Reseach Work On Eva

THE USE OF ECONOMIC VALUE ADDED (EVA) TO MEASURE THE PERFORMANCE OF COMMERCIAL BANKS IN NIGERIA

BY BABATUNDE YUSSUF JIMOH

SUBMITTED TO AGRIBUSINESS AND FARM MANAGEMENT DEPARTMENT, COLLEGE OF AGRICULTURAL SCIENCES, OLABISI ONABANJO UNIVERSITY, YEWA CAMPUS, AYETORO, OGUN STATE.

IN PARTIAL FULFILMENT FOR THE AWARD OF B.Sc. COOPERATIVE AND BUSINESS MANAGEMENT HONOURS.

ABSTRACT This research evaluates the performance of commercial banks in Nigeria using economic value-added (EVA). For purpose of this study, ten (10) out of the twenty-one (21) commercial banks listed on Nigeria stock exchange market (NSE) were examined. Also structured questionnaires were used to obtain data from 30 stock broken firms and 70 individual investors. All together 100 respondents made the sample of investors. Descriptive statistics such as frequency, ranking and simple percentage, statistical analysis e.g. correlation, regression and quantities techniques (ROA, ROE, EPS, EVA, MVA, PER etc) were employed in this study. On average investors (respondents) rank technical analysis first (4.42), follow by fundamental analysis (4.28), fundamental and technical analysis claim the third position (4.23), respondents consider noise in the market (2.67) in stock valuation. Banks were rank base on value creation and destruction in parenthesis, in the year 2006 first bank Nig. Plc create the highest value (EVA), during the year access bank Nig. Plc and diamond bank destroyed value. As at the year 2007, united bank for Africa produce the highest EVA. The year 2008 brought changes as bank PHB improve tremendously from 8 positions in the previous year to claim first and first bank Nig. Plc. claim second. Union bank plc destroy value in the year 2008. Among the commonly used traditional methods there is strong correlation between EVA and EPS than others, with (0.4) in 2006, (0.88) in 2007 and (0.53) in 2008. Net interest margin display the highest association with market adjusted return, with R2 of 19%, follow by return on assets (ROA) with R2 of 18%. While net income displays R2 of 15%, EPS displays R2 of 10.1%. EVA displays the lowest R2 of 2.6%. Change in EPS explains 25% change in market value added, while change in ROA explains 21% and EVA explain 19.7%. Contrary to EVA proponents that EVA outperform and dominate the traditional accounting performance in explaining stock market returns, I found that EVA weakly associate with stock market returns and ROA,EPS, NI and ROE generally, dominate EVA in association with stock market returns, EPS outperform EVA in explaining change in market value added (EVA).

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Individual investors on Nigeria stocks exchange market should improve in the use of fundamental analysis while investors should give more preference to portfolio analysis, as diversification of investments will help a lot to reduce. Along with EVA, companies should continue monitoring performance using the traditional measures of accounting profits such as EPS, ROA and ROE. This is consistent with other stock market research suggesting that to explain more completely the variability in stock returns, multiple determinants are required.

iii

TABLE OF CONTENTS

Abstract

vi

Table of Contents

vii

CHAPTER ONE – INTRODUCTION 1.1

Background of the study

1

1.2

The state of Nigeria banks before and after N25 recapitalization

2

1.3

Problems statement

4

1.4

Objectives of the study

5

1.5

Justification of the study

5

CHAPTER TWO – LITERATURE REVIEW 2.1

Literature review

7

2.2

Theoretical frameworks

13

2.3

EVA and its components

15

CHAPTER THREE – RESEARCH METHODOLOGY 3.1

The area of study

17

3.2

Method of data collection

17

3.3

Sampling techniques

17

3.4

Method of data analysis

18

CHAPTER FOUR – RESULTS AND DISCUSSION 4.1

Result and discussion of findings

22

4.1.1

Socio- economic characteristics and investment behaviour of sample

iv

investors on Nigeria stock exchange market

22

4.1.2

Value creation and destruction by commercials banks in Nigeria

29

4.1.3

Relationship between the behaviour of EVA traditional performance measures.

4.1.4

30

Association between performance measures, stock market adjusted returns and market value-added.

