A machine learning dynamic switching approach to forecasting when there are structural breaks

A machine learning dynamic switching approach to forecasting when there are structural breaks

Forecasting economic indicators is an important task for analysts. However, many indicators suffer from structural breaks leading to forecast failure. Methods that are robust following a structural break have been proposed in the literature but they come at a cost: an increase in forecast error vari...

Полное описание

Библиографические подробности
Главные авторы:	Marcondes Pinto, J, Castle, J
Формат:	Working paper
Язык:	English
Опубликовано:	University of Oxford 2021

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