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dc.contributor.authorWildi, Marc-
dc.date.accessioned2019-04-24T10:08:02Z-
dc.date.available2019-04-24T10:08:02Z-
dc.date.issued1998-
dc.identifier.isbn978-0-7923-8309-3de_CH
dc.identifier.isbn978-1-4615-5625-1de_CH
dc.identifier.issn1388-4301de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/16835-
dc.description.abstractThe paper proposes a forecasting-technique well suited to stationary and non-stationary economic or financial data. Two methods are used which together generalize the Box-Jenkins ARIMA-technique: Optimized-Infinite-Impulse-Response-Filters generalize difference-filters and composed-threshold (piecewise linear) models generalize linear ARMA-models.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesAdvances in computational management sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectHigh pass filterde_CH
dc.subjectStationary componentde_CH
dc.subjectFilter designde_CH
dc.subjectInfinite impulse responsede_CH
dc.subjectAmplitude functionde_CH
dc.subject.ddc332: Finanzwirtschaftde_CH
dc.subject.ddc500: Naturwissenschaftende_CH
dc.titleForecasting non-stationary financial data with OIIR-filters and composed threshold modelsde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.publisher.placeBostonde_CH
dc.identifier.doi10.1007/978-1-4615-5625-1_31de_CH
zhaw.conference.details5th International Conference Computational Finance, London, United Kingdom, 15-17 December 1997de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawNode_CH
zhaw.pages.end402de_CH
zhaw.pages.start391de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number2de_CH
zhaw.publication.reviewPeer review (Abstract)de_CH
zhaw.title.proceedingsDecision technologies for computational finance : proceedings of the Fifth International Conference Computational Financede_CH
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Wildi, M. (1998). Forecasting non-stationary financial data with OIIR-filters and composed threshold models [Conference paper]. Decision Technologies for Computational Finance : Proceedings of the Fifth International Conference Computational Finance, 391–402. https://doi.org/10.1007/978-1-4615-5625-1_31
Wildi, M. (1998) ‘Forecasting non-stationary financial data with OIIR-filters and composed threshold models’, in Decision technologies for computational finance : proceedings of the Fifth International Conference Computational Finance. Boston: Springer, pp. 391–402. Available at: https://doi.org/10.1007/978-1-4615-5625-1_31.
M. Wildi, “Forecasting non-stationary financial data with OIIR-filters and composed threshold models,” in Decision technologies for computational finance : proceedings of the Fifth International Conference Computational Finance, 1998, pp. 391–402. doi: 10.1007/978-1-4615-5625-1_31.
WILDI, Marc, 1998. Forecasting non-stationary financial data with OIIR-filters and composed threshold models. In: Decision technologies for computational finance : proceedings of the Fifth International Conference Computational Finance. Conference paper. Boston: Springer. 1998. S. 391–402. ISBN 978-0-7923-8309-3
Wildi, Marc. 1998. “Forecasting Non-Stationary Financial Data with OIIR-Filters and Composed Threshold Models.” Conference paper. In Decision Technologies for Computational Finance : Proceedings of the Fifth International Conference Computational Finance, 391–402. Boston: Springer. https://doi.org/10.1007/978-1-4615-5625-1_31.
Wildi, Marc. “Forecasting Non-Stationary Financial Data with OIIR-Filters and Composed Threshold Models.” Decision Technologies for Computational Finance : Proceedings of the Fifth International Conference Computational Finance, Springer, 1998, pp. 391–402, https://doi.org/10.1007/978-1-4615-5625-1_31.


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