Volatility prediction with mixture density networks

Schittenkopf, Christian and Dorffner, Georg and Dockner, Engelbert J. (1998) Volatility prediction with mixture density networks. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 15. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.


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Despite the lack of a precise definition of volatility in finance, the estimation of volatility and its prediction is an important problem. In this paper we compare the performance of standard volatility models and the performance of a class of neural models, i.e. mixture density networks (MDNs). First experimental results indicate the importance of long-term memory of the models as well as the benefit of using non-gaussian probability densities for practical applications. (author's abstract)

Item Type: Paper
Keywords: Aktienindex / Volatilität / Prognose / Neuronales Netz / Heteroskedastizität
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 07 Mar 2002 16:21
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/344


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