ISSN 2277 6753 - CMRCET - MBA · Dr. D Maheswara Reddy, Suresh Chandra Ch 4. Performance Evaluation...

Vol. 1, No 1 Jan-March, 2012 Journal of Management

Referred Journal of CMR College of Engineering & Technology

Department of Master in Business AdministrationCMR College of Engineering & Technologywww.cmrcetmba.in

Empirical Study On Satisfaction Of The Policyholders Towards The Services

Provided By LIC Of India In Madurai Division

- Dr. J. Arulsuresh

“Efficiency Of Stock Markets - Comparing The Behavior Of Stock Indices Of

NSE And NYSE “

- Dr. A. Patrick, Mrs.R.Sushama

Human Resource Management practices in organized retailing - A study of select

retailers

- Dr. D. Maheswara Reddy, Suresh Chandra Ch

Performance Evaluation of Open Ended Schemes of Mutual Funds

- Dr . Vikas Kumar

Unearthing the Epidemic of Non-Performing Assets a Study With Reference

To Public Sector Banks In India.

- Dr. Hosmani.A.P, Mr.Jagadish Hudagi

Working Capital Management of Indian Electrical Equipment Manufacturers

- A Comparative Study

- T. Chandrabai Dr. K.Venkata Janardhan Rao

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ISSN 2277 6753

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"SUMEDHA Journal of Management Vol. 1, No. 1, Jan-March 2012"

Editorial

This is occasion to rejoice as it gives me immense pleasure in publishing the firstissue of the SUMEDHA Journal of Management. CMR College of Engineering &Technology nurtures and transforms its students, empowering them to gain leverage inthe future as we at CMRCET-MBA strongly believe in “Education with Technology andnot for Technology”. The driving force of this knowledge hub has always been academicexcellence. The institute is committed to develop managers and technical professionalsto keep pace with growing demand for skilled professionals in the global corporate world.CMRCET-MBA has gained reputation for its academic vigour and faculty-studentinteraction. A committed team of faculty and staff plays an integral role in the realizationof the institution’s quest excellence in management, IT emerging fields.

I believe that research is the seed corn for the harvest of benefit as it enhancesthe rate of return on investment and opens plethora of opportunities, it improves theoverall quality of education. At CMRCET-MBA education is imparted through researchand innovation. The realization that the Indian economy to become globally competentmust integrate research with education and industry has been a motivating factor forpublishing this journal as it provides a platform to top notch leaders, researchers andprofessionals to make their latest innovations in research public through SUMEDHAJournal of Management

I would like to thank everyone including eminent educationists, pioneers, researchscholars, academicians, reviewers, editorial board members and the advisory board fortheir unremitting support and help to bring out this journal

Chief Editor

Mr A Kotishwar

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Contents

Page No

1. Empirical Study On Satisfaction Of The Policyholders Towards 3 - 7

The Services Provided By LIC Of India In Madurai Division -

Dr. J Arulsuresh

2. “Efficiency Of Stock Markets - Comparing The Behavior Of Stock 8 - 15

Indices Of Nse And NYSE “

Dr. A Patrick, Mrs R Sushama

3. Human resource management practices in organized retailing – 16 - 26

A study of select retailers -

Dr. D Maheswara Reddy, Suresh Chandra Ch

4. Performance Evaluation of Open Ended Schemes of Mutual Funds – 27 - 42

Dr Vikas Kumar

5. Unearthing the Epidemic of Non-Per Forming Assets 43 - 54

A Study With Reference To Public Sector Banks In India. -

Dr. Hosmani.A.P, Mr Jagadish Hudagi

6. Working Capital Management of Indian Electrical Equipment 55 - 62

Manufacturers-A Comparative Study -

T Chandrabai Dr. Venkata Janardhan Rao

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Empirical Study On Satisfaction Of The PolicyholdersTowards The Services Provided By LIC Of India In

Madurai DivisionDr. J Arulsuresh*

Abstract

The success of the life insurance business depends on the awareness

of the policyholders about the products and satisfaction of the policyholders

regarding the service rendered by LIC of India. Life insurance being a service

sector is no exception to this principle. The basics of Customer Relations

Management (CRM) include a business strategy that focuses on developing and

retaining the relationships existing between customer and organization. CRM

also provides the customer with a much needed avenue to find expression for his

problems, ideas and suggestions. Hundreds of sales leads are lost yearly as

disinterested employees pay slack attention to customer suggestions. A venue is

required for these suggestions. This is supplied by CRM implementation.

1.1 Introduction

The current scenario in the insurance industry is a complex and competitive environmenttinged with little stability. The major hassle the industry faces is obtaining clients. This is due to thefact that the big fish in the insurance industry dominate the sector. It has become increasinglydifficult for this particular sector to gain profits while curtailing costs. Right now insurers canachieve excellent policy administration; good billing systems etc but fall short on the customerfront. However this alone is insufficient to survive on. Insurers have now realized that CRM isessential if they want to deliver high quality services since it satisfies current customers and gainsnew ones. This is because policies get sold only if relationships are built. CRM solves these problemswith its user-friendly, web-based CRM tools that increase sales opportunities

* Assistant Professor, Loyola College, Chennai

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1.2 Methodology

This study is an empirical research based on survey method. It is a blend of both descriptiveand the analytical methods of study. An interview schedule was prepared separately for findingout the perception of the policyholders towards the service rendered by LIC of India.

1.3 Construction of Tools

A pilot study was undergone by the researcher in order to identify the research problem andtools. Based on this, the researcher has decided to use structured interview schedules. With a viewto identify the variable for constructions of the interview schedules, the researcher obtained an in-depth review of previous studies. Moreover, discussions were held with the policyholders andofficers of LIC of India, Madurai Division. In the light of the information gathered, interviewschedules were constructed for this study to collect data from the policyholders.

This was done to assess and test the validity in the context of the LIC of India of Maduraidivision. In this way, the interview schedule was tested. The comments and suggestions offeredby the policyholders were duly incorporated in the interview schedule. Thus the interview schedulewas finalized.

1.4 Sample Design

As per the instructions given by IRDA, the LIC of India opened branches in rural and semiurban and urban areas. The LIC of India Madurai Division is located in six districts. There areabout 25 branches in this division. The researcher has selected all these branches under censusmethod for this study. There are about 300 policyholders selected at random in order to obtain theiropinion of the service offered by LIC of India. That is, 12 policyholders from each branch wereselected.

1.5 Field Work

The field survey, for this study, was conducted by the researcher himself. As each interviewschedule required nearly one hour for securing information. Most of the LIC of India branches inMadurai Division have working hours between 10.a.m and 4.p.m. So the researcher contactedthem after the working hours. On the dates fixed, in the first instance, the policyholders wereinterviewed. As there were 25 branches in the sampling area it took 6 months for the researcherto complete the survey of the policyholders of the LIC of India.

1.6 Data Processing

After completing the data collection, a thorough check was made. The whole interviewschedule was processed for coding the data in a computer. Then, the cross tables were preparedby using experts and appropriate tools were framed to get good results.

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1.7 Framework of Analysis

In order to analyse the perception of the policyholders, techniques namely Percentage Analysisand Factor Analysis were used.

1.8 Opinion about the service rendered by the LIC of India to the respondents – Factor Analysis

Insurance industry is a service-oriented unit. It renders services like available space; displayadequate information, suggestion box and so on to the policyholders. It is essential that LIC ofIndia should attract and satisfy the policyholders in different ways. There are 14 measuresidentified by the researcher and the respondents were asked to fill in the respective columns. Theresearcher has used multivariate technique called factor analysis in order to classify the selectedvariables.

Factor analysis is a statistical method used to describe variability among observed variablesin terms of fewer unobserved variables called factors. The observed variables are modeled aslinear combinations of the factor, plus “error” terms. The information gained about theinterdependences can be used later to reduce to it a set of variables in a data sheet. Factor analysisoriginated in psychometrics and is used in behaviour sciences, social sciences, marketing productmanagement, operations research and other applied science that deal with large quantities of data.

Factor Analysis is a method for investigating whether number of variables of interestY1,Y2,…….Yn are linearly related to a smaller number of unobservable factors F1,F2,…….Fn..Factor analysis is a way of grouping of variables based on the criterion of common characteristicswhich would serve as a common denominator for such a classification.

1.8.1 The Analytical Framework

This technique was adopted to analyse the opinion of the policyholder about the serviceprovided by LIC of India branches in Madurai Division. But the principal factor method withorthogonal variance rotation is mostly used widely available in factor analytic computer programmes.One of the final outcomes of a factor analysis is called rotated factor matrix, a table of co-efficientthat compresses the ratios between the variable and factor that have been prepared. The sum ofthe squares of the factor loading of a variable is called communalities (h2).

The communalities of a factor are its common factor variance. The factors whose factorloading is 0.50 or greater are considered significant factors. This limit is chosen because it hadbeen judged that factors with less than 50 per cent common variation with the rotated factorpattern are too weak to report.

In the present study, the principal factor analysis method with orthogonal varimax rotation isused to identify the significance of different variables of the opinion of policyholders on serviceprovided by LIC. The estimated results are presented in Table 1.1

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1.8.2 Result and Discussion of Opinion of the Policyholders

There are 14 statements given to the respondents. They have filled in their opinion in differentcolumns. Besides, the rotated factor loadings received by F1,F2 are presented in Table 1.1

Table 1.1 : Opinion of the policyholders on Service Provided by LIC of India

Sl.No. Variables Factor 1 Factor 2 Communalities

1. Branch is Easy to Approach 0.758 0.666

2. Amenities are Adequate 0.750 0.470

3. Parking Facilities are Available 0.722 0.385

4. Availability of Space 0.718 0.643

5. Customers Meet the Development Officers 0.675 0.579Periodically

6. Customers can Meet the Agents Periodically 0.585 0.395

7. Displays all Information on Notice Board 0.576 0.491 0.176

8. Clarification of Doubts with LIC Officials 0.797 0.577

9. Pamphlets for all the Policies - 0.761 0.576

10. Complaints are Considered without Delay 0.741 0.343

11. Touch Screen to know about the Position of Policies 0.653 0.556

12. Suggestion Box is Available 0.612 0.713

13. Branch Premises are Kept Clean 0.609 0.666

14. Branch following Time Norms 0.449 0.487 0.170

Source: Primary Data.

Table 1.1 represents the matrix of common factor co-efficients or factor loading. The numberfactor extracted was from LIC policyholders. The ratios which have the highest loading (>0.50) ineach fact are grouped, that is the ratios which are more closely related to particular group arebolded. In the following section, these results have been interpreted by carefully examining thesignificant loadings for ratios clustering on each factor.

1.8.3 Factor 1

In the first factor variable like, ‘branch is easy to approach’ (0.750), amenities are adequate(0.750) parking facilities are available (0.722), customers can meet the development officersperiodically (0.675) customers meet the agents periodically (0.58) and displays all the informationon the notice board (0.576) have been examined, LIC branches were easy to approach (0.758)have the highest significant positive loading. Hence factor one is characterized as “Availability ofServices in LIC Branch”.

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1.8.4 Factor 2

The second factor consists of the variables namely, clarification of doubts with LIC officials(0.797), pamphlets for all the policies (0.761), complaints are considered without delay (0.741),touch screen to know about the position of policies (0.653) suggestion box is available (0.612),branch premises are kept clean (0.609) and branch follows time norms (0.487). These are thevariables with the highest significance in factor two. These variables represent protection ofpolicyholders. Factor two is termed as “grievance redresal mechanism”.

1.9 Conclusion

Since most insurance companies are not adequately equipped to help their agents deal withcustomer centered problems CRM insurance enables insurance organizations to survive in a tougheconomic climate by using the data the insurance company has on the existing customers and thenuse it to increase the level of profitability. It manages to enhance customer relationships based oncustomer’s unique requirements. CRM enables customers themselves to do research on products,have answers to their questions etc. In addition to this policyholders can check their claim status,change their account information, submit complaints etc. Insurers find that CRM is assisting themin their marketing efforts as well through a comprehensive understanding of the client base. CRMaids the insurance companies by ensuring that campaigns are more affective.

References

1. www. insurancejournal.com

2. M.N. Mishra, Insurance-Principle and Practice, S. Chand and Company Ltd, New Delhi,1998, p.230.

3. www. insurancenetworking. com

4. Charles Dutt, Insurance Marketing – its Principle and Practice, - A Short Overview,Swiss Re-insurance Company, First Edition, p.28.

5. G.R. Desai, Life Insurance in India-its history and Dimensions of Growth, MacMillanIndian, New Delhi, 1973, pp.13-15.

6. Prasoon Kumar Roy, “Life Insurance Lightens the Hope of the People”, The InsuranceTimes, Vol.7, February 1987,pp.10 and 11.

7. National Council of Applied Economics Research “Attitude towards Life Insurance Cover”,Report on Household Income and its Disposition, New Delhi, 1979, pp.1-87.

8. M.N. Mishra, “Life Insurance Corporation of India-A Study of Working andPerformance, RBSA Publishers, Jaipur, 1991, pp.49-182.

9. LIC of India, “Spreading the Light” Yogakshema, Vol. 44, No.5, May 2000, p.24.

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“Efficiency of Stock Markets - Comparing theBehavior of Stock Indices of NSE and NYSE"

Dr. A. Patrick*, Mrs.R.Sushama**

Introduction:

Market efficiency has an influence on the investment strategy of an investor because ifmarket is efficient, selecting the winners will be a waste of time. In an efficient market there willnot be any under valued securities offering higher than deserved expected returns, at a given risk.On the other hand if markets are not efficient excess returns can be earned by correctly pickingthe winners. In this paper, a comparative analysis of stock indices of BSE and NYSE iscarried out to test the efficiency level in respective stock markets and the random walknature of the stock market is tested by using the run test and the autocorrelation functionACF (k).

