AN EMPIRICAL STUDY ON COMPARISON & FORECAST OF FMCG PERSONAL CARE STOCKS VS FMCG NIFTY

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1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 7, July 2018, pp , Article ID: IJMET_09_07_011 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed AN EMPIRICAL STUDY ON COMPARISON & FORECAST OF FMCG PERSONAL CARE STOCKS VS FMCG NIFTY SHANTHAGOWRI B Research Scholar VIT Business School, VIT University Vellore, TamilNadu, India DR. SEETHA RAM VEDANTAM Assistant Professor, Department of Technology Management, School of mechanical Engineering VIT University, Vellore, TamilNadu, India ABSTRACT Purpose Fast moving consumer goods industry is moving fast on the secondary markets across the globe. However, diversified segments of the sector have varied performance at different countries. In India, this sector is growing rapid and is grabbing attention of all types of investors in the market. Hence, it is felt necessary to understand whether stocks listed in this segment are really defensive for long term investors or not and do they influence the whole indices or not. Methodology Current study is an exploratory study for which data is collected from eight personal care stocks listed on National Stock Exchange from 1stJanuary, 2015 till 18thSeptember, 2017 considering daily closing prices. A sample of 672 is considered for which statistical tools such as Pearson s correlation coefficient, covariance, price variance analysis, and augmented dickey fuller unit test are applied. Further, to do a thirty week forecasting, to understand the quality of forecasting and seasonality, auto-regressive integrated moving average method and exponential smoothing process are applied. Findings Results indicate that two of the eight companies' stocks are highly divergent in nature and doesn t influence the indices movement. However, these two stocks are good for long term investors as they are traded at consistent price and deviation in price is also nominal during the study period. It is also observed that, there is no seasonality influence amongst selected stocks and trend is present for six out of eight stocks with some showing additive trend while others multiplicative. Value Advantageous for prospective investors to understand and select an appropriate company s stock for investment, based on the historical data assessment. Keywords: FMCG, NIFTY, Personal Care, Seasonality 97 editor@iaeme.com

2 An Empirical Study on Comparison & Forecast of FMCG Personal Care Stocks Vs Fmcg Nifty Cite this Article: Shanthagowri B and Dr. Seetha Ram Vedantam, An Empirical Study on Comparison & Forecast of FMCG Personal Care Stocks Vs Fmcg Nifty, International Journal of Mechanical Engineering and Technology, 9(7), 2018, pp INTRODUCTION Fast Moving Consumer Goods (FMCG) is the fourth largest sector in Indian economy. It has three segments Food &Beverages, HealthCare, Personal &House hold care(ibef, 2017). It contributes about 47.3 billion of business and creates employment to more than 3 million people across India (Assocham and Tech Sci research, 2017).Food and Beverages industry contributes 19 percent to overall market share in terms of revenue, while health care industry has a share of 31 per cent. Personal & household care has a share of 50 percent which is a leading segment in the FMCG market(ibef, 2017).Personal care segment products comprise hair care, skin care, oral care, personal wash, soaps, cosmetics, toiletries and feminine hygiene (Assocham and Tech Sci research, 2017).India s personal care segment is valued at 54.6 billion and on an average an Indian spends 8% of his/her income on these personal care products(na Kumar and Joseph, 2015).The household and personal care account for 50% of the market share and personal care about 22.7% (IBEF, 2017). Hair care is the leading segment with 23% of the total FMCG market in revenue terms and food products is second with 18% health and oral care 16% (IBEF, 2017).It is observed that FMCG sector has grown from 16 to 21 % in the past two years. It is also expected that FMCG market size is likely to shoot up from 49 billion in to billion by 2020 and likely to grow from 9 to 9.5 % in FY (Madhan, Sabnavis & Kansara, 2017) supported by expectations of the total consumption expenditure reaching nearly US$ 3,600 billion by 2020 from US$ 1,469 billion in 2015(IBEF & Tech Sci, 2016).Increased awareness of products and brands, rise in demand, easy access to market with strong distribution, growing rural market with rising income and purchase drive, launch of numerous new products, shift in lifestyle, Government s FDI reforms are the important factors for the FMCG sectors growth (IBEF & Tech Sci, 2016) combined with modern retail market channelization which has been anticipated to mount up from 600 billion US dollars in the year 2015 to 1 trillion US dollars by 2020 and estimated to increase the growth up to 20% per annum(ibef & Aranca, 2018). 2. REVIEW OF LITREATURE It is observed that personal care FMCG stocks are best choice for long term and rationale investors, as it proves to be stable, depicts less fluctuations in price, least influenced by market and economic factors like inflation. It is fundamentally and financially sound with a lot of scope for future growth (G.Sudarsana Reddy, 2013).Analysts once who have looked upon FMCG stocks as lukewarm now vote for FMCG stocks as safe and protective accompanied with small players threatening the market share of organized ones and existence of short lived activity of preventing them from any further fall in prices.(anand.a,2007). A stock or sector can be categorized as defensive stocks if the measure of change in stock prices in comparison to overall stock market i.e. BETA is less than one indicating that the stock will move less than the overall market, its ROE must be greater than 25% for minimum 5 years and track of stable dividend yield. In order to find out the best of buy in FMCG stocks sector using fundamental and technical analysis for the data of Researchers selected FMCG stock prices and found out that, Dabur and Godrej are more volatile, Godrej Consumer Products Ltd. and Hindustan Unilever Ltd. as best buy for long term investors. He also opined that Dabur and Godrej are overvalued hence short term 98 editor@iaeme.com

