applied to state filtering and sequential parameter learning. This paper introduces robust state space models whose error …

equilibrium dynamics resulting from this learning process helps to explain the main stylized facts of free-floating exchange rates … the number of agents (not more than about 1000). With a larger population, this collective learning dynamics looses its … Hauptinteresse geht dahin, herauszufinden, ob die Gleichgewichtsdynamik, die aus diesem Lernprozess resultiert, dabei helfen kann …

Deep learning is playing an increasingly important role in time series analysis. We focused on time series forecasting …, which also allowed to improve the prediction capacity of a LSTM, while improving the efficiency of the learning task …