For many years economists, statisticians and teachers of finance have been interested indeveloping and testing models of stock behavior. One important model that has evolved from thisresearch is the theory of random walks. This theory casts serious doubt on many methods fordescribing and predicting stock behavior-methods that have considerable popularity outside theacademic world. The Random Walk Hypothesis of stock prices is concerned with the question ofwhether one can predict the future prices based on the past prices. In simple terms this theorystates that price changes cannot be predicted from earlier changes in any meaningful manner.Successive price changes in individual securities are independent over time and price changesoccur without any significant trend or pattern. Thus past prices in no way can guide us to predictthe future behavior.

The Efficient Market hypothesis (EMH) assumes that stock prices adjust rapidly to thearrival of new information, and thus, current prices fully reflect all available information. Fama(1970)

Formalized the theory, organized the empirical evidence, and divided the EMH into threesub- Hypotheses. The weak-form EMH states that current stock prices fully reflect all historicalMarket information such as: prices, trading volumes, and any market oriented information. The

* Sr. Asst. Professor, Dept of Commerce, OU , Hyderabad-07,

** Research Scholar, Department of Business Management, OU and Sr.Asst. Professor, Badruka College PG Centre,Hyderabad-27,

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semi strong-form EMH asserts that prices fully reflect not only the historical information but alsoall public information including non-market information, such as earning and dividend announcements,economic and political news. Finally the strong-form EMH contends that stock prices reflects allinformation from historical, public, and private sources, so that no one investor can realize abnormalrate of return. Stock market efficiency is an important concept, both in terms of an understandingof the working of stock markets and in their performance and contribution of the development ofa country’s economy. If the stock market is efficient, the prices will represent the intrinsic valuesof the stocks and in turn, the scarce savings will be optimally allocated to productive investments ina way that benefits both individual investors and the country economy.

The weak form of EMH states that the current prices fully reflect the entire informationfound in the record of past prices and volumes. In an efficient market at a given instant of time theprices are assumed to reflect all available information. Hence one would expect the current priceof security to be good estimate of its intrinsic values. If the adjustment to new information isinstantaneous then successive price changes will be independent.

Brief Review of Literature:

Burton G. Malkiel in his article “ The efficient market hypothesis and its critics” has examinedthe attacks on the efficient market hypothesis and the relationship between predictability andefficiency. He concludes that the stock markets are more efficient and less predictable. He furthersuspects that the end result will not be an abandonment of the belief of many in the profession thatthe stock market is remarkably efficient in its utilization of information. Periods such as 1999 where“bubbles” seem to have existed, at least in certain sectors of the market, are fortunately the exceptionrather than the rule. More ever, whatever patterns or irrationalities in the pricing of individual stockthat have been discovered in a search of historical experience are unlikely to persist and will notprovide investors with a method to obtain extraordinary returns.

Sharma and Kennedy (1977) compared the behavior of stock indices of the Bombay, Londonand New York Stock Exchanges during 1963-73 using run test and spectral analysis. Both run testsand spectral analysis confirmed the random movement of stock indices for all the three stockexchanges. They concluded that stock on the BSE obeys a random walk and is equivalent in themarkets of advanced industrialized countries.

Kulkarni(1978) investigated the weekly RBI stock prices for Bombay, Calcutta, Delhi, Madrasand Ahmedabad stock exchanges and monthly indices of six different industries by using spectralmethod. He concluded that there is a repeated cycle of four weeks for weekly prices and seasonalityin monthly prices. This study has thus rejected the hypothesis that stock price changes were random.

Yalawar(1988) studied the month end closing prices of 122 stocks listed on the BombayStock Exchange during the period 1963-82. He used only the non-parametric tests Spearman’srank correlation test and run test. 21 out of 122 lag 1 correlation coefficients were significant at 5%significance.

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Iqbal has tested the semi-strong form of efficient market hypothesis by examining the stockprice responses to quarterly earnings announcements. The study period he had chosen was fromJune 2000 to June 2004. In his study he has used non-parametric tests and sign test. The purposeof the study is to ascertain and compare how stock prices respond to earnings on quarterly basisand also for the same quarter of different years. For all the three portfolios under market modelwith raw returns and market model with log returns stock price behavior around quarterly earningson an average produced abnormal returns in pre- and post- announcements periods. Further, theabnormal returns were found to persist up to 31 trading days subsequent to to the quarterly earningsannouncement day. This clearly indicates that the stock price adjustment to quarterly earningsannouncement is delayed and it persists throughout the event window. Hence, the results of thisstudy contradict semi-strong form of efficient market hypothesis.

Research Methodology

Sources of Data, Sampling technique and sample size:

Since the test of weak form of EMH , in general, has come from the random walk literature,so the present study is testing whether successive price changes are independent of each other ornot . The present study uses secondary data. The data is collected from Yahoo finance.com andweekly closing values of NIFTY and NYSE Composite are taken from Jan 2007 to October 2011.

Scope of the study:

The present study has used the data pertaining to leading stock indices NIFTY and NYSEComposite and analysis is been done using the data of four years (i.e. from Jan 2007 to October2011).

Tools of analysis:

In the present study Autocorrelation and Run test is used for testing the efficiency of thestock markets.

Autocorrelation ACF(k):

Autocorrelation is one of the statistical tools used for measuring the dependence of successiveterms in a given time series. Therefore it is used for measuring the dependence of successive shareprice changes. It is the basic tool used to test the weak form of EMH. The autocorrelation functionACF (k) for the time series Yt and the k-lagged series Yt-k is defined as:

ACF(K)= -é)(yt-k- é) _________________________

Where é is the overall mean of the series with n observations.

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The standard error of ACF(k) is given by:

1Se ACF(k) = _______

“n-k

Where n is sufficiently large (n e” 50), the approximate value of the standard error of ACF(k) isgiven by :

1 Se ACF(k) = _____

“(n)

To test whether ACF (k) is significantly different from zero, the following distribution of ‘t’ isused, i.e., t=ACF(k)/Se ACF(k)

For both random variable series and series with trends, ACF (k) will be very high and declineas the lag value (k) increases. At the same time the ACF (k) of the first difference series (pricechanges or returns) are statistically insignificant when the series is a random walk series. A randomwalk series drifts up and down over time. In some situation it may be difficult to judge whether atrend or drift is occurring. Hence to determine whether a series has significant trend or whether itis a random walk, the t- test is applied on the series of first differences.

Run Test

Run test is a non-parametric test. It depends only on the sign of the price change but not onthe magnitude of the price. It does not require the specification of the probability distribution. Itdepends only on the sign of the price change. It is essentially concerned with the direction ofchanges in the time series.

A Run test may be defined as a sequence of price changes of the same sign preceded andfollowed by price changes of different sign. In a given time series of stock prices there are threepossible types of price changes, namely positive, negative and no change. This gives three types ofruns. A positive (negative) run is a sequence of positive (negative) price changes preceded andsucceeded by either negative (positive) or zero price change. Similarly, a zero run is sequence ofzero price changes preceded and succeeded by either negative or positive price change.

Under the hypothesis that the successive price changes are independent and the sampleproportion of positive, negative and zero price changes are unbiased estimates of populationproportions, the expected number of runs of all the types is computed as follows(by Wallis,Robert(1956)),

M=

Where M=Expected number of runs

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ni = Number of price changes of each sign (i=1,2,3)

N = Total number of price changes = n1+n2+n3

The standard error of the expected number of runs of all signs may be obtained as:

Σ3i=1

n (Σ3i=1

n2i + N(N+1) - 2N Σ

3i=1

n2i – N

3

σm =

[ ______________________________________________

] N3(N-1)

Where N is sufficiently large, the sampling distribution of expected number of runs of all types isapproximately normally distributed with mean M and standard deviation Σm.

Limitations of the study:

1. The study is limited to stock indices NIFTY-50 and NYSE-Composite only.

2. Only weak form of efficiency is been tested in this study.

3. Data pertaining to years 2007 to 2011 is only included for the study.

Results and Discussion

Autocorrelations of weekly closing values of the two indices NIFTY-50 and NYSE-Compositeare summarized in table no.1:

Table 1: Autocorrelations of weekly changes in stock indices

Lag(k) NIFTY-50 NYSE Composite

N 246 246

1 0.034756 0.983253

2 0.034059 0.967205

3 0.033194 0.948643

4 0.032362 0.931451

5 0.031445 0.916863

6 0.030597 0.899488

7 0.029717 0.880963

8 0.028861 0.863416

9 0.027942 0.84332

10 0.026975 0.824961

11 0.026096 0.80721

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12 0.025283 0.790158

13 0.024478 0.775369

14 0.02358 0.757854

15 0.002268 0.739091

16 0.021548 0.716925

17 0.020404 0.693096

18 0.019218 0.66792

19 0.018075 0.644086

20 0.016976 0.619047

Standard error 0.0638 0.0638

Source: Calculated based on secondary data

For NIFTY-50, the autocorrelation coefficient for lag 1 is 0.034756, which is very muchsmaller than twice the standard error(=2*.0638). Thus the autocorrelation doesn’t differ significantlyfrom zero. From the table, we can see that out of 20 autocorrelation computed for NIFTY-50 noneof them differ significantly from zero.

For NYSE-Composite, the autocorrelation coefficient for lag 1 is .983253, which is verymuch larger than twice the standard error (=2*.0638). Thus the autocorrelation differ significantlyfrom zero. From the above table, we can see that all the 20 autocorrelation computed for NYSE-Composite differs significantly.

The t-values of the autocorrelations corresponding to the stock indices NIFTY-50 and NYSE-Composite are given in the following table:

Table 2: t-values of the autocorrelations corresponding to the stock indices


N 246 246

1 0.545 15.412

2 0.534 15.1599

3 0.52 14.869

4 0.507 14.599

5 0.493 14.37

6 0.479 14.09

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7 0.465 13.81

8 0.452 13.53

9 0.438 13.21

10 0.423 12.93

11 0.409 12.65

12 0.396 12.38

13 0.384 12.15

14 0.369 11.88

15 0.0355 11.58

16 0.337 11.24

17 0.319 10.86

18 0.301 10.47

19 0.283 10.09

20 0.266 9.7

Standard error 0.0638 0.0638

Source: Calculated based on secondary data.

The t-values of the autocorrelations corresponding to the stock index NIFTY-50 are lesserthan 1.96 (at 5% level of significance). Thus it can be concluded that stock index NIFTY-50 isunbiased random time series and the stock market (NSE) is weakly efficient in pricing its securities.

The t-values of the autocorrelations corresponding to the stock index NYSE-Composite aregreater than 1.96 (at 5% level of significance). Thus it can be concluded that the stock indexNYSE-Composite is biased random time series and the stock market (NYSE) is not weakly efficientin pricing its securities.

To verify this, run test is performed. With the help of run test the null hypothesis that the pricechanges are independent is been tested. The result of the run test is as follows:

Table 3: Run analysis of weekly closing values of stock indices

Index n n1 n2 n3 R óm Z

NIFTY-50 245 138 107 0 114 38.27 -1.34

NYSE-Composite 245 128 117 0 119 104.96 -1.99

Source: Calculated based on secondary data

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Where n= Total number of observations

N1=Ups ; n2= Downs; n3=zeros; N=n1+n2+n3; R= Total number of observed runs;

óm = Standard error; Z= Standardised Variable.

The results show that NIFTY-50 shows weak form of market efficiency whereas NYSE-Composite is unbiased random time series data. The stocks the index NIFTY-50 absorb the priceinformation effectively. But the results regarding NYSE-Composite is different, having Z value of-1.99 which is significant at 5% level.

Conclusion

The assumption that the stock prices are random is basis to the Efficient Market Hypothesisand Capital Asset Pricing Model. The study carried out in this paper has compared the weak formof efficiency of NSE and NYSE and has presented the evidence of efficient form of NSE andinefficient form of NYSE. From autocorrelation analysis and runs test it can be concluded that theseries of stock indices of NSE is unbiased random time series whereas stock indices of NYSE isbiased random time series. The autocorrelation analysis indicates that the behavior of share pricesconfirms the applicability of the random walk model in the Indian stock market whereas applicabilityof the model is not confirmed in NYSE. Thus there are undervalued securities in the NYSE and theinvestors can always make excess returns by correctly picking them.

References:

1. Anand Pandey, “Efficiency of Indian Stock Market,” SSRN id 474921, Oct 2003.

2. Burton G. Malkiel, “A Random Walk Down Wall Street,” book by W. W. Norton & Company.

3. Chandra, Prasanna “ Investment Analysis and Portfolio Management”, second edition, TataMcGrawhill publishing company limited, pp 302

4. Fama, Eugene F.,” The Behavior of Stock Market Prices”, Journal of Business, XXXVIII(January, 1965) p.p. 34-45

5. Graham Smith, “Random walks in Middle Eastern stock markets,” Applied Financial Economics,Apr 2007.

6. Iqbal, “Efficiency of Indian Stock Market: Study of Stock PRICE responses to EarningsAnnouncements of selected companies listed on BSE” , Finance India, Vol. XXIV No.4,December 2010, pp. 1383-1389.

7. www.yahoofinance.com

8. www.nscindia.com

9. www.nyse.com

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Human Resource Management practices inOrganized retailing - A Study of select retailers

Dr D. Maheswara Reddy* Suresh Chandra Ch**

1.0. Introduction

Human resource management (HRM) practices are most effective when matched withstrategic goals of organizations. HRM’s role in the company’s success is growing rapidly with thegrowth in many sectors in the present globalized era. HRM is a vital function in organizations andbecoming more important than ever. The HRM practices are crucial in designing the structure forman power, staffing, performance appraisal, compensation, and training and development. HRMpractices are a primary means for defining, communicating and rewarding desired role behavioursand desired role behaviours are a function of organizational characteristics. Innovative HRMpractices can play a crucial role in changing the attitude of the companies and its employees inorder to facilitate the entry and growth in the markets. The HRM practices in service sectorespecially in the area of retailing have found significant importance in the present scenario. Theretailing is one of the service sectors where the need of qualitative human resources is highlyexpected.

