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Performance Analysis of FMCG Sector in India


Affiliations
1 Department of Management Studies, I.K. Gujral Punjab Technical University, Kapurthala, Jalandhar, Punjab, India
2 GGSD College, Chandigarh, India
3 Rayat Institute of Management, Chandigarh, India
     

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For the performance analysis of Fast Moving Consumer Goods (FMCG) industry, discriminatory power of financial ratios are examined by using Wilks’ lambda and Multiple discriminant function analysis. For this purpose sample of eighteen FMCG companies listed with Bombay Stock Exchange is taken in to account. Market capitalization is taken as basis for selecting these companies. Data is collected for twelve years ranges from 1 April 2006 to 31 March 2017. For effective implementation of discriminant analysis, firstly average stock market returns are computed from the annual stock prices of the selected companies and average stock market returns are classified in to three groups viz. ‘Market Under-Performers’, ‘Market Average-Performers’ and ‘Market Out-Performers’. It has been found that revenue from operations/share is the most important ratio and having impact to assess the company’s market performance. Debt equity ratio and inventory turnover ratio having moderate impact in assessing the company’s stock market performance of companies and dividend payout ratio is the ratio having less impact in assessing the company’s stock market performance.

Keywords

Multiple Discriminant Analysis, FMCG, Average Stock Market Return, Financial Ratios.
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  • Alayande, S. A., & Adekunle, B. K. (2015). An overview and application of discriminant analysis in data analysis. Journal of Mathematics, 11(1), 12–15.
  • Altman, E. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 589-609.
  • Banerjee, S., & Pawar, S. (2013). Predicting consumer purchase intention: A discriminant analysis approach. NMIMS Management Review, 23, 113–129.
  • Bhunia, A. (2008). A discriminant analysis and prediction of liquidity-profitability. Vidyasagar University Journal of Commerce, 13, 100–106.
  • Bhunia, A. (2011). A study of financial distress based on MDA. Journal of Management Research, 3(2), 1–18.
  • Brown, M. T., & Tinsley, H. E. A. (1983). Discriminant analysis. Journal of Leisure Research, 15, 290–310.
  • Celen, A., Erdogan, T., & Taymaz, E. (2005). Fast moving consumer goods conditions and policies. Working Papers in Economics. Middle East Technical University, Economic Research.
  • Charabji, A., Ali, H. F., & Mrrash, M. (1993). Predicting the government’s decision to seek rescheduling of external debt. Journal of Applied Economic, 25(6).
  • Chen, K. H., & Shimerda, T. A. (1981). An empirical analysis of useful financial ratios. Financial Management, Spring, 51-60.
  • Chin-Fook Yap, B., Fie-Gun Yong, D., & Wai-Ching, P. (2010). How well do financial ratios and multiple discriminant analysis predict company failures in Malaysia. International Research Journal of Finance and Economics, 54, 166–175.
  • Cochran, W. G. (1974). On the performance of the linear discriminant function. Technometrics, 6, 179–190.
  • Dillon, W. R., & Goldstein, M. (1984). Multivariate analysis. New York, NY: Wiley.
  • Edward, A. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23, 589–609.
  • Eisenbeis, R. A., & Avery, R. B. (1972). Discriminant analysis and classification procedures: Theory and applications. Lexington, MA: D.C. Heath & Co.
  • Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annuals of Eugenics, 50, 179-188
  • Gupta, S. K., & Sharma, R. K. (n.d.). Management accounting. Bangalore: Kalyani Publishers.
  • Gupta, S. P. (2000). Statistical methods. New Delhi: Sultan Chand & Sons.
  • Huang, Q., & Liu et al. (2002). Face recognition using Kernel-based Fisher Discriminant Analysis. IEEE International Conference on Automatic Face and Gesture Recognition (pp. 205–211).
  • Huberty, C. J. (1975). The stability of three indices of variable contribution in discriminant analysis. Journal of Experimental Education, 44, 59–64.
  • Joy, O. M., & Tollefson, J. O. (1975). On the financial applications of discriminant analysis. Journal of Financial and Quantitative Analysis, 10, 723–739.
  • Kaveri, V. S. (1980). Financial ratios as predictor of borrower’s health. New Delhi: Sultan Chand & Sons.
  • Khatri, D. K. (2016). Financial ratios, econometrics and prediction of corporate bankruptcy: An empirical study. International Journal of Accounting Research, 4(128).
  • Kothari, C. R. (1990). Research methodology, methods & techniques. New Delhi: New Age International Pvt Ltd Publishers.
  • Letza, S. R., Kalupa, L., & Kowalski, T. (2003). Predicting corporate failure: How useful are multi-discriminant analysis models? The Poznan University of Economics Review, 3(2), 5–11.
  • Lev, B. (1974). Financial Statement Analysis a New Approach. Englewood Cliffs, NJ: Prentice-Hall.
  • Mann, P. W., Sharma, S., & Dhingra, N. (2012). Role and influence of children in buying children’s apparel. Pacific Business Review International, 4(3), 45–50.
  • Maricica, M., & Georgeta, V. (2012). Business failure risk analysis using financial ratios. Procedia - Social and Behavioral Sciences, 62(2012 ), 728-732.
  • McKinsey & Company. (2013). The 30$ trillion decathlons: How consumer companies can win in emerging markets. Retrieved from https://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/winning-the-30-trillion-decathlon-going-for-gold-in-emerging-markets.
  • Mohamed, S., Li, A. J., & Sanda, A. U. (2001). Predicting corporate failure in Malaysia: An application of the logit model to financial ratio analysis. Asian Academy of Management Journal, 6(1), 99–118.
  • Mohanty, S. (2002). An alternative to crisis credit rating: Using discriminant.
  • Pandey, I. M. (2011). Financial management. New Delhi: Vikas Publishers Pvt. Ltd.
  • Patel, H. M. (1977). Banking development in India: Outlook for future. The Banker, 24, 9–12.
  • Rencher, A. C. (1992). Interpretation of canonical discriminant functions, canonical variates, and principal components. Amer. Statistician, 46(3), 217–225.
  • Rajan, S. (1991). Measuring failure. The Banker, 38, 32–34.
  • Saqib, N. (2017). Drivers to FMCG sector in Indian emerging market. International Conference on Latest Innovations in Science, Engineering and Management (pp. 284–297).
  • Saupe, J. L. (1965). Factorial-design multiple discriminant analysis: A description and an illustration. American Educational Research Journal, 2, 175–184.
  • Taffler, R. J. (1983). The assessment of company solvency and performance using a statistical model. Accounting and Business Research, Autumn, 295-307.
  • Taffler, R., & Howard, T. (1977). Going, going, gone-four factors which predict failure. Accountancy, 50–54.
  • Walter, J. E. (1959). A discriminant function for earnings price ratios of large industrial corporations. Review of Economics and Statistics, 41, 44–52.

