We study optimal trading in an Almgren-Chriss model with running and terminal inventory costs and general predictive signals about price changes. As a special case, this allows to treat optimal liquidation in “target zone models”: asset prices with a reflecting boundary enforced by...

We derive convergence rates for a deep learning algorithm for semilinear partial differential equations which is based on a Feynman-Kac representation in terms of an uncoupled forward-backward stochastic differential equation and a discretization in time of the stochastic equation. We show that...

Summary We introduce a class of optimal stopping problems in which the gain is at least a fraction of the initial value. From a financial point of view this structure can be seen as a guarantee for the holder of an American option. It turns out that the optimal strategies are of two-sided type...

Quantitative Datenanalyse ist ein unverzichtbares Werkzeug in der digitalen Wissensgesellschaft. Dieses Lehrbuch bietet eine leicht verständliche Einführung in die Thematik für Studium und Berufsalltag. Besondere Aufmerksamkeit wird dabei der Abhängigkeitsmessung gewidmet, da sie...

In this paper we consider stochastic optimization problems for an ambiguity averse decision maker who is uncertain about the parameters of the underlying process. In a first part we consider problems of optimal stopping under drift ambiguity for one-dimensional diffusion processes. Analogously...

The principles of smooth and continuous pasting play an important role in the study of optimal stopping problems with jump processes. These principles state that the optimal stopping boundary is selected so that the value function is smooth and continuous, respectively (depending on the behavior...