Retailing is an important element of business around the globe. Retailing consists of allactivities that result in the offering for sale of merchandise to consumers for their own use. Retailingis the final step in bringing goods to consumer. They sell both goods and services. Retailing is theprocess of “Sale of goods or merchandise, from a fixed location such as a departmental store orkiosk, in small or individual lots for direct consumption by the purchaser. Retailing may includeservices, such as product delivery. Buyers may be individuals’ or businesses; a retailer buys goodsor products in large quantities from manufacturers or importers, either directly or through a wholesaler,and then sells in smaller quantities or lots to the end –users or consumers. Retailers are the endlinks of the supply chain as an important part of manufacturing/marketer overall distribution strategy.

1.1 Overview of Indian Retail Industry

Retailing is one of the pillars of economy because of its 13% contribution to GDP. Thoughthe Indian retail sector is dominated by unorganized sector with 90% share, it is providing immenseopportunities for large scale retailers to set-up their operations. The organized retailing sector issteadily increasing with the entry and operations of departmental stores, hyper markets, supermarkets

*Assistant Professor, I T M Business School, email: [email protected] mobile: 99636601530, Warangal** UGC JRF (PhD) Research scholar, Kakatiya University, Warangal

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and specialty stores which are replacing the traditional formats dramatically altering the retailinglandscape in India.

India is the third most attractive retail market for global retailers among the 30 largest emergingmarkets, according to US consulting group AT Kearney’s report published in June, 2010. The totalretail sales in India will grow from US $ 395.96 billion in 2011 to US $ 786.12 billion by 2015,according to the BMI India Retail report fro the third quarter of 2011. Robust economic growth,high disposable income with the expansion in middle and upper class consumer because, the reportidentifies potential in India’s tier-II and tier-III cities as well. The greater availability of personalcredit and a growing vehicle population providing improved mobility also contribute to a trendtowards annual retail sales growth of 12.2 percent. An increasing number of people in India areturning to the services sector for employment due to the relative low compensation offered by thetraditional agriculture and manufacturing sectors. The organized retail market is growing at 35percent annually while growth of unorganized retail sector is pegged at 6 percent.

Though the retailing sector is growing rapidly, some of the constrains are restricting its growth.Apart from the regulations and approval for Foreign Direct Investments (FDIs), the sector isstrongly lacking the effective human resource practices. The problems of lack of trained workforce, low skill level for retailing management, lack of development programmes to the existinghuman resources and problems in retaining qualitative manpower are some of the obstacles creatinghuge challenges to the Indian retail sector. At present, to overcome some of the challenges facedby retail, the companies are investing heavily in training and recruitment of qualitative work force.

1.2 Statement of the problem

In the present competitive scenario, the role of retailing is increasing rapidly with the entry ofglobal players. Many Indian companies strongly keeping their aim on entering in retail industry.With increasing globalization, firms are entering a dynamic world of international business that ismarked by liberalization of economic policies in a large number of emerging economies like India.To face the challenge of increasing competition that has resulted from liberalization, Indianorganizations have initiated adoption of innovative human resource management practices bothcritically and constructively to foster creativity and innovation among employees. The hugeopportunities in organized retailing encouraging the companies to enter in retail industry. The last2 decades has witnessed the tremendous potential for organized retailing. The growing needs ofretail industry can be matched up with the aggressive human resource practices. The present retailorganizations which are performing organized retailing are facing huge challenges in procuring andretaining and maintaining qualitative human resources. Hence, an attempt was made to analyzethe various human resource practices followed in select retailers in organized retailing.

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1.3 Research Objectives

The major objective of this study is to study the human resource management practicespursued in the organized retailing. The study covers the retailer wise employee satisfaction on thevarious HRM practices employed in the retail outlets. Further, the study is also aimed at studyingthe various problems and challenges ahead for HR managers in the implementation of HRM practicesin selected organized retail outlets.

1.4 Research Methodology

The present research paper is an empirical one. The survey for the present research isconducted through primary data with the help of a questionnaire surveyed to employees of selectorganized retailers. The sample taken for the study consisted of 100 which include daily wageworkers and employees from the select retail outlets situated in Warangal District.

1.5 Analysis and Discussion

The research survey is conducted in order to analyze the various Human ResourceManagement (HRM) practices adopted in the select organized retailers. For the purpose of studyingthe HR practices implemented and to evaluate, the following organized retailers are selected.

a) Organized retailers selected for the study:

S.No. Name of the CompanyName Places District Sample SizeOrganized Retailer

1. Reliance Fresh, Reliance Industries Excise Colony, Warangal 40

Limited Naim Nagar,

Subedari

2. Spencers, Spencer’s Retail Adalath Circle Warangal 25

Limited

3. More, Aditya Birla Group Circuit House Warangal 10

Road

4. Reliance Super , Reliance Industries Alankar Circle Warangal 25

Limited

Total 100

Source: Field Survey

Overall, 4 organized retailing units are selected for the study. Reliance Fresh outlets arebeing more in number; hence, 3 retailing units are selected for the study. And the 3 other retailingunits were selected for the study include Spencers, More, and Reliance Super. The samples

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selected from the retail outlets include the sales persons, supporting staff, teller employees and theexecutive and managerial level employees.

b) Emphasis on employees share on different aspects:

Name Share of Specialty Typical Extra Incentive Hours for % inof the part Tellers New Hire Selection based pay orientation Employeeretailer timers Test period involvement

Spencer’s NA 18% Graduate No Yes 12 61-80%

Reliance 20% 10% Graduate No Yes 10 21-40%

Fresh

More 12% 16% Under No Yes 10 21-40%

Graduate &

Graduate

Reliance 22% 26% Graduate Yes Yes 18 41-60%

Super & Post

Graduate


Note:

Share of part-timers refers to the percentage of employees work fewer than 5 hours a week.

Specialty tellers refers to the percentage of tellers that perform only a subset of teller tasksduring a typical shift

Typical new hire gives the highest education level of the typical new employee

Extra selection test refers to the use of additional selection procedures beyond backgroundreviews, skills tests and personal interviews.

Incentive-based variable pay refers to the presence of any incentive pay program other thanstandard merit pay.

Orientation period refers to the hours a new employee spends in training before beginningwork.

% of Employee Involvement refers to the percentage of employees involved in group problem-solving, quality circles, or other similar activity.

From the above table, it is evident that Reliance Super is on top in terms of share of parttimers, i.e., the percentage of employees work fewer than 5 hours a week. Again Reliance Superis leading in terms of specialty tellers , i.e., the percentage of tellers that perform only a subset ofteller tasks during a typical shift. And “More” retail store showed that the education level for its

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employees begin with undergradutation which is least educational qualification compared to theemployees of other retail outlets, as the employees’ highest education level starting from Graduationand where as the Reliance Super is achieved new hire with Graduates and Post Graduates. Andalso Reliance Super is engaging the employees through Extra Selection Test. Where as other retailoutlets are not concentrating on extra selection test while recruiting the employees. And from thesurvey, it was found that all the retail outlets are adopting incentive based pay to its employees.When it comes to Orientation period, Reliance Super is making the employees to get accustomed tothe work activities. Finally, the employees’ involvement statistics clearly showing that the employeesof Spencers have more commitment towards problem solving and other activities.

c) Observations on HRM practices in Selected Organized Retailers:

S.No. HRM Practices Name of Organized Retailer

Reliance Spencer’s More RelianceFresh Super

1 % employees whose skills & abilities are 65.12% 71.26% 58.20% 62.34%

fully utilized

2 % employees whose jobs help them acquire 62.0% 65.19% 65.06% 82.16%

skills needed for other jobs in the company

3 % employees who have more than one position 42% 36% 42% 58%

available to them for promotion

4 % employees whose jobs are highly enriched 56% 56% 50% 58%

5 % employees whose performance appraisals 52% 66% 48% 64%

are formalized

6 %employees whose performance appraisal 72% 74% 68% 78%

results are used to determine compensation

7 % employees whose performance appraisals 72% 70% 68% 76%

focus on how job is done, not how well

8 % employees who have a say in the criteria 44% 38% 52% 64%

used in their performance appraisal

9 % employees whose performance appraisals are 56% 64% 52% 62%

based on objective quantifiable results

10. % employees whose performance appraisals are 56% 64% 52% 62%

used to identify their training needs


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From the survey on the opinions of the employees regarding different HR practices employedin the retail organizations, the following observations were made.

71.26% of the Spencers’ employees favoured to the factor “percentage of employees whoseskills & abilities are fully utilized”. For the second factor, 82.16% of the Reliance Super employeesfavoured to the factor “percentage of employees whose jobs help them acquire skills needed forother jobs in the company”. For the third factor, 58% of the employees of Reliance Super favouredto the factor “percentage of employees who have more than one position available to them forpromotion”. For the fourth factor, 58% of the employees of Reliance Super favoured to the factor“percentage of employees whose jobs are highly enriched”. For the fifth factor, 66% of theemployees of Spencers favoured to the factor “percentage employees whose performance appraisalsare formalized”. For the sixth factor, 78% of the employees of Reliance Fresh favoured to thefactor “ percentage of employees whose performance appraisal results are used to determinecompensation”.

For the seventh factor, 76% of the employees of Reliance Fresh favoured to the factor“percentage of employees whose performance appraisals focus on how job is done, not how well”.For the eighth factor, 64% of the employees of Reliance Fresh have favoured to the factor“percentage of employees who have a say in the criteria used in their performance appraisal”. Forthe ninth factor, 64% of the employees of the Spencers favoured to the factor “percentage ofemployees whose performance appraisals are based on objective quantifiable results”. For thetenth factor, “64 % of the employees of Spencers favoured to the factor “percentage of employeeswhose performance appraisals are used to identify their training needs”.

d) Table showing the opinion of the employees regarding the performance appraisal that hascome from:

S.No. Evaluator Reliance Fresh Spencers More Reliance Super

1. Supervisor 79.19% 72.89% 73.56% 72.21%

2. Supervisor’s boss 10.92% 13.69% 11.98% 8.12%

3. Peers 2.01% 2.56% 2.56% 1.96%

4. Subordinates 1.92% 1.59% 2.5% 3.49%

5. Subordinates 2.99% 4.92% 6.31% 5.62%

6. Clients 2.97% 4.35% 3.09% 8.6%

Total 100% 100% 100% 100%


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Note: Values indicate the means percentage of employees who were covered by the practice.Respondents divided 100 points among the categories listed.

From the above table, it is evident that the role of supervisor is vital for the organized retailersin implementation of performance appraisal. 79% of the employees of Reliance Fresh favouredthat “Supervisor is the initiator for the Performance appraisal. 72.89% of Spencers employees,73.56% of the More employees and 72.21% of the Reliance Super employees favoured thatsupervisor is the initiator for the Performance appraisal system in their respective retail organizations.Apart from that the next decider plays key role in the performance appraisal are Supervisor’s boss.The role of peers, subordinates, clients are less in making decisions about the performance appraisalsystem in the selective retail organizations selected for the study.

e) Table showing employees opinion on the motivational aspects encouraged their performance:

S.No. Name of factor Name of the Organized retailer

Reliance Spencers More Reliance Fresh Super

1 Appraisal process motivated for better 12.50% 15.00% 8.5% 10.00%performance

2 Positive work environment encouraged for 32.65% 20.5% 10.50% 25.00%better performance

3 Good team commitment encouraged for 18.50% 25.00% 15.00% 10.45%better performance

4 Healthy environment in the work flow 12.50% 10.50% 25.00% 10.25%encouraged the performance

5 Incentive encouraged for better performance 13% 8.50% 25.00% 13.80%

6 Qualitative training and better scope for 10.85% 20.5% 16.00% 30.50%promotion encouraged for performance

Total 100% 100% 100% 100%


From the above table, it is clear that, the employees of the Reliance Fresh favouring more tothe factor “positive work environment” which is encouraging for better performance. The employeesof Spencers have opinioned that “good team commitment encouraged for better performance. Theemployees of More are favouring to the fact “Incentive schemes encouraged for betterperformance”. The employees of Reliance Super have favoured more to the fact “qualitativetraining and better scope for promotion encouraged for better performance”.

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e) Table showing the opinions of the employees regarding the satisfaction over the facilities providedin the retail outlets:

S.No. Name of factor Name of the Organized retailer

Reliance Spencers More RelianceFresh Super

1 Employee Rest rooms 12.50% 15.00% 25.5% 35.00%

2. Sanitation & Water facilities 70% 55% 75% 80%

3. Satisfaction over the transportation facilities 50% 80% 45% 70%

4. Recreational area with landscaped sit out 0% 0% 0% 0%

5. On-site First-aid Clinic 45% 45% 30% 50%

6. Refreshment stalls and canteen for healthy food NA NA NA NA

7. Staff accommodation NA NA NA NA


Note: NA refers to Not Applicable. Figures indicate the percentage of employees showed theirsatisfaction over the facilities offered to them by the retail organizations.

From the above table, it is observed that , the employees of Reliance Super have the satisfactionof 35% over the employee rest room facilities. The employees of Reliance super again topped as80% of the employees of Reliance Super have shown their satisfaction over the sanitation & waterfacilities. For the factor ‘satisfaction over the transportation facilities’, 80% of the Spencersemployees showed their intent of satisfaction. When it comes to the facilities about recreationalarea with landscaped sit out, no employee of any of the selected retail out lets showed theirsatisfaction. When it comes to On-site First-aid Clinic, 50% of the employees of Reliance Superhave showed their satisfaction. And regarding the staff accommodation, no retail outlets selectedfor the survey are providing staff accommodation.

g) Problems & challenges Ahead:

Human resources people are the backbone of any company and the success of retail businessdepends a lot upon the kind of human resource strategies it is following and how people are managed.Because of increasing competition between organized retailers, the retail industry is facing thechallenges and hurdles from different areas. From the survey on select organized retailers, thefollowing observations were made.