3 Shanthagowri B and Dr. Seetha Ram Vedantam investors need to hold on to the stocks to gain in the long run where the share prices of these companies appreciate. He also pointed out that Dabur shares are apt for investors who expect good dividends, while HUL is a good choice for both long and short term investors as it is undervalued by the market(sulaiman.e,2013). Some researchers found CNX FMCG is not weak form efficient hypothesis and individual stocks of FMCG have lesser volatility(hemalatha,2014). On examining various days, effect in a week effect on different sectors the results revealed FMCG sector stocks have influence only on Fridays(Banumathy&Azhagaiah,2014). Whereas, some researchers found Tuesdays and Wednesdays to be positive and significant for FMCG sector stocks (Dhiman and Jassal, 2016 ). Forecasting is an important factor in stock market for prediction of future prices and so is the ARIMA model and its effectiveness on diversified sectors with different spans of time periods. Researchers found that forecasting of FMCG stocks using ARIMA gives the most effective results in predicting stock prices as well as precision with 95% and other sectors all above 85% (Mondal et al.,2014). On extensively studying the behaviour of FMCG sector time series during Jan 2010 to Dec 2016 using six methods of forecasting, it is proved that FMCG sector stocks perform better during September month and subdued in February month. It is also observed that, in FMGG time series the trend component seems to be outstanding factor, while seasonal and random components though significant do not have an effect on the overall time series(chaudhri,j.s & T.D. 2017). 3. OBJECTIVES 1. To observe the performance of selected FMCG personal care stocks listed on FMCG NIFTY. 2. To find out whether there is a relationship between movement of selected independent FMCG stock s price and FMCG NIFTY indices during the study period. 3. To understand whether selected FMCG personal care stocks have influenced FMCG NIFTY indices during the study period. 4. To apply appropriate statistical techniques and prove the influence of selected personal care stocks on FMCG NIFTY movements. 4. METHODOLOGY There are fifteen companies listed under FMCG segment that comprise personal care and food & beverages under FMCG NIFTY. However, only eight companies qualify for personal care segment. Hence, all the eight companies are selected for the current study. The eight personal care stocks selected for the study are Colgate Palmolive Ltd. (COL), Dabur India Ltd., Emami Ltd (Emami), Hindustan Unilever Ltd. (HUL), Marico Ltd. (Marico), Godrej Consumer Products Ltd. (GPCL), Godrej Industries Ltd. (GIL) and Procter and Gamble India Ltd. (P&G).Selected stocks are independently analyzed in detail and their share price movement is compared with FMCG NIFTY Index movement. After correlation, variance analysis is studied using IBM SPSS version and covariance using E-Views 9.5 student version. While testing for covariance; it is realized that the stock price is in monetary value i.e. INR and FMCG NIFTY is in index value, which will hinder the process of estimation. Hence, it is decided to bring both the estimators on to a common parameter by finding out price variance of each stock and FMCG NIFTY indices for the study period applying IBM SPSS version and then proceeded with further assessment of testing the stationary by performing Augmented Dickey Fuller Unit Root Test 99 editor@iaeme.com

