This paper explores the attributes that drive company wealth creation in the Miscellaneous Industrials sector of the Australian Stock Market. It looks at how the company's wealth creation changes in comparison to the changes in the Miscellaneous Industrial Index. We examine traditional and artificial intelligent (AI) feature selection techniques, to select attributes that drive company wealth and observe if a multiple domain model outperforms a single domain model with regards to predicting company wealth. Using a large number of calculated attributes, our empirical findings suggest that a multiple domain model was most effective. We found that WACC, Funds from Operation / EBITDA and EPS assist in guiding the direction of change in shareholder wealth. Whereas ROA, Capital Turnover and Gross Debt / Cashflow are key attributes in understanding the behaviour of the relative shareholder growth. We observed that ROIC, Ordinary Share Price, EVA, EPS and Trading Revenue / Total Assets are the important attributes that drive relative shareholder wealth in this industry. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Barnes, M. B., & Lee, V. C. S. (2007). Feature selection techniques, company wealth assessment and intra-sectoral firm behaviours. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4681 LNCS, pp. 134–146). Springer Verlag. https://doi.org/10.1007/978-3-540-74171-8_14
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