Two series, German mark/US dollar exchange rate and US consumer price index, are tested to illustrate if nonlinear noise reduction could help to improve prediction. Three nonlinear noise reduction methods, local projective (LP), singular value decomposition (SVD) and simple nonlinear filtering (SNL), are used to generate the filtered time series. Different projection dimensions of the noise reduction methods are also selected for the sensitivity test on the prediction results. The results show that noise reduction does help in improving prediction in both of the examples providing that an appropriate method of noise reduction and suitable parameter values for the method are used.
Download Info
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page
whether it is in fact available.
3. Perform a search for a similarly titled item that would be
available.
Publisher Info
Paper provided by Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance in its series CeNDEF Workshop Papers, January 2001 with number
PO9.
Length: Date of creation: 04 Jan 2001 Date of revision: Handle: RePEc:ams:cdws01:po9
Contact details of provider: Postal: Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands Phone: + 31 20 525 52 58 Fax: + 31 20 525 52 83 Web page: http://www.fee.uva.nl/cendef/ More information through EDIRC
For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).