1. High Attrition: Employee retention and motivation of staff has become the major concern forHR department in the organized retailing sector. Because of the strenuous schedules and tasksinvolved in the retail industry, it becomes imperative for HR staff to take good care of theiremployees who form the building blocks of their retail chain. The undercurrents among theemployees regarding company policies are many and they must be felt from time to time tosustain the quality crowd and reduce the attrition rate.

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From the report of Retailer, it is found that the attrition rates are comparatively high when itcomes to the retail industry in India. The attrition rate in the Indian retail industry is 30-35percent. The main reasons found to be the typical nature of job where a particular employee ofan organized retail company need to work on his feet the whole day and the job is reactionintensive and the business is mainly transactional.

2. Training for competition: The need for efficient trained sales team is of great importance inthe organized retailing at present. For every retail organization, the secret behind the successof their business is to keep the list of their loyal consumers interact. The need for a welldesigned HR practices are greatly needed for proper training to the newly recruited people tothe retail organization. Providing training to the sales staff plays a significant role in everybusiness operation. Nowadays, the organized retailers are looking at a sales training companyto help the sales staff gain more proficiency and expertise in their respective field.

3. Observations found in Training sessions of select organized retailers

From the field based survey, it was found that the organized retailers at Warangal District,apart from using the services of outsourcing firms to train its sales people, they are also usingsome of the innovative new training techniques to the staff. The techniques which are observedduring the survey are:

a) Stressing upon benefits of advertising: The HR managers and trainers are emphasizingupon making the sales people to think and act innovatively in designing the retail out let andas well as attracting the customers through innovative promotional strategies. The trainersare focusing on making the staff to effectively use advertising as a tool to enhance sales,promote growth, and attract new consumers.

b) Counting the customers: In this, the retail firms and the trainers are making the staff ofthe retail organization to increase the customer relationship management. Through effectivetraining, the trainers are working on highlighting the components of marketing strategieswhich the sales people should perform activities of promotion, product development,relationship management, distribution and pricing. The trainers are making the retail staffwhich include sales staff and supporting staff to identify the firm’s marketing goals, and areexplaining about how the goals can be achieved.

3. Online Training: The trainers of HR department are showing the visuals of well designedand successfully running retail organization’s outlets to the employees in order to make them torealize the importance of the design of retail outlet. Apart from that, from the survey it was alsorealized that the trainers are focusing on online training which include web based support toenhance the abilities of the staff of the retail outlets.

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4. High Labour costs and Complex nature of labour laws: Because of the increasingcompetition and the complex nature of the work, the retail outlets are facing the problems oflabour costs. Apart from that, various labour laws are giving restrictions to the HR departmentto achieve desired objectives of the retail organizations. From the survey, it was found that theHR department is facing with the problems like lengthy leisure hours and frequent absenteeismof the employees to the duties. Even, it was found that the existing labour laws in India forbidemployment of staff on a contractual basis that makes it difficult to manage employee schedule.Especially, when retail organizations are performing 365- day operation, the problems inencouraging and motivating the employees to perform well is a tough challenge for the HRdepartment.

1.6 Findings & Suggestions

The human resource management practices are vital for the development of any business orsector. The HRM practices have inevitable dependence on the organized retailers. From the studyit was found that, right from new hire to orientation period, there are many differences in theimplementation of HR practices in the selected organized retailers. The satisfaction levels ofvarious performance appraisal measures adopted in the selected retail outlets showed that theemployees are not only favoured to the incentive plan but also the healthy environment and closerelations between the peers are playing vital role for their performance. Further, the supervisor hasthe key role in taking initiative in the implementation of performance appraisal at the select organizedretail outlets. The employee facilities in the select organized retail outlets found to be not satisfactoryto the employees of the retail outlets. The HR department is facing the challenges which includehigh attrition rate, absenteeism, and implementation of innovative practices in the retail outlets.Hence, from the study, it was found that the HR management practices in the select retail outletsare still in the initial stages of development. The employee facilities and proper performanceappraisal measures will always encourage the employees to achieve the best. Hence, the retailoutlets should decide and implement proper HR practices in order to retain and develop the workforce who are the assets for the development of organizations. The government should also needto bring revision of existing labour laws and should provide flexibility in working hours and shouldencourage with its laws that can bring conducive environment.

References

1. A CII – A.T. Kearney report, “Retail in India: Getting organized to drive growth”.

2. Ashok Som, “Bracing for MNC Competion through innovative HRM Practices: the Way aheadfor Indian Firms”, Thunderbird International Business Review, Wiley InterScience, Vol.48(2)207-237, March-April,2006., Pg.No.207-211

3. Barry Berman & Joel R. Evans(2007), “Retail Management – A strategic approach”, 10th

Edition, Eastern Economy Edition, New Delhi.

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4. Derek C.Jones, Panu Kalmi & Antti Kauhanen, “How Deos Employe Involvement Stack Up?The effects of Human Resource Management Policies on Performance in a Retail Firm, WorkingPapers , Cornell University.

5. James R. Ogden & Denise T. Ogden(2008), “Integrated Retail Management”, Biztantra, AnImprint of Dreamtech Press, Reprint Edition 2008, New Delhi.

6. Michael Levy & Weitz(2007), “Retailing Management”, Tata McGraw-Hill Publishing CompanyLimited, New Delhi.

7. Susan E.Jackson & Randall S. Schuler, “HRM Practices in Service-based organizations: Arole theory perspective”, Advances in Services Marketing and Management, Vol.1, Pages:123-157.

8. U.C. Mathur(2010), “ Retail Management - Text and cases”, I.K. International PublishingHouse Pvt. Ltd., New Delhi.

9. Wharton, “How will competition change Human Resource Management in Retail banking? AStrategic Perspective”, Workiing Paper Series, Wharton School, University of Pennsylvania,Pg. No.1-29.

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Performance Evaluation of Open endedSchemes of Mutual Funds

Dr . Vikas Kumar*

Introduction

Household savings play an important role in domestic capital formation. Only a small part ofthe household savings in India is channelized to the capital market. Attracting more householdsavings to the capital market requires efficient intermediation. Mutual funds have emerged as oneof the important class of financial intermediaries which cater to the needs of retail investors. Mutualfunds have become an important vehicle for mobilization of savings particularly from the householdsector.

Mutual funds are one of the most favoured investment routes for the small and mediuminvestors across the world. Ideally, Mutual funds provide opportunities for small investors to participatein the capital market without assuming a very high degree of risk. An important principle of investmentin capital market is that do not put all the eggs in one basket i.e. diversification. A small investor isnot able to have a diversified portfolio mainly due to paucity of resources. However, a mutual fundpools together the savings of such small investors and invests the same in the capital market andpasses the benefits to the investors. Thus, investors can indirectly participate in the capital marketby subscribing to the units of mutual funds. Mutual funds employ professional fund managers tomanage the investment activities. Therefore, investors also get benefits of professional expertise ofthese managers.

Objectives of the Study

1. To examine the funds sensitivity to the market fluctuation in the terms of Beta.

2. To appraise the performance of mutual funds with regard to risk-return adjustment, the modelsuggested by Sharp, Treynore and Jensen.

Significance of the Study

Evaluating historical performance of mutual funds is important both for investors as well asportfolio managers. It enables an investor to access as to how much return has been generated bythe portfolio manager and what risk level has been assumed in generating such returns. Further, aninvestor can also appraise the comparative performance of different fund managers. Similarly fundmanagers would also be able to know their performance over time and also vis-a-vis that of other

* Guest Faculty,Department of Commerce, Sri Harischandra Post Graduate College, Varanasi

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competitors in the industry. The evaluation also provides a mechanism for identifying strengths andweaknesses of fund managers in the investment process, which helps them to take correctiveactions.

Benchmark Index

For this study, broad-100 shared base BSE National Index has been used as a proxy formarket index this is because BSE National index is comparatively for broad based than BSESensex that is constituted of 30 shares only. Hence it would cover the majority percentage ofdifferent scheme portfolios and therefore is expected to provide better performance benchmark.

Risk Free Rate

Risk free rate of return refers to that minimum return on investment that has no risk of losingthe investment over which it is earned. For the present study, it has been marked as 6% (.06) perannum or 0.005 per month.

Period of Study

The growth oriented schemes, which have been floated by the selected funds during theperiod Jan. 2000 to Dec. 2009, have been considered for the purpose of the study. Monthly NetAsset Value (NAV) as declared by the relevant mutual funds from the Jan. 1st 2000 of a particularscheme to 31st Dec. 2009 has been used for the purpose.

Data

This study examines 20 open-ended schemes being launched by selected five mutual fundsnamely LIC, HDFC, ICICI, Reliance and Birla Sun Life. These schemes have been selected onthe basis of regular data availability during the period of Jan. 2000 to Dec. 2009. Monthly NetAsset Value (NAV) data has been used and the period of the data considered is from the date 1st

Jan. 2000 of the scheme or from the date of availability till Dec. 31, 2009.

Limitations of the Study

For the purpose of performance evaluation, those schemes have been selected which are inoperation since last 10 years. These schemes relate to five mutual funds namely LIC, HDFC,ICICI, Reliance and Birla Sun Life. Only open ended schemes have been considered for thispurpose. Performance evaluation of all the schemes operated by selected mutual funds was notpossible because of non availability of sufficient data. Table 5.1 depicts the list of sample schemeselected for study, these schemes relate to five mutual funds namely LIC Mutual Fund, HDFCMutual Fund, ICICI Mutual Fund, Reliance Mutual Fund and Birla Sun Life Mutual Fund. Only

29


open ended schemes have been considered for this purpose. Out of 20 schemes 13 schemes areequity schemes 4 are debt schemes and remaining 3 are balanced schemes.

Table 5.1 List of Mutual Funds Schemes Studied

Name of the Scheme Date of Launch

Equity Scheme

Birla Sun Life Buy India Fund 15/01/2000

Birla Sun Life Equity Fund Growth 27/08/1998

Birla Sun Life India Opportunities Fund 27/12/1999

Birla Sun Life MNC Fund 22/04/1994

HDFC Top 200 Growth 11/09/1996

ICICI Prudential FMCG Growth 31/03/1999

ICICI Prudential Growth Plan 09/07/1998

ICICI Prudential Tax Plan Growth 19/08/1999

LIC Equity Fund Growth 15/02/1999

LIC Growth Fund Growth 03/02/1999

LIC Tax Plan Growth 03/02/1999

Reliance Growth Fund 08/10/1995

Reliance Vision Growth 08/10/1995

Debt Scheme

Birla Sun Life Income Fund 03/03/1997

Birla Sun Life Income Plus Growth 21/10/1995

Birla Sun Life Monthly Income Plus 14/07/1999

ICICI Prudential Income Fund Growth 09/07/1998

Balanced Schemes

Birla Sun Life 95 Growth 10/02/1995

Birla Sun Life Freedom Fund Growth 22/10/1999

ICICI Prudential Balance Growth 03/11/1999

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Different scheme launch in different dates therefore, for the purpose performance evaluationthe period covers Jan, 2000 to Dec. 2009. The parameters like average return, standard deviation,coefficient of determination, Beta, Sharpe ratio, Treynor ratio, Jenson’s measures, etc. has beencalculated separately for all the schemes.

Table 5.2 Average Return Earned by the Schemes

Name of the Scheme Return

Equity Scheme

Birla Sun Life Buy India Fund 0.014665

Birla Sun Life Equity Fund Growth 0.019982

Birla Sun Life India Opportunities Fund 0.010991

Birla Sun Life MNC Fund 0.016069

HDFC Top 200 Growth 0.019883

ICICI Prudential FMCG Growth 0.014816

ICICI Prudential Growth Plan 0.015230

ICICI Prudential Tax Plan Growth 0.020373

LIC Equity Fund Growth 0.011283

LIC Growth Fund Growth 0.011397

LIC Tax Plan Growth 0.008421

Reliance Growth Fund 0.024002

Reliance Vision Growth 0.025032

Debt Scheme

Birla Sun Life Income Fund 0.007495

Birla Sun Life Income Plus Growth 0.007665

Birla Sun Life Monthly Income Plus 0.008938

ICICI Prudential Income Fund Growth 0.007817

Balanced Schemes

Birla Sun Life 95 Growth 0.015434

Birla Sun Life Freedom Fund Growth 0.009223

ICICI Prudential Balance Growth 0.011527

Table 5.2 shows the average return earned by the various schemes. For calculation of averagereturn earned by the schemes Growth in the value for each month over the previous month hasbeen divided by the value of the previous month. Then the average of the full series has been taken.In equity schemes Reliance vision growth 0.025032, Reliance growth fund 0.024002, ICICI prudentialtax plan growth 0.20373, Birla Sun Life equity fund Growth 0.019982 and HDFC top 200 Growth0.019883 are the higher return earners as against BSE 100 return (0.017370), LIC tax plan growth,

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with 0.008421 has shown the worst performance as against BSE 100 return of 0.017370. It couldbe seen here that 8 out of 13 the equity schemes has underperform the market. In debt scheme,Birla Sun Life Income Fund 0.007495, Birla Sun Life Income Plus Growth 0.007665, Birla Sun LifeMonthly Income Plus 0.008938, ICICI Prudential Income Fund Growth 0.007817. Debts schemesare registered underperform against the BSE 100 index. In Balanced Schemes, Birla Sun Life 95growth 0.0154, Birla Sun Life freedom fund growth 0.092 and ICICI Prudential balanced growth0.0115 has underperformed the BSE 100 return 0.017370. Out of the total of 20 schemes studied,5 schemes showed average return higher than that of BSE 100 average return out of which 5 areequity schemes.

