Buch

Applications of stochastic optimal control to economics and finance

In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues inpricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue "Applications of Stochastic Optimal Control to Economics and Finance", which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used.

ISBN
978-3-03936-059-8

Sprache
Englisch

Klassifikation
Wirtschaft
Thema
Kontrolltheorie
Stochastischer Prozess
Wissenschaftliche Methode

Ereignis
Geistige Schöpfung
(wer)
Federico, Salvatore
Ferrari, Giorgio
Regis, Luca
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Buch

Beteiligte

  • Federico, Salvatore
  • Ferrari, Giorgio
  • Regis, Luca
  • MDPI

Entstanden

  • 2020

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