(such as rough volatility models) within the scope of applicability in industry practice. As customary for machine learning … mind we discuss how our approach addresses the usual challenges of machine learning solutions in a financial context … and robustness. We also find that including the intermediate step of learning pricing functions of (classical or rough …

Different theories of expectation formation and learning usually yield different outcomes for realized market prices in … dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental …

This paper develops a theory of expectations-driven business cycles based on learning. Agents have incomplete knowledge … series is captured, unlike in standard models. Inherited from real business cycle theory, the benchmark model suffers a …

triggers large asset-price jumps. We show that the learning choice is critically determined by preference parameters and the …

triggers large asset-price jumps. We show that the learning choice is critically determined by preference parameters and the …