31

CHAPTER FIVE – SUMMARY, CONCLUSION AND RECOMMENDATIONS. 5.1

Summary and policy implication of research findings.

34

5.2

Conclusion

36

5.3

Recommendation.

37

References

39

Appendix

v

CHAPTER ONE 1.0 1.1

INTRODUCTION Background of the Study Bank has a number of stakeholders with differing, sometime conflicting goals.

The stakeholders include the owners, lenders, management, personnel, costumer, suppliers, creditors, government and regulatory agency. In corporate government agency theory the managers are regarded as agents of the owners in stakeholders’ wealthmaximization. Managing to create a sustainable shareholder value (SHV) is currently recognized by academics and partitions as the most important for Nigeria banks. One might ask why since 1990s there is such a strong interest toward SHV among practitioners, academic and even regulators. The primary reason for this increasing of interest of banks toward creation of SHV is that banking market has evolved becoming more competitive. This new scenario requires a new approach to keep both stakeholders and shareholders satisfied. Banks performance can be measured using various techniques. Banks performance measure can be qualitative or quantitative characterization of performance. Quantitative performance which is the most useful for investors, analysts, academics and practitioners was focused in this study. It refers to the physical measurement that enables investors to evaluate business activities through financial statement of the banks. The most basic quantitative performance measure is centered on earnings, such as earning per share (EPS). Though investors use many other tools such as Return on Equity (ROE), Return on Assets, Return on invested capital, price Earning Ratio (PER), pre-tax profit margin and the banks traditional performance measures Net interest margin. In evaluating stock but all begins and ends with earnings. 1

However, it is argue if earnings or profit alone can be considered as best performance tools. Sternwat (1991) argue that accounting earnings fails to recognize cost of capital and the riskiness in firms operations. He stress further that earnings (EPS) and earning growth are misleading measure of corporate performance. Chen and Dodd (1997), Rogerson (1997), Lehn and Makhja (1997) suggested that there is no single accounting based measure upon which one can rely to explain change in shareholders wealth. Stewart (1991) opined that as earnings or earnings per share (EPS) derived from accounting information can be easily manipulated, it is believe that for a new method to be adopted it must have more elements in its calculations as compare to current performance measure tools. The tools must combine factors such as Economics, accounting, and market information in its assessment consideration. Franker (2006) said that EVA is based on the principles that since a company’s management employ equity capital to earn a profit; it must pay for the use of this equity capital. Drucker (1995) said until a business return a profit that is greater than its cost of capital, it operates at loss. Never mind that it pays taxes as if it had genuine profit. The enterprises still return less to the economy than devours in resource …………Until them it does not create wealth it destroy it.

1.2

The state of Nigeria banks before and after the N25bm Recapitalisation exercise (2005) Modern banking stated in Nigeria in 1891 when the south African based banking

corporation (ABC) now first bank of Nigeria open shop in Lagos, followed by the entry

2

of other foreign banks like Barclays bank (now Union bank of Nigeria) British and French bank for commerce and industry (united bank for Africa – UBA). These foreign banks discriminate local businessman and denied Nigerians facilities to fund their business. In other to break the monopoly of these banks, there were mushroom of indigenous banks that were established during the period, notable among them are, African continental bank (ACB), National bank of Nigeria (NBN) and Wema bank (Oslika and Chris 2007). The period of 1952 – 1958 saw the first round of bank failures in Nigeria, According to Uzoaga (1998 p 80), by 1954, out of about 25 indigenous bank establish during the period, only four (4) survived the 1952 bank ordinance, while twenty-one (21) went under. Between the 1970s and 1980s, the banking industry was dominated by the “big three” – First bank, Union bank and United bank for African. After the deregulation of the of the financial system as part of the structural adjustments programs (SAP) in 1986, the number of banks increase to over 100, this make the late 1980s and early 1990s refer to as years of financial boom. The banking industry witnesses another round of bank failures between 1989 and 1998. As at 2003 there were 89 banks left. The then banks were comparatively small in size with the total capitalization of less than USD46bn. However, the new done beings in July, 2004 when the CBN led by Prof. Charles Soludo announced a consolidation plan designed to reform and growth the capacity of Nigeria banking industry. The reform includes increase in bank shareholders fund to N25bn from the former level of N2b compliance on or before 25, Dec., 2005. At the end of N25 billion recapitalization exercise 25 banks sealed the huddle either by merger, acquisition or alone.

