Variance Stabilizing Transformations for Electricity Spot Price Forecasting

By Bartosz Uniejewski, Rafal Weron, Florian Ziel. IEEE Transactions on Power Systems, 2018

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Energy Forecasting: A Review and Outlook (2020, methodology): “Attempts at tackling this issue include proposing simple bidding strategies based on a comparison of the actual prices and their forecasts [114], [115] or using measures popular in financial portfolio analysis, like the Sharpe ratio [116], [117].”
Recent advances in electricity price forecasting: A review of probabilistic forecasting (2016, methodology): “, is the same as the true distribution of the spot price process, FPt), then PITt is independent and uniformly distributed [98].”
Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark (2020, methodology): “Typically, studies considering advanced statistical techniques only compare them with simple ML methods [9–11] and show that statistical methods are obviously better.”
Econometric modelling and forecasting of intraday electricity prices (2018, methodology): “n handle all real values and has a logarithmic tail behaviour as the log, but for both positive and negative values. Thus, it solves all issues concerning the heavy tails in the data. In the paper of Uniejewski et al. (2018) it is shown, that, considering the quality of the forecasts, it performs re”