2021/12/07 by Leonardo Rydin Gorjão, Gorjão, Leonardo Rydin, Dirk Witthaut +5
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Complex Systems and Time Series Analysis #FOS: Economics and business #FOS: Physical sciences #Nonlinear Dynamics and Pattern Formation #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Statistical Finance (q-fin.ST)
paper · pdf · doi:10.48550/arxiv.2112.03513
openalex publication_date 2021/12/07 · openalex created_date 2022/05/05 · openalex updated_date 2026/07/28
The European Power Exchange has introduced day-ahead auctions and continuous trading spot markets to facilitate the insertion of renewable electricity. These markets are designed to balance excess or lack of power in short time periods, which leads to a large stochastic variability of the electricity prices. Furthermore, the different markets show different stochastic memory in their electricity price time series, which seem to be the cause for the large volatility. In particular, we show the antithetical temporal correlation in the intraday 15 minutes spot markets in comparison to the day-ahead hourly market. We contrast the results from Detrended Fluctuation Analysis (DFA) to a new method based on the Kramers--Moyal equation in scale. For very short term (<12 hours), all price time series show positive temporal correlations (Hurst exponent H>0.5) except for the intraday 15 minute market, which shows strong negative correlations (H<0.5). For longer term periods covering up to two days, all price time series are anti-correlated (H<0.5).