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  • Performance Analysis of FMCG Sector in India

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Authors

Rosy Dhingra
Department of Management Studies, I.K. Gujral Punjab Technical University, Kapurthala, Jalandhar, Punjab, India
Kapil Dev
GGSD College, Chandigarh, India
Madhuri Gupta
Rayat Institute of Management, Chandigarh, India

Abstract


For the performance analysis of Fast Moving Consumer Goods (FMCG) industry, discriminatory power of financial ratios are examined by using Wilks’ lambda and Multiple discriminant function analysis. For this purpose sample of eighteen FMCG companies listed with Bombay Stock Exchange is taken in to account. Market capitalization is taken as basis for selecting these companies. Data is collected for twelve years ranges from 1 April 2006 to 31 March 2017. For effective implementation of discriminant analysis, firstly average stock market returns are computed from the annual stock prices of the selected companies and average stock market returns are classified in to three groups viz. ‘Market Under-Performers’, ‘Market Average-Performers’ and ‘Market Out-Performers’. It has been found that revenue from operations/share is the most important ratio and having impact to assess the company’s market performance. Debt equity ratio and inventory turnover ratio having moderate impact in assessing the company’s stock market performance of companies and dividend payout ratio is the ratio having less impact in assessing the company’s stock market performance.

Keywords


Multiple Discriminant Analysis, FMCG, Average Stock Market Return, Financial Ratios.

References