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 marketvalue- 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 66.38% of the firms in the training set and 65% in the out-of-sample validation set providing support for a hypothesis that changes in corporate strategy are linked to changes in corporate performance.
CITATION STYLE
Brabazon, A., O’Neill, M., Ryan, C., & Matthews, R. (2002). Evolving classifiers to model the relationship between strategy and corporate performance using grammatical evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2278, pp. 103–112). Springer Verlag. https://doi.org/10.1007/3-540-45984-7_10
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