A STUDY ON QUALITY OF EARNINGS IN FMCG SECTOR

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1 A STUDY ON QUALITY OF EARNINGS IN FMCG SECTOR B. Sudheer Kumar 32 Dr. V. Mallikarjuna 33 ABSTRACT When any investor goes for investment, he sacrifices his present benefits for the sake of future profits. Any investment made is to earn profits by accepting some sort of risk. In the wake of present Scenario of highly publicized financial frauds and failures and accounting manipulations, the emphasis on earnings quality has renewed. That s why investors and creditors from all over the world are turning toward the assessment of the earnings quality of the individual company in which they are trying to invest their investment. Through present study on quality earnings, it was found that various earnings quality proxy s which represent the quality of earnings position in the organization. The quality earnings from a company to company vary according to the parameters they depend on. In the study, the quality earnings often are high in personal care industry and leather industry. The results of present investigation show that intellectual capital has positive impact on earnings quality, because relationship between values and is linear and inversely proportional and its lead to conclude that intellectual capital has a positive role in best financial practices and reporting. KEYWORDS Calculation of Intellectual Capital, Human Capital Coefficient, Structural Capital Coefficient etc. INTRODUCTION There are many way through which the organizations are manipulating the financial statements, they use certain approaches that help a firm to hide the true conditions. The investors need to assess the extent to which a firm's reported earnings are free from mistake or manipulation, so they should have an idea about the possible approaches and ways the firms use to lower its earning quality and increase their speculative profits. They are: Recording revenue too soon or of questionable quality, Recording fictitious revenue, Boosting income with one-time gains, Shifting current expense to a different period, Failing to record or improperly reducing liabilities, Shifting current revenue to a later period, and Shifting future expenses to the current period as a special charge. NEED OF STUDY In order to understand a company financial report genuinely, you need to understand the accounting concepts that are used to justify the accounting rules. Basically, these accounting concepts provide rule makers with guidance that will result in financial reports the best help investors, creditors and other financial report user s asses. Investors overlook factors outside the financial reporting system that quantify their profits or losses most of the time without even their acknowledgement, by the study of earning quality of the firm we can throne a light on all the other factors that can affect earnings quality and organizations true earnings, by which the investors, creditors, share holders and others depend on the firm s financial well-being get benefited. OBJECTIVES OF THE STUDY To estimate earning quality of selected industries, To develop between intellectual capital and earning quality, To establish relationship between earning quality and stock returns, To develop relationship between values added intellectual co-efficient and its components, To develop between discretionary accruals with other components. 32 Assistant Professor & H.O.D., Department of MBA, Vaagdevi Institute of Technology & Science, Andhra Pradesh, India, bskmba06@gmail.com 33 Professor & H.O.D., Department of MBA, Sri Sai Institute of IT and Management, Andhra Pradesh, India, v.mallik@yahoo.com 1788 P a g e

