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
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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