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Recently, the use of Self-Organizing Map (SOM) has provided a benchmark in analyzing and visualizing high dimensional data as a rapid growing field in data mining, especially in the analysis of financial statements. The dataset relates to 445 companies of five major industrial sectors from Indian corporate database published by Capital market, India. The dataset comprises of important financial ratios of 78 companies from cement, 115 companies from steel, 102 companies from plastic, 66 companies from leather and 84 companies from hardware and software industries. The time frame of the data pertaining to the present study is 2006-2010. Out of numerous ratios, eleven financial ratios are carefully chosen that had different notions of the objectives and significant meaning in the literature. The analysis is a two-stage procedure. First, SOM is used on the data relating to all the 445 companies to produce prototype vectors which are then, partitioned applying k-means clustering algorithm that yielded only 3 meaningful clusters with optimum Davies-Boudl in index for each of the study period. The labels of the prototype vectors are then assigned to the data on the basis of the best mapping unit. This procedure is used to grade the companies as Grade A, Grade B and Grade C based on their financial ratios. Grade A companies are those with higher profile than B and C. Similarly, Grade B companies had their profile of performances superior to Grade C but inferior to Grade A. The grades of the 445 companies are compared for the successive years from the year 2006 to 2010, taking 2006 as the base reference year. The movements of every company are studied for each the said period. A company could move from Grade C to Grade B, Grade B to Grade A, or Grade C to Grade A from one year to the next. On the other hand, it is also possible for a company to have lower profile in the successive years by moving in the opposite direction; that is, from Grade A to Grade B, Grade B to Grade C, or Grade A to Grade C. Those companies, which are stable, maintain their grades over the study period. It is found that certain companies had moved upwards during the period 2002-2010 (11%), 2007-2008 (12%) and 2008-2009 (54%). But there was a reverse trend in the year 2009-2010, where many companies moved in the opposite direction, which accounted for about 82%. About 69% of the companies retained their grades in the years 2002-2004 while it was 78% in 2004-2006, indicating more stability in the performances of the companies. However, only 45% of the companies retained their grades from 2006 to 2008. There was a nose dive in 2008 -20010 accounting for only 18% of the companies retaining the same grades. This pattern suggests that the reason for the companies to have reverse effects may be due to the instability at the centre, and also the sales and price mix policy of the companies.

Application of Self-Organizing Map to Assessing Performance Stabilities of Top Ranking Companies