Publication type: Conference paper
Type of review: Peer review (abstract)
Title: Forecasting non-stationary financial data with OIIR-filters and composed threshold models
Authors: Wildi, Marc
DOI: 10.1007/978-1-4615-5625-1_31
Proceedings: Decision technologies for computational finance : proceedings of the Fifth International Conference Computational Finance
Page(s): 391
Pages to: 402
Conference details: 5th International Conference Computational Finance, London, United Kingdom, 15-17 December 1997
Issue Date: 1998
Series: Advances in computational management science
Series volume: 2
Publisher / Ed. Institution: Springer
Publisher / Ed. Institution: Boston
ISBN: 978-0-7923-8309-3
978-1-4615-5625-1
ISSN: 1388-4301
Language: English
Subjects: High pass filter; Stationary component; Filter design; Infinite impulse response; Amplitude function
Subject (DDC): 332: Financial economics
500: Natural sciences
Abstract: The 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.
URI: https://digitalcollection.zhaw.ch/handle/11475/16835
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Appears in collections:Publikationen School of Engineering

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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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