An algorithm for variable selection in firm valuation models

Fernando Garcia, Francisco Guijarro and Ismael Moya

International Journal of Business Performance and Supply Chain Modelling, 2009, vol. 1, issue 2/3, 144-161

Abstract: Firm valuation constitutes a classical topic in finance research. Variable selection in valuation models is a problem addressed by many researchers mainly focused on multivariate analysis. This study proposes a methodology for dealing with the problem of explicative variable selection in financial models for firm valuation. With a view to its eventual automation, it is presented in three consecutive steps. These ensure that the models obtained are parsimonious, and that there is control of their degree of multicollinearity without sacrificing their explicative power. The method combines several statistical techniques, notably simple regression analysis and principal components analysis. To test the proposal, we used a database of stock market and accounting information relating to firms quoted on the Madrid Stock Exchange in 2002 and 2003.

Keywords: firm pricing; business performance modelling; financial statements; multicollinearity; principal components analysis; PCA; regression; variable selection; firm valuation models; Spain. (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=30639 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijbpsc:v:1:y:2009:i:2/3:p:144-161

Access Statistics for this article

More articles in International Journal of Business Performance and Supply Chain Modelling from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().