We develop an algorithm for solving a large class of nonlinear high-dimensional continuous-time models in finance. We approximate value and policy functions using deep learning and show that a combination of automatic differentiation and Ito's lemma allows for the computation of exact...

This study endeavors to unravel the structured and sequential intricacies underlying the empirical da-ta-generating process (DGP) and the captivating evolutionary dynamism of Islamic fixed income securi-ties. To achieve this goal, we delve into the realm of nonlinear dynamics governing the Dow...

We develop a nonlinear duopoly model in which the heuristic expectation formation and learning behavior of two boundedly rational firms may engender complex dynamics. Most importantly, we assume that the firms employ different forecasting models to predict the behavior of their opponent....

The paper examines whether the US evidence in favour of a nonlinearity in the Phillips curve is robust or fragile. To this end, we use both cross city and aggregate time series data. We are particularly concerned with the possibility that the evidence in favour a nonlinear Phillips curve may is...