3

1.3

Problems Statement Modern financial management posits that a firm must seek to maximize the

shareholder value. Market value of a firm’s share is the measurement of the shareholder wealth. With increasing pressure on firm to deliver shareholders value, there has been a renewed emphasis devising measure of corporate financial performance to increase shareholders wealth. This is as a result of recent question by value investors and analysts – Does high growth and accounting profitability lead to increase value to shareholders? One professedly recent innovation in the filed of internal and external performance measure is the trade-marked variant of residual income know as Economic value-added (EVA). However, some pervious studies have found mix result in using EVA as a performance tool. As an advocate and support, Stewart (1994) has suggested that EVA stand well out from the crowd as a single best measure of wealth creation on a contemporaneous basis and it’s almost 50% better than its closet accounting-base competitors (accounting measurement tools), in explaining changes in shareholders wealth. On other hand, Armitage, et al., (2001) said manager will remember the strong correlation claimed between the adoption of EVA measurement and stock performance. Recent evidence has shown that the correlation is much weaker than original claimed, in fact, it`s not better than the measurement system it has claimed to displace. Fernalez (2001) observe a low (and sometime negative) correlation between EVA and MVA and concluded that traditional tools present higher level of correlation with the increase in MVA. This study is motivated by this controversy; its important to know which performance measure best explains change in market value? 4

1.4

Objective of the Study The broad objective of this study is to examine an appropriate way of evaluating

bank’s performance while the specific objectives are to 1.

describe the investment behaviour of two different market participants in Nigeria stock exchange (NSE).

2.

determine banks that have created or destroyed shareholders value (in term of EVA) during the period under review.

3.

analyze the relationship between the behaviour of EVA and accounting-base performance measures.(ROA, ROE, EPS, EARNING POWER, NET INCOME, PER, NET INTEREST MARGIN)

4.

Analyse the performance measure that best explain change in market adjusted returns .

1.5

Justification of the study This research work set out to evaluate the performance of commercial banks using

economic value-added. EVA is frequently regarded as a single, simple measure that provides a real picture of shareholder wealth creation. In addition to motivating managers to create shareholder value and to serving as a basis for the calculation of management compensation, there are further practical advantages that value based measurement systems can offer. An EVA system helps managers Roztoci and Needy (1998) to: • make better investment decisions; • identify improvement opportunities; and • consider long-term and short-term benefits for the company.

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EVA is an effective measure of the quality of managerial decisions and a reliable indicator of a company’s value growth in the future. Constant positive EVA values over time will increase company values, while negative EVA values might decrease company values. This will enable investors to distinguish between dying banks and under value one. Bank managers will also monitor the performance of their banks in order to increase shareholder value. The professional e.g. financial analysts, stock brokers, regulatory agency will also judge the performance of banks on a move sound note. It will also serve as a guide and reference material to other researchers who may chose the research into the topic in future.

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CHAPTER TWO 2.0

LITERATURE REVIEW Performance measurement systems were developed as a means of monitoring and

maintaining organisational control, which is the process of ensuring that an organisation aims at strategies that lead to the achievement of its overall goals and objectives. Performance measures, is the key tools for performance measurement systems and play a vital role in every organisation as they are often viewed as forward-looking indicators that assist management to predict a company’s economic performance and many times reveal the need for possible changes in operations (Nanni, Dixon and Vollmann 1990; Otley, 1999; Simons, 1999). However, the choice of performance measures is one of the most critical challenges facing organisations (Ittner and Larcker, 1998; Knight, 1998). Poorly chosen performance measures routinely create the wrong signals for managers, leading to poor decisions and undesirable results. There are enormous hidden costs in misused performance measures. Shareholders pay the bill each day in the form of overinvestment and acquisitions that do not pay off etc. It is not that management is poor. Simply, it is the wrongly chosen performance measures, which in turn push management to take improper decisions (Knight, 1998). Performance measures may be characterised as financial and non-financial. This study has tended to restrict itself to looking only at financial performance measures, such as earnings ROA, ROE, EPS, etc. and EVA. The perceived inadequacies in traditional accounting performance measures have motivated a variety of measurement innovations such as the economic value measures (Ittner and Larcker, 1998). Over the last few years an increasing number of consultants,

