Nonlinear and Nonparametric Methods for Analyzing Financial Time Series

  • We consider nonparametric generalization of various well-known financial time series models and study estimates of the trend and volatility functions and forecasts based on kernel smoothers as well as on neural networks.

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Metadaten
Author:Jürgen Franke
URN (permanent link):urn:nbn:de:hbz:386-kluedo-9353
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (44)
Document Type:Preprint
Language of publication:English
Year of Completion:1999
Year of Publication:1999
Publishing Institute:Technische Universität Kaiserslautern
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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