4 An Empirical Study on Comparison & Forecast of FMCG Personal Care Stocks Vs Fmcg Nifty by setting null and alternate hypothesis such that forecasting can be done for the selected stock. As regards forecasting, the researchers considered 30 weeks (24 th September, 2017 till 15 th April, 2018) forecast period for which data from 28 th December, 2014 till 17 th September, 2017 with Sunday to Saturday as study week period. Data is run using Tableau Desktop Version 10.2, since forecasting can be done with higher rates of accuracy for a larger sample using this software. After forecasting, it is felt necessary to understand quality of forecasting and seasonal assessment, for which tests such as ARIMA using GRETL Version and Exponential Smoothing technique using Tableau Desktop 10.2 Version for the weekly average prices trend is conducted and the results are interpret. The reason for considering GRETL software is due to non-availability of ARIMA option in Tableau Desktop 10.2 Version. However, exponential smoothing is available with Tableau Desktop 10.2 Version. In the process of data collection, the researchers experienced difficulties, as Colgate Palmolive Ltd. stock is split on 23 rd September, 2015 into two shares due to which evaluation became difficult and hence, to maintain uniformity across the stocks and study period, researchers have halved the stock price of concerned company from 1 st January, 2015 till 22 nd September, 2015; as the time period for which the stock traded as a single share is less than(183 out of 672 observations) the post-split time period considered for the study. 5. RESULTS & DISCUSSION Table 1 Augmented Dickey Fuller Unit Root Test of Selected FMCG Personal Care Stocks Company Name ADF (Stat) Probability value Result Critical value COL T stat < Critical value DABUR T stat < Critical value EMAMI T stat > Critical value GCPL T stat < Critical value GIL T stat < Critical value HUL T stat < Critical value MARICO T stat < Critical value P&G T stat < Critical value FMCG NIFTY T stat < Critical value Source E-views 9.5 student version results consolidated Interpret Data is Non Stationary and has unit The daily closing prices of 672 observations are tested for stationary of their mean data and variance; of FMCG personal care stock prices and FMCG NIFTY indices value which is carried out independently by running ADF unit test with the following null and alternate hypothesis 1. H0- There is a unit for the series and selected FMCG personal care stocks will follow random walk and are non-stationary. 2. H1 - There is no unit and the selected FMCG personal care stocks are stationary editor@iaeme.com

5 Shanthagowri B and Dr. Seetha Ram Vedantam The results are compared with all critical values of MacKinnon at 1%, 5% and 10% significance levels (-3.43), (-2.86), () respectively which is found to be same for all variables. Consolidated results are tabulated as given in Table No-3 shows that only Emami stock depicts ADF value to be greater than its critical value and accept the null hypothesis that it has unit and is non-stationary of its mean data. While, rest of the companies stock prices show ADF value less than critical value, showing the alternate hypothesis is accepted. It can be concluded from the results that, except Emami shares, all other stocks are showing stationary relationship between stock price and indices value. From the results, one can understand the extent of influence of selected stock s price on selected index value.fmcg NIFTY Indices (0.91) influence on HUL (0.29) and GIL (0.30) is very less and the individual companies are moving at a very slower pace i.e. not even one third of FMCG indexes pace. This helps these two companies managements to take action to cope up with the other players in the market. The other six companies i.e. P&G (0.85), Dabur (3.2), Emami (4.14), GCPL (2.4), and Marico (2.10) and COL (1.6) are either moving along with or with a higher pace than the index movement (0.91) showing stationary existence amongst them. After completing the testing of stationary using unit test and differentiating the time series of selected FMCG personal care stocks; one can apply exponential smoothing and ARIMA models which are most commonly applied methods in time series forecasting. Exponential smoothing is applied to identify whether there exists any trend or seasonality in time series data and ARIMA for the purpose of estimating autocorrelation in the data set within selected personal care stocks and FMCG NIFTY Index values. Table 2 ARIMA FORECASTING OF SELECTED FMCG PERSONAL CARE STOCKS Model 1 ARMAX, using observations 2015/01/ /07/28(T = 672) (Dependent variable: FMCGINDEX and Standard errors based on Hessian) Coefficient Std. Error Z p-value Const < *** phi_ < *** theta_ COL DABUR < *** EMAMI ** GCPL ** GIL < *** HUL < *** MARICO *** P & G Mean dependent var S.D. dependent var Mean of innovations S.D. of innovations Log-likelihood Akaike criterion Schwarz criterion Hannan-Quinn Real Imaginary Modulus Frequency AR Root MA Root Source: GRETL version Considering the FMCG Index as dependent variable and eight selected FMCG Personal care stocks as independent variables, ARIMA is run in GRETL software for all the 672 observations collected on daily basis from Jan 1 st, 2015 to July 28 th, 2017 and the results are projected in table -2.In the AR term-modulus with nearly 1.02 which is almost equal to one indicates that there is no considerable variance between the selected variables indicating that editor@iaeme.com

