Identification of Factor Models for Forecasting Returns
AbstractA data-driven approach for forecasting returns of asset prices is introduced. Special emphasis is given to data-driven specification and to dimension reduction. Specification is performed by a modified AIC, BIC-based An-algorithm. Quasi-static principal component analysis, quasi-static factor models with idiosyncratic errors and reduced rank regression are considered. The forecasting results obtained are compared. Copyright 2005, Oxford University Press.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 3 (2005)
Issue (Month): 2 ()
Contact details of provider:
Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK
Fax: 01865 267 985
Web page: http://jfec.oxfordjournals.org/
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press) or (Christopher F. Baum).
If references are entirely missing, you can add them using this form.