Table 5.3 shows the standard deviation of selected schemes. it is the most common expressionto measure risk of the fund return. Higher the value of standard deviation of the fund returns,greater will be the total risk carried by the fund. It is observed that the maximum deviation of fundsreturn is shown by ICICI Prudential tax Plan growth 0.101619 followed by Reliance Vision Growth0.101581, Birla Sun Life India Opportunity Fund 0.101142, Birla Sun Life Equity Fund Growth0.094323, Birla Sun Life MNC Fund 0.092142. Birla Sun Life Monthly Income plus was least riskyscheme with lowest standard deviation 0.017068. Standard Deviation of benchmark BSE 100 indexis 0.120745.

Table 5.3 : Standard Deviation

Name of the Scheme Standard Deviation

Equity Scheme














32


Debt Scheme





Balanced Schemes




All the schemes selected for study less standard deviation then BSE 100 Index. It means allthe schemes are less risky than benchmark index, but equity schemes are more risky then balancescheme and Debt schemes because in the case of equity schemes shows higher standard deviationin comparison to balance schemes and debt schemes.

Categorizations of Schemes Table 5.3 (a) presents the risk return grid of Mutual Funds.

After classification of the sample schemes in to risk return category 15 schemes falls incategory 1st i.e. Low Return Low Risk. Out of 15 schemes 8 are equity schemes, 4 are Debtschemes and remaining 3 are balanced schemes.

Further five schemes fall in 2nd category i.e. High return and low risk. These five schemesare Reliance growth fund, Reliance Vision Growth, ICICI Prudential tax plan growth, Birla SunLife Equity Fund Growth and HDFC Top 200 Growth.

No schemes fall in 3rd category i.e. High Return and High Risk and 4th category i.e. LowReturn and High Risk because all the schemes have lower standard deviation then benchmarkBSE 100 index.

Table 5.3 (a) : Risk Return Grid of Mutual Funds Schemes

Category 1 Category 2

LIC Tax Plan Growth Reliance Growth fund

Birla Sun Life India Opportunities Fund Reliance Vision Growth

LIC Equity Fund Growth ICICI Prudential tax plan growth

LIC Growth Fund Growth Birla Sun Life Equity Fund Growth

Birla Sun Life Buy India Fund HDFC Top 200 Growth

ICICI Prudential FMCG Growth

ICICI Prudential Growth Plan

Birla Sun Life MNC Fund

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Birla Sun Life Income Fund

Birla Sun Life Income Plus Growth

ICICI Prudential Income Fund Growth

Birla Sun Life Freedom Fund Growth

ICICI Prudential Balance Growth

Birla Sun Life 95 Growth

Birla Sun Life Monthly income Plus

Category 3 Category 4

No sample scheme No sample scheme

Table 5.4 : Co-efficient of Determination (R2)

Name of the Scheme R2

Equity Scheme














Debt Scheme





Balanced Schemes




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Table 5.4 shows that Coefficient of determination (R2), the coefficient measure to extent towhich market index has been able to explain the variation in mutual fund. The table 5.4 remains thatin the equity schemes the maximum and minimum values of (R2) where found in case of ICICIprudential growth plan (0.5184) and Birla Sun Life MNC fund (0.2571) respectively. The low valueof (R2) indicates less diversification of the portfolio. High Value of (R2) in case of ICICI prudentialgrowth plan shows high diversification of the portfolio that can be easily contains the marketvariability. Thus it could be seem that the schemes like LIC equity fund growth (0.5092), Birla SunLife Equity fund growth (0.4907), HDFC top 200 growth (0.4765), ICICI prudential tax plan growth(0.4488) and Reliance growth fund (0.4365) have reasonably exploited the diversification strategyfor performing their portfolios. However for other schemes the lower value of (R2) indicates thatthe market does not explain substantial part of variation in the return of a particular scheme. Thissuggests that the portfolio of the scheme is inadequately diversified in debt scheme.

In debt scheme generally a low (R2) value for majority of the scheme that portfolio of isscheme is generally confined to investment in shares of particular type of companies only. For the,in Balanced Schemes a high (R2) value of the schemes show that the portfolio of these schemes isadequately diversified.

Table 5.5 presents the systematic risk of 20 schemes. Considered for the purpose of thisstudy in all the scheme have beta less than 1 (i.e. market beta) implying thereby that these schemestended to hold portfolios that were less risky than the market portfolio. It was observed that highestbeta in the case of ICICI prudential tax plan growth 0.589844 followed by Birla Sun Life EquityFund Growth 0.57253, Birla Sun Life India Opportunity Fund 0.54895, LIC Equity Fund Growth0.53301, Reliance Growth Fund 0.52993, and lowest beta in the case of Birla Sun Life income plusgrowth 0.02204.

Table 5.5

Name of the Scheme Beta (βββββ)

Equity Scheme











35





Debt Scheme





Balanced Schemes




Table 5.6 : Sharpe of the Schemes

Name of the Scheme Sharpe

Equity Scheme














36


Debt Scheme





Balanced Schemes




Table 5.6 depicts value of Sharpe’s reward to variability ratio. It is an excess return earnedover risk free return per unit of risk involved, i.e. per unit of standard deviation. Positive value ofthe index shows good performance it could be seen that 15 out of 20 schemes have recorded betterSharpe index than the BSE National Index. This indicates 75 percent schemes have outperformedthe BSE national index. Five schemes namely LIC Growth Fund Growth 0.070432, LIC EquityFund Growth 0.069671, Birla Sun Life Freedom Fund Growth 0.069438, Birla Sun Life IndiaOpportunity Fund 0.059232 and LIC Tax Plan Growth 0.037636 are less than BSE 100 nationalindex Sharpe ratio i.e. 0.10245, the top five performers are Birla Sun Life Monthly Income Plus,Reliance growth fund, Reliance Vision Growth, HDFC Top 200 growth, Birla Sun Life Equity FundGrowth. This implies that the funds decision for diversified portfolio in a falling market has provedsuccessful in earning higher excess returns per unit of risk as compared to the market. The Sharpeindex is important from small investor point of view who seek diversification through mutual funds,i.e. mutual funds are supposed to protect small investors against vagaries of stock markets and thefund managers of these schemes has done well to protect them.

Table 5.7 shows Treynor of the scheme it is the excess return over risk free return per unitof systematic risk i.e. beta. Here, too, all the schemes recorded positive value indicating there bythat the schemes provided adequate returns as against the level of risk involved in the investment.Analysis of table 5.7 reveals that all the mutual funds schemes have positive values. In terms ofTreynors ratio, the top five performers are ICICI prudential Income Fund Growth 0.23666, ICICIprudential balance Growth 0.177599, Birla Sun Life Income Fund 0.142715, Birla Sun Life IncomePlus Growth 0.120927, Birla Sun Life Monthly Income Plus 0.043573 A higher Treynor Index ascompared to market indicates that investor who invested in mutual fund to form well diversifiedportfolio did receive adequate return per unit of systematic risk undertaken.

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Table 5.7 : Treynor of the Schemes

Name of the Scheme Treynor

Equity Scheme














Debt Scheme





Balanced Schemes




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Table 5.8 : Jensen’s Measure

Name of the Scheme Jensen

Equity Scheme














Debt Scheme





Balanced Schemes




Table 5.8 shows the Jenson’s Measures. It is the regression of excess return of the schemewith excess return of the market, acting as dependent and independent variables respectively.Higher positive value of alpha posted by the scheme indicates its better performance. The analysisof the table reveals that all the schemes have positive Jenson’s Measures. Highest Value of Jenson’sMeasure are Reliance Vision Growth 0.02244 followed by Reliance Growth Fund 0.021352, HDFCTop 200 Growth 0.017428, ICICI Prudential tax Plan 0.017424, Birla Sun Life Equity Fund Growth0.17119. Lowest Jenson’s measure found again in the case of LIC tax Plan Growth .005961.

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Higher Positive value of Jenson’s measures indicates good market timing ability of fund managersas regard investment in securities

Performance Appraisal

Equity Scheme

i. As far as the equity schemes are concerned, Reliance Vision Growth was at the top withhighest average monthly return (2.5032%) followed by Reliance Growth Fund (2.4002%),ICICI Prudential Tax Plan Growth (2.0373%), Birla Sun Life Equity Fund Growth (1.9982%),HDFC Top 200 Growth (1.9883), Birla Sun Life MNC Fund (1.6069%), ICICI PrudentialGrowth Fund (1.523%), ICICI Prudential FMCG Fund (1.4816%) and Birla Sun Life BuyIndia Fund (1.4665%).

ii. Calculation of total risk as measured by standard deviation shows that ICICI Prudential TaxPlan was the most risky scheme with highest standard deviation (0.101619), followed byReliance Vision Growth (0.101581), Birla Sun Life India Opportunities Fund (0.101142). ICICIPrudential FMCG Growth was least risky scheme with lowest standard deviation (0.072029).

iii. Calculation of systematic risk as measured by beta shows that all the equity schemes foundlow systematic risk as beta less than 1, ICICI Prudential Tax Plan have highest beta (0.58984)followed by BSL Equity Fund Growth (0.57253), Birla Sun Life India Opportunity Fund (0.54895)LIC Equity Fund Growth (0.53301) and Reliance Growth Fund (0.52993). ICICI PrudentialFMCG Growth have lowest beta (0.3366).

iv. The coefficient of Determination (R2) measures the extent to which market index has beenable to explain the variation in mutual funds. The maximum and minimum value of R2 wasfound in the case of ICICI Prudential Growth Plan (0.5184) & Birla Sun Life MNC Fund(0.2571).

v. As per Sharpe ratio Reliance Growth Fund (0.208988) maintain 1st Rank followed by RelianceVision Growth (0.197199), HDFC Top 200 Growth (0.173323), Birla Sun Life Equity FundGrowth (0.158833), ICICI Prudential Tax Plan (0.151283), lowest Sharpe ratio found in thecase of LIC Tax Plan Growth (0.037636)

vi. As per Treynor Ratio Reliance Vision Fund (0.038674) highest ratio, followed by RelianceGrowth Fund (0.035857), HDFC Top 200 Growth (0.030317), ICICI Prudential FMCG Growth(0.029161), and Birla Sun Life MNC Fund (0.027309), lowest Treynor ratio found in the caseof LIC Tax Plan Growth (0.006953).

vii. As per Jenson’s alpha Reliance Vision Growth (0.022442) performed well followed by RelianceGrowth Fund (0.021352), HDFC Top 200 Growth (0.017428), and ICICI Prudential Tax PlanGrowth (0.017424) lowest Jenson’s alpha found in the case of LIC Tax Plan Growth (0.005961).

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Debt Scheme

i. As far as the income schemes are concerned, Birla Sun Life Monthly Income Plus was at thetop with highest average monthly return (0.8421%) followed by ICICI Prudential IncomeFund (0.7817%), Birla Sun Life Income Plus (0.7665%), Birla Sun Life Income Fund (0.7495%).

ii. Calculation of total risk as measured by standard deviation shows that ICICI Prudential IncomeFund Growth was the most risky scheme with highest standard deviation (0.020414) followedby Birla Sun Life Income Plus Growth (0.018286), Birla Sun Life Income Fund (0.017836),Birla Sun Life Monthly Income Plus was least risky scheme with lowest standard deviation(0.017068).

iii. Calculation of systematic risk as measured by beta shows that all the income schemes foundlow systematic risk as beta less than 1, Birla Sun Life Income Fund have highest beta (0.17482)followed by ICICI Prudential Income Fund (0.12054), Birla Sun Life Income Plus Growth(0.02204) and Birla Sun Life Monthly Income Plus Fund (0.09035).

iv. The maximum and minimum value of R2 was found in the case of Birla Sun Life Income PlusGrowth (0.0148) and ICICI Prudential Income Fund Growth (0.0023) and in case of Birla SunLife Monthly Income Plus (0.3576).

v. As per Sharpe ratio Birla Sun Life Monthly Income Plus (0.230694) maintain 1st Rank followedby Birla Sun Life Income Plus Growth (0.145737), Birla Sun Life Income Fund (0.139881) andlowest Sharpe ratio found in the case of ICICI Prudential Income Fund Growth (0.137973)

vi. As per Treynor Ratio ICICI Prudential Income Fund (0.233666) highest ratio, followed byBirla Sun Life Income Fund (0.142715), Birla Sun Life Income Plus (0.120927), and Birla SunLife Monthly Income Plus (0.043573).

vii. As per Jenson’s alpha Birla Sun Life monthly Income Plus (0.008485) performed well followedby ICICI Prudential Income Fund (0.007756), Birla Sun Life Income Plus (0.007555), andlowest Jenson’s alpha found in the case of Birla Sun Life Income Fund (0.007408).

Balanced Scheme

i. As far as the balance schemes are concerned, Birla Sun Life 95 was at the top with highestaverage monthly return (1.5434%) followed by ICICI Prudential Balance Fund (1.1527%),Birla Sun Life Freedom Fund (0.9223%).

ii. Calculation of total risk as measured by standard deviation shows that Birla Sun Life 95 Fundwas the most risky scheme with highest standard deviation (0.069698) followed by ICICIPrudential Balance Fund (0.062286), Birla Sun Life Freedom Fund (0.060821).

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iii. Calculation of systematic risk as measured by beta shows that all the balanced schemes foundlow systematic risk as beta less than 1, Birla Sun Life 95 Fund have highest beta (0.43115)followed by ICICI Prudential Balance Fund (0.36749) and Birla Sun Life Freedom Fund(0.32581).

iv. The maximum and minimum value of R2 was found in the case of Birla Sun Life 95 Fund(0.514) and Birla Sun Life Freedom Fund (0.4022).

v. As per Sharpe ratio Birla Sun Life 95 Fund (0.149705) maintain 1st rank followed ICICIPrudential Balance Fund (0.104787), lowest Sharpe ratio found in the case of Birla Sun LifeFreedom Fund (0.069438).

vi. As per Treynor Ratio ICICI Prudential Balance Fund (0.177599) highest ratio, followed byBirla Sun Life 95 Fund (0.0242), Birla Sun Life Freedom Fund (0.012962).

vii. As per Jenson’s alpha Birla Sun Life 95 Fund (0.013278) performed well followed by ICICIPrudential Balance Fund (0.009689), Birla Sun Life Freedom Fund (0.007594).