6 An Empirical Study on Comparison & Forecast of FMCG Personal Care Stocks Vs Fmcg Nifty the dependent variable FMCG NIFTY indices has no influence on the selected FMCG personal care stocks which are independent variables. Table 3 FORECASTING by Exponential Smoothing of FMCG Personal care stocks Model Quality Metrics Smoothing Coeff Level Trend Season RMSE MAE MASE MAPE (%) AIC Alpha Beta Gamma COL Multiplicative Multiplicative None , Dabur Additive None None Emami Additive None None , GCPL Multiplicative Multiplicative None , GIL. Additive Additive None HUL Multiplicative Multiplicative None Marico Multiplicative Multiplicative None P&G Multiplicative Multiplicative None , Study of seasonal influence trend with 13 Weeks cycle and random component values of time series by exponential smoothing enables one to understand the growth pattern, seasonal characteristics and the degree of randomness exhibited by time series of all the selected FMCG personal care stocks. Exponential smoothing model with trend or seasonal components is effective when the measure to be forecasted exhibits trend or seasonality over a period of time on which the forecast is dependent. The results given above reveal that Dabur, Emami and GIL depict additive nature, while, all other stocks show multiplicative nature. It is also observed that, whenever there is multiplicative trend, the stocks are positive in their level as well as trend, but as regards additive nature stocks, they have higher independence in reflecting stock price movement and consistency in price movement as well. 6. CONCLUSION & LIMITATIONS From the results one can understand that three (P&G, GIL and HUL) of the selected companies are showing close correlation values and are influencing one another s price in stock market there by influencing FMCG NIFTY during the study period. However, the degree of price dependence is observed to be 70 to 80% only. Further, it is observed that, the degree of price variance in FMCG NIFTY indices to independent stocks such as P&G is found to be zero; while in case of HUL and GIL to indices, it is slow but not zero. This indicates that HUL and GIL do have positive impact on FMCG NIFTY indices movement making to prospective investors select these stocks for their investment portfolio. When the trend evaluation is compared, Dabur and Emami have close relationship and are showing additive trend with three to four times higher than selected indices movement, while rest of the selected companies are showing multiplicative trend, this gives an indication that, in additive trend companies, there are diversified factors, that show influence collectively. Research Limitations In the current study, only personal care segment is evaluated rather considering all the three segments of FMCG industry. Another limitation to the study is, one of the sample companies which just supplies raw materials, but is listed as a personal care company on NIFTY is part of assessment. REFERENCES [1] IBEF (2017) "Fast moving Consumer Goods", India brand equity foundation,(july), pp1 38 [2] Assocham and Tech Sci research (2017) "Indian FMCG Market 2020", Research Report. [3] NA Kumar and Joseph (2015) "A Study on consumer behaviour towards FMCG products among the rural-suburban HHs of Ernakulam", International Journal of Economics & Management Sciences, Vol. 3 No editor@iaeme.com

7 Shanthagowri B and Dr. Seetha Ram Vedantam [4] Madhan, Sabnavis & Kansara, D. (2017) "FMCG Industry Structure & Prospects CARE". [5] IBEF & Tech Sci (2016) "Fast moving Consumer Goods", India Brand Equity Foundation, (January) [6] IBEF & Aranca (2018) "Fast moving Consumer Goods", Indian Brand Equity Foundation, (February), pp [7] G. Sudarsha reddy (2013) "Analysis of select FMCG companies stock performance with market", ELK Asia Pacific Journals of Finance and Risk Management, Vol. 4 No. 1, pp [8] Anand, A. (2007) "FMCG & Pharma : down but not out ; Investors have been lukewarm to the FMCG and pharma sectors. But the future looks brighter than the immediate past.", Proquest. Living Media India, Ltd. [9] Sulaiman, E. (2013) "Comparative study on valuation of select personal care sector scripts in Indian stock market", International Journal of Application or Innovation in Engineering & Management,, Vol. 2 No.12, pp [10] Hemalatha, K. N. (2014) "Testing on weak form efficiency & Volatility of FMCG sector : The evidence from National stock exchange", International Journal on recent and innovation Trends in computing and Communication, Vol.2 No.9, pp [11] Banumathy, K. and Azhagaiah, R. (2014) "Risk return relationship in sectoral indices: some evidence in India., Vol. 5 No. 2, pp [12] Dhiman, B. and Jassal, T. (2016) "Sectoral analysis of week day anomaly", International Journal on Applied Business and Economic research, Vol. 14 No. 7, pp [13] Mondal, P., Shit, L. and Goswami, S. (2014) "Study of effectiveness of time series modelling (ARIMA) in forecasting stock prices", Vol. 4 No.2, pp [14] Chaudhuri, J. S. and T. D. (2017) "A predictive analysis of the Indian FMCG Sector using time series decomposition - Based approach", Journal of Economics Library, Vol. 4 No. 2, pp [15] Jakeer Hussain Shaik, Santoshi bhuma and Vymisha Vankayala, A Study on Testing Performance of Nifty Commodity index constituent companies in India Using Carhart Four Factor Model: Empirical Analysis, International Journal of Civil Engineering and Technology, 9(1), 2018, pp ANNEXURES Source Tableau 10.2 student version editor@iaeme.com