Routine action', a form to take action, is widely accepted in the economic field, because of its resource saving effect which contributes to average cost degression. However, from an entropic point of view, each form of acting requires decision making in regard to consumption of resources and...

Recent experimental simulations have shown that autonomous pricing algorithms are able to learn collusive behavior and thus charge supra-competitive prices without being explicitly programmed to do so. These simulations assume, however, that both firms employ the identical price-setting...

This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1-2019Q4. The adaptive learning model...

Deep hedging is a deep-learning-based framework for derivative hedging in incomplete markets. The advantage of deep hedging lies in its ability to handle various realistic market conditions, such as market frictions, which are challenging to address within the traditional mathematical finance...

Two separate branches of research have shown the empirical benefits of nonlinearities in macroeconomic models and bounded rationality, respectively. This paper bridges these literatures by developing a methodology for estimating DSGE models when expectations are formed by adaptive learning...