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Datapred starts coverage of European emission allowances

Posted by Datapred | Sep 1, 2021 10:26:48 AM

The new online software is the first in this category on EEX’s InsightCommodity platform.


LAUSANNE – SEPTEMBER 1, 2021 – Datapred, the digital twin for raw material and energy buyers, today announced that it started delivering market analyses and price trend predictions to participants in the European Emission Trading System.


This online version of Datapred is accessible from the Datapred website and the InsightCommodity platform of EEX, where it is the first Analytics and Price Forward Curve solution available to buyers of EU Allowances.

EUA prices have doubled in one year, and the Commission’s Fit For 55 plan ensures that industrial participants in that market will continue to feel the pain” said Thomas Oriol, Director of Datapred. “We are glad to start providing them with the analyses and predictions our clients in the Metals, Chemicals, Energy and Agriculture sectors already enjoy.”

The new solution is based on the analysis and prediction engine included in Datapred’s digital twin for raw material and energy buyers. Datapred uses advanced time series modeling, and processes tens of data streams (EUA prices from EEX of course, but also energy prices, stock prices, market indices, temperatures…) to provide buyers with the analyses, predictions and simulations they need to make better decisions.

To launch its CO2 solution, Datapred has notably drawn from the experience accumulated during the past three years with large European players in the natural gas, power, metals and chemicals markets – most of them mandatory participants in the European Emission Trading System.

Datapred will enrich the solution continuously – both enlarging its coverage of EUA buying instruments and enriching the visualization, anticipation and optimization tools available to EUA buyers.


About Datapred
Founded in 2015 and based in Lausanne, Switzerland, Datapred is a digital twin for raw material and energy buyers. Datapred uses machine learning, operations research, and tens of external and internal data streams to help buyers make better decisions and shave 3-5% off their direct material costs, year over year.

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