Back to Search Start Over

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

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
De-Shuang Huang
Heutte, Laurent
Loog, Marco
Barnes, Mark B.
Lee, Vincent C. S.
Source :
Advanced Intelligent Computing Theories & Applications. With Aspects of Theoretical & Methodological Issues; 2007, p134-146, 13p
Publication Year :
2007

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540741701
Database :
Complementary Index
Journal :
Advanced Intelligent Computing Theories & Applications. With Aspects of Theoretical & Methodological Issues
Publication Type :
Book
Accession number :
33100696
Full Text :
https://doi.org/10.1007/978-3-540-74171-8_14