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Risikoquantifizierung: Charakteristische Funktion und numerische Methoden als Alternative zur Monte-Carlo-Simulation: Fallbeispiele zu kombinierten Verteilungen

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  • Knobloch, Ralf

Abstract

Für Unternehmen werden die Anforderungen an die Genauigkeit bei der Bewertung von Risiken aufgrund interner und externer Faktoren zunehmend höher. Dies erfordert komplexere Modelle und Berechnungsmethoden, sowohl auf der Ebene von Einzelrisken als auch auf der Ebene von Risikoportfolios. Häufig führen Unternehmen daher Monte-Carlo-Simulationen zur Ermittlung von Risiko-Kennzahlen durch. In der vorliegenden Arbeit wird eine numerische Alternative, basierend auf dem stochastischen Begriff der charakteristischen Funktion, vorgestellt und in drei komplexeren Fallbeispielen angewendet. Es zeigt sich, dass bei den hier gewählten Fallbeispielen die Abweichungen zwischen den Ergebnissen der beiden Methoden nicht signifikant sind.

Suggested Citation

  • Knobloch, Ralf, 2025. "Risikoquantifizierung: Charakteristische Funktion und numerische Methoden als Alternative zur Monte-Carlo-Simulation: Fallbeispiele zu kombinierten Verteilungen," Forschung am ivwKöln 1/2025, Technische Hochschule Köln – University of Applied Sciences, Institute for Insurance Studies.
  • Handle: RePEc:zbw:thkivw:330328
    DOI: 10.57684/COS-1303
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    1. Oecd, 2025. "Co-operative antitrust in remedy design," OECD Roundtables on Competition Policy Papers 328, OECD Publishing.
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      JEL classification:

      • G - Financial Economics
      • G2 - Financial Economics - - Financial Institutions and Services
      • G29 - Financial Economics - - Financial Institutions and Services - - - Other

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