دانلود مقاله ISI انگلیسی شماره 57377
ترجمه فارسی عنوان مقاله

پیش بینی تغییرات قیمت در بازارهای برق آشفته

عنوان انگلیسی
Predictability of price movements in deregulated electricity markets
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
57377 2015 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Energy Economics, Volume 49, May 2015, Pages 72–81

ترجمه کلمات کلیدی
بازار برق؛ فرضیه بازار کارآمد؛ تحلیل نوسانات؛ پیش بینی های مالی
کلمات کلیدی انگلیسی
C12 Hypothesis Testing: General; C46 Specific Distributions • Specific Statistics; C53 Forecasting and Prediction Methods • Simulation Methods; E32 Business Fluctuations • Cycles; E37 Forecasting and Simulation: Models and Applications; Q47 Energy ForecastingDeregulated electricity markets; Efficient market hypothesis; Detrended fluctuation analysis; Financial forecasting
پیش نمایش مقاله
پیش نمایش مقاله  پیش بینی تغییرات قیمت در بازارهای برق آشفته

چکیده انگلیسی

In this paper we investigate predictability of electricity prices in the Canadian provinces of Alberta and Ontario, as well as in the US Mid-C market. Using scale-dependent detrended fluctuation analysis, spectral analysis, and the probability distribution analysis we show that the studied markets exhibit strongly anti-persistent properties suggesting that their dynamics can be predicted based on historic price records across the range of time scales from 1 h to one month. For both Canadian markets, the price movements reveal three types of correlated behavior which can be used for forecasting. The discovered scenarios remain the same on different time scales up to one month as well as for on- and off-peak electricity data. These scenarios represent sharp increases of prices and are not present in the Mid-C market due to its lower volatility. We argue that extreme price movements in this market should follow the same tendency as the more volatile Canadian markets. The estimated values of the Pareto indices suggest that the prediction of these events can be statistically stable. The results obtained provide new relevant information for managing financial risks associated with the dynamics of electricity derivatives over time frame exceeding one day.