2 LITERATURE REVIEW There are many literatures published on the different approaches used for assessment of quality of earnings. Earnings quality is used in numerous empirical studies to show trends over time; to evaluate changes in financial accounting standards and in other institutions, such as enforcement and corporate governance; to compare financial reporting systems in different countries; and to study the effect of earnings quality on the cost of capital. Jennifer bender and frank Nielsen (2013) indicated that earning quality as an investment signal has been popular among equity portfolio managers for the last decade. The basic idea behind this accruals anomaly is that stocks with high and increasing accruals tend to have low earnings quality, while stocks with low and decreasing accruals tend to have high earning quality. The earnings quality signal stopped working in the mid-2000s, but has staged a remarkable rebound since the end of The authors evaluate whether earnings quality is a true alpha signal, a risk factor, or both. They find that, in the periods when the signal worked, the strategy was largely driven by stock selection, suggestion that earnings quality is indeed an alpha signal. The authors also find that earnings quality is not a good risk factor, in that it does not have high statistical significance when regressed cross-sectional on returns, along with other well-known risk factors, and is not very volatile over time. Overall, their results indicate that earnings quality may be that rare example of a pure alpha factor. Ralf Ewert and Alfred Wagenhofer (2009) discussed and evaluated the usefulness and appropriateness of commonly used earnings metrics. In a rational expectations equilibrium model, through studying the information content of earnings that can be biased by a manager who has market price, earnings, and smoothing incentives. It defines earnings quality as the reduction of the market s uncertainty about the firm s terminal value due to the earnings report and compares this measure with value relevance, persistence, predictability, smoothness, and accrual quality. The evaluation is based on their ability to capture the effects of a variation of the manager s incentives and information, and of accounting risk. It is found that each metric captures different effects, but some of them, including value relevance and persistence, are closely related to our earnings quality measure. Discretionary accruals are problematic as their behavior depends on specific circumstances. These results provide insights into regulatory changes and guidance for selecting earnings quality metrics in empirical tests of earnings quality. Jeffrey T. Doyle, Weili Ge, and Sarah McVay (2007), examined the relation between accruals quality and internal controls using 705 firms that disclosed at least one material weakness from August 2002 to November 2005 and find that weaknesses are generally associated with poorly estimated accruals that are not realized as cash flows. Further, it is found that this relation between weak internal controls and lower accruals quality is driven by weakness disclosures that relate to overall company level controls, which may be more difficult to audit around. No such relation for more auditable, account specific weaknesses is found. Similar results using four additional measures of accruals quality: discretionary accruals, average accruals quality, historical accounting restatements, and earnings persistence are estimated. The results obtained are robust to the inclusion of firm characteristics that proxy for difficulty in accrual estimation, known determinants of material weaknesses, and corrections for self selection bias. Nahum D. Melumad and Doron Nissim (2008), discussed about earning quality and the related concepts of earning management, focusing on the primary financial accounts. For each key line-item from the financial statements, it is summarized that accountings and economic consideration applicable to that item, discuss implications for earning quality, evaluate the susceptibility of the item to manipulation, and identify potential red flags. The red flags and specific issues discussed for the individual line-item provide a frame work for fundamental and contextual analysis by academic researcher and practitioner METHODOLOGY & COLLECTION OF THE TA In this study, secondary data was used to achieve the designated Objectives. The secondary data is from various websites, magazines, journals and financial newspapers. The collected parameters are Revenue, debt, assets, book value and cash flow from operations, fixed assets, expenses and employee cost. The analysis was made based on secondary data, published papers and expert opinion. TA ANALYSIS PROCEDURE For the study, certain approaches are used to assess the quality of earnings, intellectual capital and stock returns P a g e

3 Calculation of Quality Earnings Quality of earnings is calculated through the following formula i,t :Is discretionary accrual that is a proxy of earnings quality TA i,t : Represents total accruals measured as net income minus cash flow from operations of firm i in year t. i.e., TA = NI CFFO; NI = NET INCOME; CA = CAS FLOW FROM OPERATION REV i, t is REENUE of firm i in year t REC i, t is RECEIABLES of firm i in year t PPE i, t is plant, property and equipment i.e., firms i FIXED COST in year t A i, t-1 is TOTAL ASSETS at the end of year t-1 of the firm i Later the value is calculated by using the multiple regression equation, which is as: Follows, Here the equation is in the form of y = a + x1b + x2c + x3d, through applying the regression analysis to the above equation we can get value. The regression analysis can be applied by the software that is analysis tool pak, after applying regression to the above equation the resulted x1 intercept, x2 intercept, x3 intercept should be substituted in the formula to get the value of. : Discretionary Accurals (it): Caluculation of Intellectual Capital () Value Added Intellectual Coefficient () Calculation 1. Value Added (VA) VA = OUT IN, OUT = Revenues, IN = Expenses 2. Human Capital Coefficient (HCE) HCE = VA/HC, HC = Employee cost 3. Structural Capital Coefficient (SCE) SCE = SC/VA, SC = VA-HC, SC = Structural cost 4. Capital Employed Efficiency (CEE) CEE = VA/CA, CA = Book-value of net assets 5. Value Added Intellectual Coefficient () = HCE+SCE+ CEE Caluculation of stock returns (R) STOCK RETURNS (R) = (P 1 -P 0 )/P 0 *100 Here, P 1 = Closin price P 0 = Opening price 1790 P a g e

