Quasi-Monte Carlo methods in portfolio selection with many constraints

Alexander Brunhuemer; Gerhard Larcher

doi:10.1007/978-3-031-10193-9_5

Quasi-Monte Carlo methods in portfolio selection with many constraints

Alexander Brunhuemer
, Gerhard Larcher^*

^*Korrespondierende/r Autor/-in für diese Arbeit

Institut für Finanzmathematik und Angewandte Zahlentheorie

Publikation: Beitrag in Buch/Bericht/Konferenzband › Kapitel › Begutachtung

Abstract

We describe a concrete on-going industry project on advanced portfolio optimization based on machine-learning techniques, and we report on attempts and results of successful and advantageous application of QMC methods in this project. We are also carrying out an approach to determine a measure for dispersion in an opportunity set, which cannot trivially be found, because of the uncertainty of the shape of an opportunity set. Finally, we state some still open problems and questions in this context.

Originalsprache	Englisch
Titel	Advances in Modeling and Simulation
Untertitel	Festschrift for Pierre L'Ecuyer
Herausgeber*innen	Zdravko Botev, Alexander Keller, Christiane Lemieux, Bruno Tuffin
Verlag	Springer, Cham
Seiten	89-109
Seitenumfang	21
ISBN (elektronisch)	978-3-031-10193-9
ISBN (Print)	978-3-031-10192-2, 978-3-031-10195-3
DOIs	https://doi.org/10.1007/978-3-031-10193-9_5
Publikationsstatus	Veröffentlicht - 2022

Wissenschaftszweige

101 Mathematik
101019 Stochastik
101025 Zahlentheorie
101007 Finanzmathematik

JKU-Schwerpunkte

Digital Transformation

Zugriff auf Dokument

10.1007/978-3-031-10193-9_5

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Quasi-Monte Carlo methods in portfolio selection with many constraints. / Brunhuemer, Alexander; Larcher, Gerhard.
Advances in Modeling and Simulation: Festschrift for Pierre L'Ecuyer. Hrsg. / Zdravko Botev; Alexander Keller; Christiane Lemieux; Bruno Tuffin. Springer, Cham, 2022. S. 89-109.

Publikation: Beitrag in Buch/Bericht/Konferenzband › Kapitel › Begutachtung

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