Forecast-based scenario-tree generation method

نویسنده

  • Michal Kaut
چکیده

Sometimes, the best available information about an uncertain future is a single forecast. On the other hand, stochastic-programming models need future data in the form of scenario trees. While a single forecast does not provide enough information to construct a scenario tree, a forecast combined with historical data does—but none of the standard scenario-generation methods is suited to handle this combination. In this paper, we present a new scenario-generation method that combines a single forecast with historical forecast errors. Œe method is purely data driven and can take into account dependencies between errors of forecasts of di‚erent lengths.

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تاریخ انتشار 2017