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corporate executives, institutional investors and scholars have taken part in the debate on the most appropriate way to measure performance (Rappaport, 1998). Consultants are willing to demonstrate the mastery of their recommended performance models. Corporate executives show clearly that the performance models adopted by their corporations are the most appropriate and successful. Institutional investors debate the advantages of alternative performance models for screening underperforming companies in their portfolios. Finally, scholars develop performance measurement models and test the extent to which existing performance evaluation and incentive compensation systems inspire management decisions and performance itself (Rappaport, 1998). Traditional performance measurement systems were developed at a time when decision-making was focused at the center of the organisation and responsibilities for decision-making were very clearly defined. According to Knight (1998, p. 173) ‘these performance measurement systems were designed to measure accountability to confirm that people met their budget and followed orders’. However, during the last two decades it was widely argued (see: Rappaport, 1986; 1998; Stewart, 1991; 1999) that most of the performance measurement systems failed to capture and encourage a corporation’s strategy, producing mostly poor information leading to wrong decisions. While traditional accounting performance measures are popular measures for financial performance measurement, they are often under severe critique since they do not take into consideration the cost of capital and moreover, they are influenced by accrual based accounting conventions. On the other hand, modern value-based measures are promoted as the measures of a company’s real profitability. Since value became of

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primary concern to investors, proponents of value based measures claim that those measures are the only performance measures tied directly to stock’s intrinsic value (Stewart, 1991; 1999; Grant, 2003). Especially, EVA proponents have argued that EVAand stock prices appear to have a trend to move together. Moreover, they have asserted the superiority of information contained in EVA when it is compared to traditional accounting figures. Those claims have been empirically tested by many scholars but with contradictory and mixed results. The most important of those studies are reported here. Bao and Bao (1998) investigated the usefulness of value added and abnormal economic earnings of 166 US firms. The results indicated that value added is a significant explanatory factor in market returns, and its explanatory power is higher than that of earnings. Riahi-Belkaoui (1993) also examined the relative and incremental content of value-added, earnings and cash flows in the US context. The results indicated that the information content of value-added is a major determinant of market returns, providing incremental information content beyond both net income and cash flow. Later, RiahiBelkaoui and Fekrat (1994) also found that performance measures based on net valueadded had lower variability and higher persistency than many corresponding accountingbased numbers, including earnings and cash flows. In a closely related but separate study, Riahi-Belkaoui and Picur (1994) confirmed the association between both relative changes in earnings and net value-added and the relative change in security prices. They also found that both the levels of net value-added and the changes in net value added play a role in security valuation. Isa and Lo (2001) said EVA has gain significant attention as an alternative to traditional accounting

9

measure foe assessing corporate performance due to its transparency and capacity to provide more vital information. McClenahen (1998) similarly observed that traditional corporate performance measures are being relegated to second class status as metric such as EVA become management primary tool. On the predictive ability of value added Karpik and Riahi-Belkaoui (1994) used the market model test value-added variables in explaining market risk, and found that the incremental information content given by value added variables is beyond that provided by accrual earnings and cash flows. Earlier work by Bannister and Riahi-Belkaoui (1991) also used the market model to explain a target firm’s abnormal returns during the takeover period. Their findings suggested that takeover targets have lower value-added ratios than other firms do in the year preceding completion of the takeover. The debate on the superiority of value added over traditional performance measures has taken three most popular approaches (correlation with MVA, stocks returns and market adjusted returns) the key important one for this study are present below. Uyemura et al., (1996), a particularly interesting study for this study since it focuses on banking, analysed the largest 100 U.S. bank holding companies over a period of ten years (1986-95). By regressing changes in standardised MVA against changes in standardised EVA (defined as EVA divided by capital) and traditional performance measures, (EPS, NI, ROE and ROA). They provided evidence suggesting that the correlation between MVA and those measures are: EVA 40 per cent, ROA 13 per cent, ROE 10 per cent, NI 8 per cent and EPS 6 per cent. EVA provides highest correlation which support EVA superiority.

