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Feature Selection Techniques, Company Wealth Assessment and Intra-sectoral Firm Behaviours

Mark B. BarnesContact Information and Vincent C. S. LeeContact Information

(1)  School of Business Systems, Monash University, Clayton Campus, Victoria, Australia
Abstract
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.

Keywords  Feature Selection - Artificial Intelligence - Company wealth and Intra sectoral firm behaviours


Contact Information Mark B. Barnes
Email: mbbar1@student.monash.edu.au

Contact Information Vincent C. S. Lee
Email: vincent.lee@infotech.monash.edu.au
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