£48.86

Deutscher Universitätsverlag Künstliche neuronale Netze zur Risikomessung bei Aktien und Renten: Am Beispiel deutscher Lebensversicherungsunternehmen: 47 (Versicherung und Risikoforschung, 47)

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Description

Die Risikomessung als Teilaufgabe des Risikomanagements stellt für institutionelle Kapitalanleger eine elementare Aufgabe dar. Hierzu werden Volatilitäten und Korrelationskoeffizienten prognostiziert, wobei verschiedene Instrumente und Methoden zur Verfügung stehen. Künstliche neuronale Netze scheinen besonders gut geeignet zu sein; darauf lassen Untersuchungen in anderen Feldern schließen, die grundsätzliche Ähnlichkeiten mit dem Problem der Risikoprognose aufweisen. Markus Rauscher untersucht die Qualität mit Hilfe künstlicher neuronaler Netze erstellter Vorhersagen hinsichtlich der Volatilität und Korrelation von DAX und REXP. Um die Eignung bestimmter Konstellationen zu ermitteln, findet eine Vielzahl unterschiedlicher Architekturen und Lernalgorithmen Verwendung. Die den herkömmlichen Methoden überlegenen neuronalen Modelle werden dargestellt und sich daraus ergebende Möglichkeiten diskutiert.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 November 2004
Listed Since
11 February 2007

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