%0 Conference Paper %1 brabazon:2002:EuroGP %A Brabazon, Anthony %A O'Neill, Michael %A Ryan, Conor %A Matthews, Robin %B Genetic Programming, Proceedings of the 5th European Conference, EuroGP 2002 %C Kinsale, Ireland %D 2002 %E Foster, James A. %E Lutton, Evelyne %E Miller, Julian %E Ryan, Conor %E Tettamanzi, Andrea G. B. %I Springer-Verlag %K algorithms, evolution genetic grammatical programming, %P 103--112 %T Evolving classifiers to model the relationship between strategy and corporate performance using grammatical evolution %V 2278 %X This study examines the potential of grammatical evolution to construct a linear classifier to predict whether a firm's corporate strategy will increase or decrease shareholder wealth. Shareholder wealth is measured using a relative fitness criterion, the change in a firm's market-value-added ranking in the Stern-Stewart Performance 1000 list, over a four year period, 1992-1996. Model inputs and structure are selected by means of grammatical evolution. The best classifier correctly categorised the direction of performance ranking change in 66.38percent of the firms in the training set and 65percent in the out-of-sample validation set providing support for a hypothesis that changes in corporate strategy are linked to changes in corporate performance. %@ 3-540-43378-3

@inproceedings{brabazon:2002:EuroGP, abstract = {This study examines the potential of grammatical evolution to construct a linear classifier to predict whether a firm's corporate strategy will increase or decrease shareholder wealth. Shareholder wealth is measured using a relative fitness criterion, the change in a firm's market-value-added ranking in the Stern-Stewart Performance 1000 list, over a four year period, 1992-1996. Model inputs and structure are selected by means of grammatical evolution. The best classifier correctly categorised the direction of performance ranking change in 66.38percent of the firms in the training set and 65percent in the out-of-sample validation set providing support for a hypothesis that changes in corporate strategy are linked to changes in corporate performance.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Kinsale, Ireland}, author = {Brabazon, Anthony and O'Neill, Michael and Ryan, Conor and Matthews, Robin}, biburl = {https://www.bibsonomy.org/bibtex/2111a721648a667b292e79cab0400122c/brazovayeye}, booktitle = {Genetic Programming, Proceedings of the 5th European Conference, EuroGP 2002}, editor = {Foster, James A. and Lutton, Evelyne and Miller, Julian and Ryan, Conor and Tettamanzi, Andrea G. B.}, interhash = {777e102f807fb4d9cbdb289c929bf9af}, intrahash = {111a721648a667b292e79cab0400122c}, isbn = {3-540-43378-3}, keywords = {algorithms, evolution genetic grammatical programming,}, month = {3-5 April}, notes = {EuroGP'2002, part of \cite{lutton:2002:GP}}, pages = {103--112}, publisher = {Springer-Verlag}, publisher_address = {Berlin}, series = {LNCS}, timestamp = {2008-06-19T17:36:51.000+0200}, title = {Evolving classifiers to model the relationship between strategy and corporate performance using grammatical evolution}, volume = 2278, year = 2002 }