• Thesis to Book with ISBN
• Aim And Scope
• Article in Press
• Editorial Board
• Current Issue
• Archives
• Publication Charges
• Authors Information
• Contact Us
• Paper Format

[Abstract] [PDF] [HTML] [Linked References]

International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605

Volume 7, Issue 2, October 2013 pp 78-83

Research Article

Indian Industrial Position on the Basis of Financial Ratios: A Data Mining Approach

R. Chandrasekaran¹, G. Manimannan¹ and R. Lakshmi Priya²

¹Department of Statistics, Madras Christian College, Chennai, Tamil Nadu, INDIA.

Academic Editor: Dr. Dase R. K.

An attempt is made to introduce a new method of grading the top ranking industries on the basis of financial ratios. It is well known that the financial ratios are being used as a measure by researchers for many purposes.  About 247 companies consist of five major industries from Indian corporate database sectors were considered for each year from 2001 to 2010.  Fourteen financial ratios were carefully chosen out of frequent ratios that could give different idea of the objectives and have important meaning in the literature. The unique feature of this study is the application of factor, K-mean clustering and discriminant analyses as data mining tools to develop the hidden structure present in the data for each of the study periods.  Initially, factor analysis is used to uncover the patterns underlying financial ratios.  The scores from extracted factors were used to find initial groups by K-mean clustering algorithm. A few outlier industries, which could not be classified to any of the larger groups, were discarded as some of the ratios possessed higher values. The clusters thus obtained formed the basis for the further analyses as they inherent the structural patterns found by the factor analysis. The cluster analysis was followed by iterative discriminant procedure with original ratios until cent percent classification was achieved.   Finally, the groups were identified as companies belonging to Grade H, Grade M and Grade L in that order, which show the behavior of High performance, Moderate performance and Low performance. From the present study it was observed that a little over 75% of the total variation of the data was explained by the first four factors for each industry. These four factors revealed the underlying structural patterns among the fourteen ratios that were initially considered in the analysis. Also only three clusters could be meaningfully formed for each of the periods.