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Decision Trees GmbH (www.dtrees.com) is a Munich based IT vendor and consultancy for the energy industry. The company applies state-of-the-art methods for simulation, statistics, time series analysis, mathematical and stochastic optimization. These mathematical concepts are implemented in the software DT.Energy, which is a valuation and decision support system for energy portfolios, which is widely applied in Germany, Austria, Switzerland and the UK.
Decision Trees’ goal is the transformation of new, highly-sophisticated procedures of financial mathematics, stochastic process modeling, operations research, mathematical and stochastic optimization into software that can withstand the test of practical operation. Decision Trees’ consultants explain the software to users on site and implement it into the company with the highest possible degree of transparency. We at Decision Trees follow the philosophy of open source, enabling users to integrate their own methods into our software. We closely cooperate with our clients and develop individual models for specific markets, assets, and portfolios.
Among others, Decision Trees has provided ExxonMobil with know how and software for the valuation of flexibility gas supply contracts based on the methodology of stochastic optimization in spot and forward gas trading markets. The software is successfully in use since 2014. Furthermore, Decision Trees’ stochastic optimization software is applied in continental Europe at various utilities for decision support in asset backed trading of gas storages and gas swing contracts (Increasing Revenues in Gas Storage Operations by using Scenario Tree based Stochastic Optimization).
Decision Trees offers workshops to train interested gas portfolio managers to find out how new mathematical and stochastic optimization approaches can increase the value of your asset portfolio in volatile energy markets! Finally, Decision Trees performs ex post simulation studies to determine the added monetary value of a highly-developed stochastic optimization for individual gas storage and gas contract portfolio in comparison to legacy dynamic backward-forward iteration and deterministic models!