4 Caluculation of Leverage ratio and size LEV IT = Debt/Total Assets, SIZE IT = Total assets in millions TA ANALYSIS AND INTERPRETATIONS General The secondary data was analyzed using the statistical technique and the obtained results were presented in the form of graphs and tables. The obtained results were discussed with the help of existing literature and the expert opinion. Assessment of Earnings quality for ITC Table-1: Values of of ITC Year Year Year Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 10 ANOVA d.f. SS MS F Significance F Regression Residual Total Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95% Upper 95% Intercept X Variable X Variable Interpretation: It can be seen that the ITC company exhibit highest earning quality in 2009, this indicates low values and high earning quality and the firm also shows low earning quality in 2014 which is Note: I can mention one sample calculation of earning quality of selected industries and remaining as usual same as above example. Relation b/w and for ITC Table-2: Relation between and for ITC YEAR YEAR P a g e

5 Volume 4, Number 3, July September 2015 Figure-1: Relationship between and of ITC Relationship b/w and y = x R² = 1 Linear () Interpretation: The relations of and have a directly proportional. So the company represents same that the will have a positive influence on the because in the company using its intellectual capital efficiency then the officials does not try to manipulate the earninga of the company. Note: I can mention one sample calculation of intellectual capital and earning quality selected industries and remaining as usual same as above example. Relation between Stock Returns and for ITC Table-3: Relation between Stock Returns and for ITC YEAR Stock Returns YEAR Stock Returns Figure-2: Relationship b/w STOCK RETURNS and of ITC Relationship b/w Stockreturns and y = x R² = Linear () Stockreturns Interpretation: It is observed that the Stock returns and relationship is inversely proportional because high accruals suggesting low-quality earnings are associated with poor stock returns in that relative year. When the Stock returns are high, will be less which indicates earnings quality is high. The relationship between stock returns and of Itc is not significant because of R 2 = Note: I can mention one sample calculation of earning quality and stock returns of selected industries and remaining as usual same as above example P a g e

6 Volume 4, Number 3, July September 2015 Relation b/w and its Components for ITC The values of and it component of ITC are presented in tables below: Table-4(a) Table 4.4.1(b) Table 4.4.1(c) Year HCE Year SCE Year CEE Figure-3: Relationship b/w and HCE of ITC Relationship b/w and HCE y = x R² = Linear () HCE Interpretation: HCE represents the (human capital coefficient) intellectuals that are entered in the company they contribute for the efficient to the firm, which in term affects the quality earnings. Figure-4: Relationship b/w and SCE of ITC Relationship b/w and SCE y = x R² = Linear () SCE 1793 P a g e

7 Volume 4, Number 3, July September 2015 Figure-5: Relationship b/w and CEE of ITC Relationship b/w and CEE y = 1.004x R² = 1 Linear () Interpretation: SCE (structural capital co-efficiency), represents the optimum structure of the firm which points out low debts and better investment to enhance the value of the company and intellectual if considered appropriate structural capital, if not the debts will be high than the profits which becomes the reason for the companies to use manipulated earnings. CEE (Capital employed efficiency), is usually available for the firm for the purpose of operations it should be used intellectually, by the intellectual use of capital employed in the firm only the firm can perform better and avoid the fraud earnings representation in the financial statements. Note: I can mention one sample calculation of value added intellectual co-efficient and its components of selected industries and remaining as usual same as above example. Relation b/w and its components of ITC The values of and its components of ITC is presented below: CEE Table-5(a) Table-5(b) Table-5(c) Year YEAR LEV YEAR SIZE , , , , , , , , , , Figure-6: Relation b/w and of ITC Relationship b/w and y = x R² = 1 Linear () 1794 P a g e