Out of the total 20 schemes studied, five schemes (25%) showed an average return higherthan in comparison to the market return while the remaining 15 schemes (75%) generated lowerreturns than that of the market. The top five performers are Reliance Growth Fund, RelianceVision Fund, ICICI Prudential Tax Plan, HDFC Top 200 and Birla Sun Life Equity Fund.

The Sharpe ratio is important from small inventors point of view who see diversificationthrough mutual funds, i.e. mutual funds are supposed to protect small investors against vagaries ofstock market and the fund managers of these schemes have done well to protect them. RelianceGrowth Fund, Reliance Vision Fund, ICICI Prudential Tax Plan, HDFC Top 200 and Birla SunLife Equity Fund have performed better than the other schemes.

Treynor ratio is the excess return earn over risk free return per unit of systematic risk i.e.beta. Reliance Growth Fund, Reliance Vision Fund, ICICI Prudential Tax Plan, HDFC Top 200and Birla Sun Life Equity Fund indicate that investors who invested in these schemes to form welldiversified portfolio did receive adequate return per unit of systematic risk undertaking.

Jensen’s measure is the regression of excess return of the scheme with excess return ofthe market. Higher positive value of alpha posted by the schemes indicates its better performance.The analysis of the schemes shows Reliance Growth Fund, Reliance Vision Fund, ICICI PrudentialTax Plan and HDFC Top 200 have highest positive alpha.

Conclusion

The analysis of the open ended schemes shows that out of twenty, five schemes namelyReliance Growth Fund, Reliance Vision Fund, ICICI Prudential Tax Plan, HDFC Top 200 and

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Birla Sun Life Equity Fund, performs better in comparison to benchmark index BSE-100 index interms of monthly average return and risk involved in these schemes less then benchmark. Inrespect of models suggested by Sharpe, Treynor and Jenson’s measures these schemes also performbetter.

References

1. Agarwal P.R. (1996), “Mutual funds-A Comprehensive Approach”, Orient Law house, Delhi.

2. Anjaria, D.C., AMFI Workbook, AMFI Mumbai,

3. Gupta, O.P. and Sehagal S. (2000), “Investment Performance of Mutual Funds: The IndianExperience”, In Indian Capital Markets: Trends and Dimensions edited by UMA Shashikantand Arumugam, Tata McGraw Hill, New Delhi.

4. Jayadev M. (1996)’ “Mutual Fund Performance; An Analysis of Monthly Returns”, FinanceIndia, Vol. X, No.1, (March), Sadhak H, (1997) “Mutual Fund Investment and Market Practicesin India”, Sage Publication India.

5. Jayadev M. (1998), “Performance Evaluation of Portfolio Managers: An Empirical Evidenceon Indian Mutual Funds”, Applied Finance Vol.5, No.2, July.

6. Khuran, Ajay (1996), “Top Management Turnover – An Empirical Investigation of MutualFund Managers”, Journal of Financial Economics, 3.

7. Mishra B, (2001), “A study of Mutual Funds in India”, unpublished Research paper under theaegis of Faculty of Management Studies, University of Delhi.

8. Pandian, Punithavathy, Security Analysis and Portfolio Management, Vikas Publication HousePvt. Ltd.

9. Rao K.V. and Venkateshwarlu, K. (1998), “ Market Timing Abilities of Fund Managers-A caseStudy of Unit Trust of India”, A paper presented at the Second Capital Market ConferenceOrganized by UTI Institute Capital Market, Mumbai.

10. Sahadevan and Raju MT, (1996), “Mutual Funds Data, Interpretation and Analysis”, Prenticehall of India.

11. Singh, Jaspal, Mutual Funds: Growth Performance and Prospectus, Deep and Deep PublicationPvt. Ltd., New Delhi, 2006 .

43


UNearthing the Epidemic of Non-per Forming AssetsA Study with Reference to Public Sector

Banks in India.Dr. Hosmani.A.P*, Mr.Jagadish Hudagi**

Introduction:

The economic reforms initiated by the then finance minister and present prime minister ofIndia Dr. Manmohan Singh would have been remained incomplete without the overhaul of Indianbanking sector. The important aspect of norms and guidelines for making the whole sector vibrantand competitive. The problem of losses and lower profitability of Non-Performing Assets (NPA)and liability mismatch in banks and financial sector depend on how various risks are managed intheir business.

Non-performing Assets (NPAs) are the smoking gun threatening the very stability of Indianbanks. NPAs wreck a bank’s profitability both through a loss of interest income and write-off ofthe principal loan amount itself. In a bid to stem the lurking rot, RBI issued in 1993 guidelines basedon recommendations of the Narasimham Committee that mandated identification and reduction ofNPAs. Their implementation immediately pushed many banks into the red. So serious is the problemthat an RBI report suggested that reducing NPAs be treated as a ‘National Priority’. According tothe concept of Non-Performing Assets in banks are those assets, which cease to generate incomefor the banks and remain irregular due to non payment of interest and principal amount. In themilieu of the complex changes when the dilemma of banks NPA was gradually recognized for thefirst time at its peak velocity, in 1992-93 there was resultant uproar and confusion as the problem inlarge magnitude exploded unexpectedly commercial banks were unable to analyze and make arealistic or complete assessment of the prevailing situation. The partial perceptions and hastyjudgments led to a policy of ad-hoc-ism. This characterized the approach of the authorities duringthe last two-decades towards finding solutions to banking ailments and dismantling recoveryhindrance. Even after repeated effort made to correct it, but the out comes were unfavorable, theproblem was challenging in fact it has became an epidemic.

The level of NPAs of the Indian banking system are now comparable to several advancedeconomies and significantly lower than several economies in world. RBI rates reduction in NPAsis one of the major achievements of the Indian banking sector of recent times. But still the Indianbanking sector is facing a serious problem of exploding amount of NPAs. Magnitude of the problem

* Associate professor,, Dept. of Commerce, Gulbarga University Gulbarga (Karnataka)-

** Research Scholar, Dept. of Commerce, Gulbarga University

44


can be understood by the fact that the level of NPAs which are to the tune of Rs.59926 Crores inPublic sector banks, Rs.17639 Crores in Private sector banks, Rs.84747 Crores in Scheduledcommercial banks, and Rs.7180 Crores in foreign banks, for the year 2009-10 The earning capacityand profitability of many banks and financial institutions has been badly affected by the high level ofNPAs. Controlling the growing NPAs becomes a challenging task in Indian economic scenario. Itaffects the liquidity, profitability, and equity. This present research paper is designed to examine theexisting position of banks in respect of Non performing assets, ascertain the causes of the problemand its remedial measures.

Statement of the Problem:

Credit is like putting paste out of a tooth paste, it is easy to get it but recovery is somewhat difficult, like putting that paste back in to the tube. That is the reason why good moneylent, some times becomes bad and doubtful, in the banking parlance it is called as Non-PerformingAsset. NPA are like flab, which causes in convenience to the Banking sector, it is a brought forwardlegacy accumulated over the past decades, when prudent norms of Banking were unoccupiedrelaxing by the radiance of security provided by government ownership. It is not wrong to havepursued social goals, but this does not justify relegating banking goals and fiscal discipline to thebackground. Ever increasing NPAs have a direct impact on profitability, liquidity and solvency.Since Indian banking industry is largely dominated by Public sector banks with almost two thirdshare of total advances in the economy it is facing an acute problem with regard to NPAs. Thereis a need to manage the ever increasing level of NPAs. Keeping this issue in view the present studyhas undertaken.

Review of Litrature:

In the context of banking sector, the issue of Non performing assets has been studied andkeenly observed by plenty of researchers, a synoptic review of the relevant literature on the topic ofNPAs has been described as under.

Basavaraj.G.Bhavi, (1990), a teacher fellow, conducted a study on Assessment of Regional ruralbanks credit on target groups- A case study of Krishna Grameena Bank. The essential objective ofthe study is to Bank’s credit on target groups in terms, Formation of assets, and to examine theextent of repayment of loan and overdue position and reasons for over dues.

Bhatacharya (2002), studied NPA management of banks and stated that surest way of containingNPAs is to prevent their occurrence. He offered suggestion on proper risk management, strong andeffective credit monitoring, co-operative working relationship between banks and borrower etcshould be tenets of NPA management policy.

Ramkrishna and Bhargavi (2004), study on Non performing asset management, found that theasset quality of commercial banks has improved considerably due to bringing in the reform packages.

45


C.Chandrakant, (2007), conducted a study on Non performing assets in Karnataka State financialCorporation – A case study of Gulbarga Division. The main objective of the study was to assess theimpact of NPA. And he suggested that better credit risk management will be an effective tool inresolving the issue NPAs.

Ashok Khurana and Mandeep Singh (2009), stated that issue of mounting NPAs is a challengingto public to public sector banks. The study found that the asset wise classification of PSBs is inright direction and there is significant variation in the recovery of NPAs in the different sector. Theresearch observed that PSBs should not be loaded with the twin object of profitability and socialweal fair.

Nature and Scope of the Study:

The present study is empirical and descriptive in nature. The study is confined to examinethe state of Non performing assets in Commercial banks operating in India wise public sectorbanks has been taken in to account, a period of 5 years has been considered.

Objectives of the study:

The banking sector striving very hard to nullify NPAs, in fact it is the level of NPAs that toa great extent determines its fincial health. Hence the following objectives have been set for ourstudy.

1. To study the magnitude and trend of NPA of Public sector banks in India.

2. To evaluate the asset portfolio and NPA proportion of Public sector bank.

3. To study the strength and weakness in recovery aspect, and provision created for NPAs insample banks.

4. To focus on sector wise NPAs and determine depth of it.

5. To offer necessary measures for effective management of NPAs in the light of our findings.

For this purpose Public sector banks which are operating in India are considered. An attemptalso been made to cross sectional analysis of NPAs.

Hypothesis of the Study:

1. There is no significant association between gross NPAs to gross advances of the public sectorbanks.

2. There is no significant difference between, priority sector, public sector, & non priority sectorfrom NPAs point of view.

3. There is no significant relation between various recovery channels, likewise Lok Adalats,DRTs and SARFESI Act.

4. There is no significant reduction in the portion of gross NPAs to gross advances.

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Methodology:

The study is descriptive and investigative in nature, it evaluate the NPAs level in publicsector, banks for a period between 2005-06 to 2009-10. By going through the path of objectives setfor the study, the relevant secondary data has been collected through various sources like, RBIweb site, Trend and progress in banking various issues, economic survey of India. The data socollected has been tabulated and analyzed by using various ratio techniques the study also examinesthe trend of NPAs in various sample banks. The findings of the study are inconformity with thestatistical tools applied as such, Average, ANOVA, correlation, and comparative percentage analysis.

Analysis and Inerpretaion:

It is the quality of loan assets which determines the financial viability and strength. Theincreasing overdue advances turning as a cause of non performing assets in public sector banks inIndia. This not only hampers the profitability but also dry out the liquidity of the bank. Completeavoidance of such losses is tough task, the management of a bank most of the strive hard avoidsuch losses. The volume of such non performing assets decides the fate of a bank. In order toassess the waves of non performing assets in public sector banks in India, the data has beentabulated shown in the following tables.

Table-1: Gross NPAS of Public Sector Banks. (Amount In-corers)

Year Gross-Advances GrossNPAs %

2005-06 1134724 41358 3.6

2006-07 1464493 38968 2.7

2007-08 1819074 40595 2.2

2008-09 2282081 44957 1.97

2009-10 2736347 59926 2.19

Gross NPAs to Gross Advances ratio.

Sources: RBI Trends & report of Banking in India 2005-2010

Table-2: Correlation Between Gross NPAS and Gross Advances

Gross Gross AdvancesNPAs Public Sector Banks

Gross NPAs Pearson’s Correlation 1 0.838

Level of Sig. (2-tailed) 10.1

N 5 5

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Table-3: ANOVA Test

Model Sum of Squares d.f Mean square F Sign.

1 Regression 204717000 1 204717000 7.06 10.1

Residual 86994400 3 28998133.33

Total 291711400 4

Predictor: (Constant) Gross advances,(Dependent variable) Gross NPAs.

It can be noticed from the table that the gross advances public sector banks increased from amt1134724 crore in 2005-06 to amt 2736347 crore in 2009-10. A drastic raise of 241.14 percentbetween 2005-06 to 2009-10. It is clear from the fact that there is continuous upturn trend ofgross advances during the study period.

At the same time gross NPAs of the public sector banks have raised from amt 41358 crore in2005-06 to amt 59926 crore in 2009-10. It has shown an increase of 144.89 percent during thestudy period, in case of gross NPAs also an increase has been recorded.

The statistical test of Pearson correlation shows that there is a high degree of positive correlationbetween gross advances and gross NPAs with r = 0.838. From table values of ANOVA, F=7.06 and at 5 percent level of significance the table value which is higher, thus the null hypothesisof no significance between gross NPAs and gross advances of public sector banks has beenaccepted.

Table-4: Net NPAS of Public Sector Banks. (Amount In-corers)

Year Net Advances Net NPAs Public sectorBanksPercentage

2005-06 1106288 14566 1.3

2006-07 1440146 15145 1.1

2007-08 1797504 17836 1.0

2008-09 2250532 21155 0.9

2009-10 2694910 29644 1.1

Total 9289380 98346 5.4

Average 1857876 19669 1.06

Net NPAs to Net Advances ratio.


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Net advances public sector banks increased in absolute terms from amt 1106288 crore in 2005-06 to amt 2694910 crore in 2009-10. A drastic raise of 243.59 percent between 2005-06 to2009-10. It is clear from the fact that there is continuous upturn growth of Net advances duringthe study period.

By looking at the Net NPAs of the public sector banks an increasing trend is noticed from amt14566 crore in 2005-06 to amt 29644 crore in 2009-10. It has shown an increase of 203.51percent during the study period.

