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An algorithm for variable selection in firm valuation models

An algorithm for variable selection in firm valuation models 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Business Performance and Supply Chain Modelling Inderscience Publishers

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1758-9401
eISSN
1758-941X
DOI
10.1504/IJBPSCM.2009.030639
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Business Performance and Supply Chain ModellingInderscience Publishers

Published: Jan 1, 2009

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