8 SIZEit LEVit Volume 4, Number 3, July September 2015 Figure-7: Relation b/w and LEVit of ITC Relationship b/w and LEVit LEV Linear (LEV) y = -2E-07x R² = Figure-8: Relation b/w and SIZEit of ITC Relationship b/w and SIZEit y = x R² = SIZE Linear (SIZE) Interpretation: The correlation ship between the and its components is no significant but these components have influenced in the companies quality earnings because all the three components can be manipulated easily. It can also be seen that the relationship between the and its components. Note: I can mention one sample calculation of discretionary accruals with other components of selected industries and remaining as usual same as above example. FINDINGS Through present study on quality earnings, it was found that various earnings quality proxy s which represent the quality of earnings position in the organization. The quality earnings from a company to company vary according to the parameters they depend on. The results of present investigation show that intellectual capital has positive impact on earnings quality, because relationship between values and is linear and inversely proportional and its lead to conclude that intellectual capital has a positive role in best financial practices and reporting. Earnings with high accruals suggesting low-quality earnings are associated with poor stock returns in that relative year. The Human capital efficiency (HCE) and Capital employed efficiency (CEE) both have a positive relation with the whereas Structural capital efficiency (SCE) has an inverse relationship with because the employed capital is not properly used for the operating a structure that makes the intellectuals become efficient. The components of the that are, LEV IT (leverage), SIZE IT (total assets) combine shows a little effect on the majority of the companies however individual components especially has predominant influence on the quality earnings P a g e

9 CONCLUSION The Study of Quality of Earnings is useful for the investors and any person who are depending on the company s financial statement, it helps the investors the firms financial position is real, rather than that reported by the firms itself. The investors are suffer which company is best to invest the money, because of now companies are to show the high earnings only based on that reported earnings shown by the company due to the manipulations done. So through the study the earnings quality of the 10 companies from 1 sector is considered. The Quality of earnings topic arose from the wake of many situations in the present scenario, which are representing the manipulations in the reported earnings to promote the companies shares. It is revealed in the study done that most of the companies try to manipulate the reported earnings at least to a certain extent by adding abnormal earnings to the companies true earnings. The investors who are trying to invest in any company should not only consider the reported earnings but should also analyze quality of those earnings. In the study some of the companies like ITC, Dabur, Britannia, Himalaya, Godrej, Emami, Nestle, Ruchi showed good quality earnings so the small investors should try to invest their investment in these type of companies, whereas speculators can consider the companies like Pidilite, Marico that have somewhat low earnings quality because they are ready to face risk. The companies that have good quality earnings are the companies that pay their taxes properly. So government can give subsides on the taxation in order to encourage the company for maintaining true earnings. REFERENCES 1. Retrieved from 2. Retrieved from 3. Retrieved from 4. McAnally, M. L., A., Srivastava, & C., D. Weaver. (2008). Executive stock options, missed earnings targets, and earnings management. The Accounting Review, 83(1), McVay, S. E. (2006). Earnings management using classification shift- ing: An examination of core earnings and special items. The Account- ing Review, 81(3), Mizik, N., & R., Jacobson. (2007). Myopic Marketing Management: Evidence of the phenomenon and its long-term performance consequences in the SEO context. Marketing Science, 26(3), Roya, Darabi, S., Kamran Rad, & M., Ghadiri. (2012). The Relationship between Intellectual Capital and Earnings Quality. 8. David, Aboody, John, hughes, & Jing, Liu. (2005). Earnings Quality, Insider Trading, and Cost of Capital. 9. Patricia, M. Dechow, & Ilia, D. Dichev. (2002). The Quality of Accruals and Earnings: The Role of Accrual Estimation Errors. 10. Jennifer, Bender, & Frank, Nielsen. (2013). Earnings Quality Revisited. 11. Ralf, Ewert, & Alfred, Wagenhofer. (2009). Earnings Quality Metrics and What They Measure. 12. Jeffrey, T. Doyle, Weili, Ge, & Sarah, McVay. (2007). Accruals Quality and Internal Control over Financial Reporting. 13. Nahum, D. Melumad, & Doron, Nissim. (2008). Line-Item Analysis of Earnings Quality. 14. Peter, R. Demerjian, Baruch, Lev, Melissa, F. Lewis, & Sarah, E. McVay. (2013). Managerial Ability and Earnings Quality. 15. Retrieved from P a g e

10 16. Retrieved from Retrieved from Retrieved from Retrieved from Revenue-R Retrieved from Retrieved from Retrieved from Retrieved from Retrieved from Retrieved from Retrieved from ***** 1797 P a g e