During the study period on an average Net advances of public sector bank is amt 1857876crore, on other hand the average Net NPA is amt 19669 crore 1.06 percent of average advanceswhich is quite an alarming indication by looking at the volume of Net NPAs ( Table 4).

Table-5: Classification of Loan Assets. (Amount In-corers)

Bank Standard Sub-Standard Doubtful Loss Assets Total NPAsGroup Assets Assets Assets

Year Amount % Amount % Amount % Amount % Amount % %Change

2005-06 1092607 96.2 11453 1.0 25028 2.2 5636 0.5 42117 3.7 00

2006-07 1425519 97.3 14275 1.0 19873 1.4 4826 0.3 38974 2.7 -1.0

2007-08 1778476 97.8 17290 1.0 19291 1.1 4018 0.2 40598 2.2 -0.5

2008-09 2237556 97.9 26603 0.9 21019 0.9 4296 0.1 51918 2.2 00

2009-10 2673534 97.8 28791 1.0 25383 0.9 5750 0.2 59924 2.1 -0.1

Average 1841538 97.4 19682 0.9 22119 1.3 4905 0.26 46706 2.6 -0.5

Figures in percentage column are loan assets as a percentage to Total loan assets of respective year.

Classification of Assets as RBI guidelines


Loan assets of banks are classified in to four categories i.e. standard assets, sub-standardassets, doubt full assets, and loss assets. Standard assets being the good quality of loan assets onthe other hand sub-standard assets, doubt full assets, and loss assets put together constitutes nonperforming assets. All the other three categories of NPAs as a percentage to loan assets arerecorded a decline trend over the study period. Sub-standard assets showed a reduction from 1.0percent in 2005-06 to 0.9 percent in 2009-10. The doubt full assets reduced from 2.2 percent in2005-06 to 1.3 percent in 2009-10. The loss assets also registered decline from 0.5 percent in 2005-

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06 to 0.26 in 2009-10. Overall the non performing assets came down considerably i.e. from 3.7percent in 2005-06 to 2.1 percent in 2009-10. Indicating a positive trend of financial soundness. Theaverage standard assets, sub-standard assets, doubt full assets, and loss assets are amt 1841538crore, amt 19682 crore, amt 22119 crore and amt 4905 crore. Lastly the average NPAs being amt46706 crore (Table-5).

Table-6: Sector Wise NPAS of Public Sector Banks: (Amount In-corers)

Year Priority Sector Non Priority Sector Public Sector Total NPA

Amount % Amount % Amount % Amount %

2005-06 22374 54.0 18664 45.1 340 0.8 41378 100.0

2006-07 22954 59.1 15158 39.2 490 1.2 38602 100.0

2007-08 25287 63.6 14163 35.6 299 0.7 39749 100.0

2008-09 24318 55.2 19251 43.7 474 1.1 44043 100.0

2009-10 30848 53.8 25929 45.3 524 0.9 57301 100.0

Average 25156 57.1 18633 41.7 425.4 0.94 44215 100.0

Figures in percentage column are loan assets as a percentage to NPAs amount.

Sector wise NPA to Gross NPA percentage.


Table-7: ANOVA Test

Sources of Variation Sum of Squares d.f Mean Square F-Value Table Value

Between 1642800000 2 821401000 75.004 3.89 at 5% level

Within 131417000 12 10951400 of significance

Total 1774220000 14

In the above Table.No-6 NPAs have been classified in to three sectors i.e. priority sector,public sector and non priority sector. As per the guidelines on lending. The average sector wiseNPAs of priority sector, non-priority sector and public sector observed as follows amt 25156crore, amt 18633 crore and amt 425.4 crore respectively. It is found that asset quality of banksrecorded considerable improvement in reduction of NPAs on an average with respect to publicsector i.e.0.94 percent compared to an average of 57.1 percent with priority sector and anaverage of 41.7 percent in case of non-priority sector ( Table-6).

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Sector wise analysis of ANOVA shows that F=75.004 at 5 percent level of significance thetable value is 3.89 percent which is lower, thus the null hypothesis of there is no significantdifference between, priority sector, public sector, & non priority sector has been rejected(Table-7).

Table – 11: Provission For NPA. (Amount In-corers)

Year Public sector Banks

NPA Amt ProvisionAmt %

2005-06 41358 25024 60.5

2006-07 38968 22139 56.8

2007-08 40595 21180 52.1

2008-09 44957 22658 50.4

2009-10 59926 28402 47.4

Average 45161 23881 52.9

Gross NPAs & percentage of provision.


The NPA provisioning for the year 2005-06 amt 25024 crore where as the volume increasedto 28402 crore, but it is interesting to note that even though the volume increased considerablythe percentage of provisioning came down significantly i.e. in 2005-06 from 60.5 percent to 47.4percent. At the same time on average 52.9 percent provision has been made during the studyperiod (Table-11).

Recovery measures for Bad loans:

The Reserve Bank of India concerning to the issue of bad loans proposed prompt correctiveaction (PCA) mechanism for controlling the menace of NPA and has introduced various measureslike Credit risk management models, Compromise settlement methods, effective use of DebtRecovery Tribunals (DRTs), Asset Reconstruction Companies, Securitization and Reconstructionof Financial Assets and Enforcement of security interest (SARFAESI) Act-2002, circular ofinformation on defaulters, Corporate Debt Restructuring (CDR), Lok Adalats and so on to curb theepidemics of NPAs.

In the following table-9 an attempt has been made to measure the performance of variousrecovery channels through which the bad loans commercial banks in India have been recovered.

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Table-9: NPAS recovery through various channels (Amount In-corers).

Year Lok Adalats DRTs SARFAESI ACT Total

Amount Recovery Amount Recovery Amount Recovery Amount Recovery %Involved Involved Involved Involved

2005-06 2144 265 6273 4735 8517 3363 16934 8363 49.38

2006-07 758 106 9156 3463 9058 3749 18972 7318 38.57

2007-08 2142 176 5819 3020 7263 4429 15224 7625 50.08

2008-09 4023 96 4130 3348 12067 3982 20220 7426 36.72

2009-10 7235 112 9797 3133 14249 4269 31281 7514 24.02

Average 3260 151 7035 3540 10231 3958 20526 7649 37.26

NPA amount recovered through various Legal modes and its percentage.

Sources: RBI Trends & report of Banking in India 2005-2010.

Table-10: ANOVA Test

Sources of Variation Sum of Squares d.f Mean Square F-Value Table Value

Between 43592500 2 21796200 98.92 3.89 at 5% level of

Within 2643910 12 220326 significance

Total 46236400 14

The various recovery channels have been introduced from time to time for expediting therecovery of bad loan amount banks. Among the several channels of recovery available with thebanks, debt recovery tribunals (DRTs) and SARFAESI Act have been the most effective interms of amount recovered. On an average recovery amount from DRTs measured as 50.31percent and the SARFAESI Act stood at 38.68 percent but in case of Lok Adalats it is just 4.63percent from bad loans. Even by looking at the over all recovery percent of bad loans it was49.38 percent in 2005-06 it came down drastically to 37.26 percent in 2009-10 (Table-9).

The statistical test of ANOVA table shows F= 98.92 and at 5 percent level of significance thetable value is 3.89 which is lower, thus the null hypothesis of there is no significant relationbetween various recovery channels has been rejected (Table-10).

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Reasons and Causes for NPA:

There are numerous factors responsible for the alarming level of non performing assets.

Some of the most crucial aspects of such reasons are mentioned as under.

Improper and ineffective proposal appraisal system.

Inefficient credit risk management.

Reckless funding in order to achieve the illegitimate loan sanctioning targets.

Intentional will full defaulters and faulty projects.

Recession and variation in economic conditions.

Poor audit practices and building up pressure for loan sanction.

Direct lending under subsidy schemes.

Un-sound financial condition of the borrower.

Major Findings of the Study:

“Stitch in times save nine”, timely support may save a genuine unit. Have head and hearttogether, for a human approach. The followings are some of the important findings of the study.

The fund blocked in as Gross NPA is huge i.e. amt 59926 crore during the year 2009-10. Butthere is no time frame and follow up to recover the blocked amount.

The NPA level during the study period is quite alarming but it is positive sign to note that thepercentage of NPAs is reducing i.e. it was 3.6 in 2005-06 and came down to 2.19 in 2009-10.

The non performing assets came down considerably i.e. from 3.7 percent in 2005-06 to 2.1percent in 2009-10. Indicating a positive trend of financial soundness.

Sector wise analysis of NPAs shows that the proportion of NPAs for the priority sector loanhas increased on an average i.e. 57.1 percent compared to 41.7 percent to non priority sectorand only 0.94 percent to public sector.

Result of ANOVA sector wise break up of NPAs indicates that the null hypothesis of nosignificant association between, priority sector, public sector, & non priority sector has beenrejected.

Like wise ANOVA result of various recovery channels, indicates that the null hypothesis of nosignificant relation between various recovery channels has been rejected.

Specific recovery targets wise monthly, quarterly, and annually were fixed, but these targetsneither monitored properly nor achieved regularly.

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Lack of commitment towards the work by the bank employees. Political involvement in theadministration.

In ability to adopt, changes and rigidity in decision making by the public sector banks comparedto Private sector banks, Foreign banks and NBFC to improve its performance.

Suggestions:

In the light of our findings of the study, following suggestions offered to deal effectively inreducing the non performing assets.

Third Basel Committee report on banking supervision should be completely implemented inregular practices of the bank.

IFRS accounting practices need to be adopted to have more transparent and effective accountingsystem.

Introducing KYC norms effectively & client profile cards to have proper monitoring system.

It is better to discourage too ambitious loan proposal where ambitious projects and overenthusiastic promoters involved, it may take longer gestation period to implement the project &which invents high risk.

NPA’s management cell can be constituted at Head Office and Branch Offices to monitor thecases. To look into the NPA Portfolio of every branch.

Conclusion:

Indian banking industry is largely dominated by public sector banks with almost two thirdshare of total advances in the economy. The committee report on banking supervision Basel-IIIand IFRS accounting practices need to be adopted since the global rules with respect banking andaccounting practices are changing, this in tern helps in better asset quality management andtransparency in accounting. The study conducted on the topic unearthing the epidemic of nonperforming assets with reference to public sector banks in India, found that there is a slightimprovement in the asset quality reflected by decline in the diverse NPA percentage. But even thenthe quantum of NPAs is alarming with public sector banks in India, since NPA being as an importantparameter for assessing financial performance of banks the mounting volume of NPAs will deterthe financial health in terms of profitability liquidity and economies of scale in operation. The bankhas to take timely action against degradation of good performing assets.

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References:

1. Dr. Jaynal Ud-din Ahmed, The Management Accountant, Management of non performingassets of Commercial Banks in India, June 2009.

2. Dr. K.Rajender, Management of non performing assets in public sector banks. The IndianJournal of commerce, January-March 2009.

3. Dr. Vibha jain, “Non performing assets in Commercial banks”, Google books 2007.

4. Dr.Ashok Khurana and Dr.Mandeep singh, NPA management: A study of new private SectorBanks in India, Indian journal of finance, September 2010.

5. Google Web site.

6. Parameshwaran, R, and Natarajan, S, “Indian Banking” Sultan Chand and Sons, 2002.

7. R.K. Bharadwaj, Chetya Anuradha R, Majumdar kakali, “Quantitative Techniques for BusinessManagers” Himalaya publication 2009.

8. Report on Trends and Progress in Banking 2005-06 to 2009-10.

9. Reserve Bank of India Reports, 2005-06 to 2009-10.

10. Shri, M, Narashimam Working Group Recommendations 1975.

11. Subharao, P, “principles and practice of Bank Management”, Himalaya publication 1988.

12. T.V. Gopalkrishna, Management of non performing assets a study with reference to publicsector banks in India, Indian Institute of Banking and Finance, Google books, 2004.

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Working Capital Management of Indian ElectricalEquipment Manufacturers-A Comparative Study

T. Chandrabai* Dr.K.Venkata Janardhan Rao**

Introduction

The world in which we live is not perfect. It is characterized by considerable amount ofuncertainty regarding the demand, market price, quality and availability of own products and thoseof suppliers. These real world facts introduce problems and require the necessity of working capital.The most important areas in the day to day management of the firm, is the management of workingcapital. Working Capital Management refers to all management decisions and actions that ordinarilyinfluence the size and effectiveness of the working capital. It is concerned with the most effectivechoice of working capital sources and the determination of appropriate levels of the current assetsand their use. It focuses attention to the managing of current assets, current liabilities and therelationships that exist between them. Proper management of working capital leads to a materialsavings and ensures financial returns at the optimum level even on the minimum level of capitalemployed. Both excessive and inadequate working capital is harmful for a firm. Excessive workingcapital leads to unproductive use of scarce funds. On the other hand, inadequate working capitalusually interrupts the normal operations of a business and impairs profitability.

In this article an effort has been made to analyze the working capital management in IndianElectrical Equipment Manufacturers during the period 2005-06 to 2009-10. And this study is limitedto the companies BHEL and ABB Ltd represent public and private sector enterprises respectively.

Profile of the Companies

BHEL has been at the helm of indigenous Heavy Electrical Equipment industry in India witha sustained track record of earning profit since 1971-72. BHEL has grown in stature over the yearswith continued inflow of orders, manufacturing prowess, continued thrust on technology leading toa strong presence in domestic and international markets as a major supplier of power plant equipmentbesides establishing substantial inroads in select segment of products in Industrial sector and Railways.

* Assistant Professor in Department of Management Studies. Padmasri Dr.B.V.Raju Institute of Technology, Narsapur,Medak. Mobile: 09885096280, E-mail: [email protected]

** Professor of Commerce and Business Management, Kakatiya University, Warangal (AP). Email:[email protected]

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BHEL caters to core sectors of the Indian Economy viz., Power Generation and Transmission,Industry, Transportation, Renewable Energy, Defense, etc. The wide network of BHEL’s 15

manufacturing divisions, 2 repair units, 4 power sector regions, 8 service centers, 15 regional offices,

1 subsidiary and a large number of Project Sites spread all over India and abroad enables the

Company to promptly serve its customers and provide them with suitable products, systems and

services - efficiently and at competitive prices.