10

Milunovich and Tseui (1996) found that MVA is more highly correlated with EVA than with EPS, EPS growth, ROE, FCF or FCF growth. O’Byrne (1996) examined the association between market value and two performance measures: EVA and NOPAT. He found that both measures had similar explanatory power when no control variables were included in the models, but that a modified EVA model had greater explanatory power than NOPAT. Lehn and Makhija (1997) enter the debate by questioning which performance measure does the best job of predicting the turnover of chief executive officers (CEOs). Their results suggested that labour markets evaluate CEOs on the basis of EVA and MVA performances, rather than on the basis of more conventional accounting measures. From a slightly different perspective, Rogerson (1997) investigated the moral hazard that exists with managers to increase shareholder wealth and to thereby increase the firm’s cash flows so as to increase managerial compensation. They concluded that residual income (or EVA) as a performance measure will ensure that managers will always make efficient investment decisions. On the other hand, Fernandez (2001) observes a low (and sometimes negative) correlation between EVA and MVA, and concludes that traditional tools present higher levels of correlation with the increase in MVA. Riceman et. al (2000) found similar result. Peterson and Peterson (1996) analysed traditional and value-added measures of performance and compared them with stock returns. According to their findings, traditional measures are not empirically less related to stock returns than return on capital: as result, traditional measures should be not eliminated as a means of evaluating

11

performance, though these have no theoretical appeal. From this point of view, Peterson and Peterson (1996) rule out the possibility of value added measures not being worthwhile: since value added measures focus on economic rather than accounting profit, these play an important role in evaluating performance because managers will aim towards value creation rather than mere manipulation of short-sighted accounting figures. Dodd and Chen (1996) found that stock returns and EVA per share are correlated as advocated by EVA adopters. However, the correlation was far from perfect. On the other hand they found that ROA explained stock returns slightly better than EVA. Their findings also suggested that if a company wants to adopt the philosophy of EVA as a corporate performance measure, it might want to consider using RI instead. Finally, since nearly 80 per cent of their sample’s stock returns could not be explained by EVA, they concluded that EVA is neither the only performance measure to tie with stock returns nor a very complete one. This is consistent with other stock market research suggesting that to explain more completely the variability in stock returns, multiple determinants are required. Chen and Dodd (1997) extended the previous research and examined the explanatory power of EPS, ROA, ROE, RI, and four EVA related measures. Firstly, they found that improving EVA performance is associated with higher returns. However this association is not as strong as suggested by EVA proponents. No single EVA measure was able to account for more than 26 per cent of the variation in stock returns. Secondly, the EVA measures provided relatively more information than the traditional accounting measures in terms of the strength of their association to the stock returns. Moreover, they

12

suggested that the accounting earnings provided significant incremental explanatory power above EVA. Thus, Chen and Dodd (1997) concluded that companies should not follow the suggestions of EVA advocates where traditional accounting measures should be completely replaced with EVA and suggested that along with EVA, companies should continue monitoring the traditional measures of accounting profits such as EPS, ROA and ROE. Finally, consistent with their previous results, they found that RI provided almost identical results to EVA, without the need of accounting adjustments advocated by Stern Stewart & Co.

2.2

Theoretical background The conceptual underpinnings of EVA derive from a well-established

microeconomic literature regarding the link between firm earnings and wealth creation (Bell,1998). For much of this history, at least since Alfred Marshall’s Principles of Economics, the focus of analysis has been on adjustments to accounting earnings to reflect the of capital, primarily because the unadjusted measure can be a misleading indicator of performance in both theory and practice. In the seminal contribution, Marshall (1920) concluded, “the gross earnings of management which a man is getting can only be found after making up a careful account of the true profits of his business, and deducting interest on his capital”. Later, the desirability of quantifying economic profit’ as a measure of wealth creation was operationalised by Solomons (1965) “as the difference between two quantities, net earnings and the cost of capital”. This measure of ‘residual income’ is then defined in terms of after-tax operating profits less a charge for invested capital which reflects the firm’s weighted average cost of capital. Close parallels are thereby found in the related (non-trademarked) concepts of ‘abnormal earnings’, 13

