or IPI), was developed. Using methods of Bayesian inference, it was shown that the developed two-level specification of the stochastic volatility model, which separates the factors
influencing the deterministic and stochastic components of the series, fits the data best, among the considered
alternatives. As a result, differences in the price dynamics between the European and Siberian price zones were
revealed: the influence of the weather factor in the price zones is not the same; there are also differences in
the weekly price dynamics and the effect of holidays. The effect of low-frequency economic factors (resource
prices, IPI) on prices was not revealed. This model is a useful tool for analyzing short-term and long-term
electricity price dynamics, building scenario forecasts, and it also can potentially be used in risk-management
and electricity derivatives pricing.

Keywords: ряды Фурье, stochastic volatility model, анализ временных рядов, Bayes factor, байесовский вывод, Fourier series, linear trend, линейный тренд, Bayesian inference, модель стохастической волатильности, time series analysis, electricity spot prices, day ahead market, trend-seasonal decomposition, effective sample size, спотовые цены на электроэнергию, рынок на сутки вперед, тренд-сезонное разложение, коэффициент Байеса, эффективный размер выборки