ABB is one of the world’s leading powers, automation engineering companies and provide

solutions for secure, energy-efficient generation, transmission and distribution of electricity and for

increasing productivity in industrial, commercial and utility operations. ABB operations in India are

in excess of one billion US dollars and the company has 14 manufacturing facilities and over 6,000

employees in the country. ABB has an extensive countrywide presence with around 18 marketing

offices, 8 service centers, 3 logistic warehouses and a network of over 850 channel partners.

Objectives of the study

The main objective of the present study is to analyze the working capital management in

BHEL and ABB Ltd-A comparative study over a period of 5 years i.e., from 2005-06 to 2009-10.

The specific objectives of the study are as under:

To study liquidity position of the company by taking four measures at time namely, inventory to

current assets, debtors to current assets, cash and bank to current assets and loan &advances

and other assets to currents assets.

To analyze the component of working capital to identify the items responsible for changes in

working capital.

Methodology

The samples selected for this study are BHEL and ABB Ltd represent public and private

sector enterprises respectively. . The study covers five years period from 2005-06 to 2009-10. This

study is based on secondary data which is collected from annual reports of the companies and

various studies made available through library work. For assessing the performance of the working

capital position, in this study the technique of ratio analysis have been used. The collected data

have been analyzed in five ways:

1. Analysis of liquidity ratio.

2. Analysis of liquidity position.

3. Analysis of operating cycle.

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4. Analysis of components of Gross working capital.

5. Liquidity ranking.

For assessing the behavior of data statistical techniques have been also used e.g. mean,growth rate, standard deviation and coefficient of variation in this study.

Abbreviations Used

Current Ratio CR

Quick Ratio QR

Absolute Liquid Ratio ALR

Inventory/Sales INV/S

Age of Inventory AINV

Debtors/Sales D/S

Working Capital Turnover/Total Assets WCT/TA

Current Assets/Sales CA/S

Age of Debtors AD

Debtors DEB

Cash &Bank Balances C&B

Land &Advances L&A

Gross Working Capital GWC

Standard Deviation S.D

Coefficient of Variation C.V

Findings

1. The current ratio of BHEL is decreased from 1.58 in 2005-06 to 1.31 in 2008-09 again itincreased from later years. Fluctuations were observed in ABB ltd Company’s current ratio.The average current ratio of BHEL (1.41) is less than ABB Ltd (1.44). Both the companieshaving the current ratio less than the ideal which is 2:1. The quick ratio of both the companiesalso received in the same proportion like current ratio. But the quick ratio of both the companiesis more than the ideal which is 1:1. It is cleared that company’s short-term liquidity position issatisfactory for creditor’s working capital point of view (From TABLE_1).

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2. The absolute liquidity ratios of both the companies are in satisfactory position because it is morethan the ideal ratio which is 0.5:1. It means both the companies having enough cash in hand andcash at bank (From TABLE_1).

3. Inventory to sales ratio measures the velocity of conversion stock in to sales. Usually, a highinventory sales indicates efficient management of inventory because more frequently the stockwill be sold, the lesser amount of money is required to finance the inventory. This ratio in BHELis higher than ABB Ltd and fluctuations were observed in both the companies (From TABLE_1).

4. Age of Inventory shows moving position of inventory during the year. If age of inventory isminimum it means companies activity position is satisfactory, they are able to sell their productwithin shorter period of time which indicate sound liquidity position of organization. This is veryless in BHEL than ABB Ltd and fluctuations were observed in both the companies. On theother, if age of inventory is too high it indicate slow moving of stock, which affected directlyliquidity position of company(From TABLE_1).

5. Debtors to sales ratio indicate the velocity of debt collection of the firm. Generally, the highervalue of debtor’s turnover the more efficient is the management of debtors/sales or more liquidare the debtors. This ratio is higher in BHEL than ABB Ltd and it is increased from 2005-06 to2009-10 continuously, which is not good sign for liquidity point of view (From TABLE_1).

6. Working capital turnover ratio measures the efficiency with which the working capital is beingused by a firm. A higher ratio indicates efficient utilization of working capital. But a very highworking capital turnover ratio is not a good situation for any firm. This ratio is higher in BHELthan ABB Ltd(From TABLE_1).

7. Current assets to sales ratio indicates the efficiency with which working capital turns intosales. A lower ratio implies by and large a more efficient use of funds. Thus, a High turnoverrate indicates reduced lock up of fund in working capital. This ratio is higher in BHEL than ABBLtd (From TABLE_1).

8. Average collection period measures the quality of debtors. Generally, shorter the averagecollection period the better is the quality of debtors as a short collection period implies quickpayment by debtors. Longer the average collection period, longer are the chances of bed debts.This ratio is higher in BHEL than ABB Ltd (From TABLE_1).

9. The liquidity position of both the companies analyzed in TABLE_2 and TABLE_3. In BHELthe current assets had been increased from 2005-06 to 2009-10 with a growth rate of 162.9%.The liquid assets had been increased with a growth rate of 167.74% and the growth rate ofcurrent liabilities is 214.36%. In ABB Ltd the current assets had been increased from 2005-06to 2009-10 with a growth rate of 76.14%. The liquid assets had been increased with a growth

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rate of 73.15% and the growth rate of current liabilities is 68.06%. The growth rate of currentassets, liquid assets and current liabilities in BHEL is higher than ABB Ltd. But the workingcapital growth rate in ABB Ltd (201.17%) is higher than BHEL (74.57%). The coefficient ofvariation in BHEL is higher than ABB Ltd in case of current assets, liquid assets, currentliabilities and working capital.

10. From TABLE_4 & TABLE_5, the share of each element has been calculated in percentageseparately. In BHEL out of the four element of working capital the element namely debtorscontributed highest in gross working capital with a mean of 44.86% which shows that workingcapital blocked up due to increases in debtors resulting collection charges and bad debts areincreases. Where as the other current assets occupied the second position. The mean of inventoryto working capital is 21.29%, and it played third position in total current assets. A decrease ofinventory in total current assets is positive sign for liquidity and working capital point of view.The same situation has observed in case of ABB Ltd. The mean percentage of all these elementsin BHEL is higher than ABB Ltd.

11. From TABLE_4 & TABLE_5, the liquidity ranking in case of debtors to current assets ratio,cash & bank to currents ratio and other currents assets including loan & advances to currentassets ratio, a high value indirect relatively favorable position and ranking has been done in thatorder. On the other hand, a low inventory to current assets ratio shows a more favorableposition and hence ranking has been done in that order. Final ranking has been done on theprinciple that the lower points scored the more favorable are the liquidity position.

12. From TABLE_6 & TABLE_7, the operating cycle indicate efficient utilization of workingcapital within the organization. If the operating cycle is maximum, means the working capital isproperly and efficiently utilized. The operating cycle and cash cycle in BHEL is increased from2005-06 to 2009-10 with fluctuations. The same situation has observed in case of ABB Ltd.But the operating cycle and cash cycle in BHEL is higher than ABB Ltd.

Table - 1: Liquidity ratios of selected companies

Company Year CR QR ALR INV/S AINV (%) D/S WCT/TA CA/S AD

BHEL 2005-06 1.58 1.22 0.88 0.28 213.2 0.54 0.34 1.22 179.4

ABB 1.41 1.23 0.62 0.08 1131 0.37 0.26 0.64 111.1

BHEL 2006-07 1.46 1.17 0.79 0.24 255.7 0.56 0.29 1.22 178.6

ABB 1.37 1.21 0.56 0.08 1017 0.41 0.24 0.69 122.9

BHEL 2007-08 1.40 1.11 0.79 0.30 237.5 0.62 0.27 1.43 204.1

ABB 1.42 1.22 0.52 0.09 875 0.43 0.26 0.69 144.2

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BHEL 2008-09 1.31 1.03 0.74 0.30 259.6 0.61 0.22 1.41 194.6

ABB 1.52 1.28 0.60 0.12 658.5 0.46 0.29 0.76 170.7

BHEL 2009-10 1.32 1.04 0.69 0.28 242.2 0.63 0.22 1.31 203.4

ABB 1.47 1.26 0.59 0.11 672.9 0.46 0.27 0.78 167.9

Mean(BHEL 1.41 1.12 0.78 0.28 241.6 0.59 0.27 1.32 192

Mean(ABB) 1.44 1.24 0.58 0.09 870.9 0.43 0.26 0.71 143.4

Source: Annual reports of BHEL & ABB Ltd

Table - 2: Liquidity position of BHEL (Rs in Crores)

Year Current Liquid Current Working Increase/ Assets Assets Liabilities Capital Decrease in

2005-06 16330.78 12586.41 10320.02 6010.76 -

2006-07 21062.97 16845.3 14420.11 6642.86 +632.1

2007-08 27906.18 22169.78 20022.30 7883.88 +1241.02

2008-09 36901.07 29064.05 28332.90 8568.17 +684.29

2009-10 42934.81 33699.35 32441.72 10493.09 +1924.92

Mean 29027.16 22872.98 21107.41 7919.75 -

Growth Rate (%) 162.9 167.74 214.36 74.57 -

S.D 9811.26 7722.44 8281.78 3509.77 -

C.V 33.8 33.76 39.24 44.32 -

Source: Annual reports of BHEL

Table - 3: Liquidity position of ABB Ltd (Rs in thousands)

Year Current Liquid Current Working Increase/Assets Assets Liabilities Capital Decrease in

2005-06 27,966,725 24,419,730 19,919,063 8,047,662 -

2006-07 41,106,989 36,219,887 29,993,114 11,113,875 3066213

2007-08 46,998,260 40,571,726 33,215,206 13,783,054 2669179

2008-09 47,492,652 40,198,591 31,319,765 16,172,887 2389833

2009-10 49,262,216 42,283,690 33,476,911 24,237,036 8064149

Mean 42565368.4 36738724.8 29584811.8 12102139.8 -

Growth Rate (%) 76.14 73.15 68.06 201.17 -

S.D 7797739.15 6472032.71 4998633.24 6067414.91 -

C.V 18.32 17.62 16.89 50.13 -

Source: Annual reports of ABB Ltd

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Table - 4: BHEL company’s components of working capital (%)

Year INV/GWC DEB/GWC C&B/GWC L&A/GWC Liquidity Rank Total Final1 2 3 4 Rank Rank

1 2 3 4

2005-06 22.93 43.89 25.32 7.35 5 3 4 1 13 5

2006-07 20.02 46.03 27.58 5.42 1 2 3 4 10 2

2007-08 20.75 42.91 30.05 4.97 2 5 1 5 13 5

2008-09 21.24 43.29 27.95 6.57 3 4 2 2 11 3

2009-10 21.51 48.18 22.81 6.55 4 1 1 3 9 1

Mean 21.29 44.86 26.74 6.17


Table - 5: ABB LTD company’s components of working capital (%)

Year INV/GWC DEB/GWC C&B/GWC L&A/GWC Liquidity Rank Total Final1 2 3 4 Rank Rank

1 2 3 4

2005-06 12.7 56.1 19.5 6.36 2 5 1 5 13 4

2006-07 11.9 58.9 15.6 6.82 1 4 2 3 10 1

2007-08 13.7 63.3 7.40 7.50 3 1 5 1 10 1

2008-09 15.4 60.2 11.1 6.70 5 2 4 4 15 5

2009-10 14.2 59.4 11.9 7.20 4 3 3 2 12 3

Mean 13.58 59.58 13.1 6.92

Source: Annual reports of ABB Ltd

Table - 6: Operating Cycle of BHEL (in days)

Component 2005-06 2006-07 2007-08 2008-09 2009-10

Inventory conversion period 171.22 142.71 153.68 140.58 150.72

Debtor’s conversion period 179.31 178.54 204.08 194.60 203.62

Total operating cycle 350.53 321.25 357.76 335.18 354.44

Less: Creditors conversion period 126.06 113.69 121.67 106.44 118.58

Cash cycle 224.47 207.56 236.09 228.74 235.86


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Table - 7: Operating Cycle of ABB LTD (in days)

Component 2005-06 2006-07 2007-08 2008-09 2009-10

Inventory conversion period 32.28 35.86 41.71 55.42 54.24

Debtor’s conversion period 110.99 122.91 144.13 170.69 167.88

Total operating cycle 143.27 158.77 185.84 226.11 222.12

Less: Creditors conversion period 109.45 112.25 115.07 126.37 118.52

Cash cycle 33.82 46.52 70.77 99.74 103.60

Source: Annual reports of ABB LTD

Conclusion

From the viewpoint of conventional standard of working capital, the quick ratio, absoluteliquidity ratios in both the companies are satisfactory. The age of inventory, working capital turnoveris very much satisfied in BHEL than ABB Ltd, so some improvement is required in case of ABBLtd. In this study it is cleared that the overall position of the working capital in both the companiesare satisfactory. In both the companies the major portion of the current assets are in form ofdebtors and loan and advances. The liquidity position mainly depends upon debtors and debt collectionpolicy, but other components like inventory, loan and advances, cash and bank balance and billsreceivable etc. are also responsible. The ratio debtors to gross working capital is very high in caseof ABB Ltd, Average collection period is very high in case of BHEL, so in this study we found thatthere is a need of improvement in debtors and debt collection policy. The management of should betry to proper utilization of debtor’s and also try to maintain the debtors as per their requirement soliquidity will not interrupted.

References

1. M. Pandey: “Financial Management theory and practices”, Vikas publishing company, NewDelhi (2000).

2. Prasanna Chandra: “Financial Management theory and practice”, TMH, New Delhi (2001).

3. www.bhel.com

4. www.abb.co.in

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