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This tutorial contains an example with multiple indexes and subsequent tampering to the data in order to show resiliency and a real life use case of TC applied on cryptocurrency prices up to 2021.
Fix to the issue raised on empty dataframe, resulting from an inner merge where the existing dataframe that accumulated results and the newer one had diferent indices. A subsequent issue must be raised to either: 1 report a single model failure (on index matching) 2 fix the moirai discrepancy (only model that showed this issue)
… the title suggested
… MDA-MTRspread. Also adding the results for the first run of this version of the algorithm. These results were ran with public data from CENACE for all of 2025, but were used to predict only the spreads for november and december. All data for this run isn
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Adding spread prediction script that will run while predicting CENACE MDA-MTRspread. Also adding the results for the first run of this version of the algorithm. These results were ran with public data from CENACE for all of 2025, but were used to predict only the spreads for november and december. All data for this run isn't included in the commit (too large). Another ensemble was used for this approach, since the sign of the forecasted value is paramount for performance in the energy sector. Ensemble consists of voting for the sign of each prediction and magnitude being determined by the median of forecasts.