‘excess earnings’, ‘excess income’, ‘excess realisable profits’ and ‘super profits’ (Biddle etal., 1997). Just as EVA® bears a close semblance to non-trademarked financial performance measures, it is also closely related to performance metrics offered by other consultants. For example, the Chicago-based Boston Consulting Group, Price Waterhouse and HOLT Value Associates employ variations of Cash Flow Return on Investment or CFROI. CFROI is typically calculated in two steps. First, the inflation-adjusted cash flows available to all capital owners in the firm are measured and compared with the inflationadjusted gross investment made by the capital owners. Second, the gross cash flow to gross investment is translated into an internal rate of return by adjusting for the finite economic life of depreciating assets and the residual value of non-depreciating assets (such as land and working capital). In addition, there are many other value-based metrics that are even more closely related to EVA®. In fact, the legal conflict between Stern Stewart’s EVA® and KPMG’s ‘Economic Value Management’ over the proprietary nature of EVA® suggests even closer, less discernible differences in these products (Lieber, 1998). Myers (1996), amongst others, has arrived at this conclusion: “The fact is, EVA, CFROI, and all the others are premised on fundamental economics that 20 years ago was called residual income”. It is this perception of EVA as “a practical and highly flexible refinement of the economists’ concept of ‘residual income’ – the value that is left over after a company’s stockholders (and all other providers of capital) has been adequately compensated” that provides the basis for the following discussion (Stern, Stewart and Chew, 1995, p. 32). 2.3

Eva and its Components

EVAt = NOPATt – (Capital Investedt-1 * Cost of Capital) 14

Where: EVAt = EVA of periodt NOPATt = NOPAT of periodt Capital Investedt-1 = Capital Invested measured at the end of periodt-1 In order to calculate EVA, there are three basic inputs: a) Net Operating Profit After Tax (NOPAT); b) Capital invested; c) Cost of capital invested In calculating NOPAT and capital invested there are some adjustments propose by eva advocates to produce un-bias EVA. NOPAT and capital invested cannot be calculated on an accounting basis, but need to be calculated on an economic basis. Advocates of EVA have identified more than 120 accounting adjustments, but it is unrealistic even to think of making all these adjustments for any single company. What researchers do in empirical investigation is to calculate a “disclosed EVA” which is EVA obtained making some standard adjustments to publicly available accounting data. Advocates of EVA suggest some adjustments in order to: • Avoid mixing operating and financing decisions; • Provide a long term perspective; • Avoid mixing flow and stock; • Convert GAAP cash-flow items to additions to capital. According to franker (2006) most companies require no more than about ten adjustments to produce a sufficiently EVA figure. He then put forward four rules to decide on what adjustments to make to a company operating income 15

The materiality of the adjustments The effect they will have on management’s behavior How easily they are understood The degree to which they will impact on the company’s market value The two most common adjustments for commercial banks have been made in this paper. Also, the cost of capital will follow view express Sironi (1999, pp 6) he identify four differences (labeled as “ the separation principle” “bank as a provider of liquidity services” “capital ratios,” “off balance sheet pro”) between a bank’s cost of capital and that of non-financial company, and observes “ with a capital structure exogenously determined by regulators, a marginal cost of debt close to that

obtainable from inter

bank market, and relatively similar to that of all other major banks and an array of product that do not need any debt financing, bank should look at their costs of capital as a key variable. This study will employ cost of equity capital to measure cost of capital for bank. CAPM was used to calculate cost of equity. Invested capital was also calculated using book value of equity after making the necessary adjustment.

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CHAPTER THREE 3.0

RESEARCH METHODOLOGY

3.1

Study Area The study was carried out carried out on Nigeria banking industry. The Nigeria

banking industry for the scope of this study includes the twenty-one (21) listed commercial banks on Nigeria stock exchange market (NSE).

3.2

Method of Data Collection. Both primary and secondary data was employed in this study. Primary data include

the use of structured questionnaire while the secondary data extracted from the financial statement of the study banks, Sec databank special publication among others.

3.3

Sampling Techniques A stratified sampling technique was used in this study. For the purpose of this

study commercial banks was divided into 3 strata base on their years of trading present on NSE. Including; •

The first generation banks i.e union bank, first bank plc, united bank for Africa and Afribank ( have trading present as at 1995)

•

Second generation banks i.e Diamond bank, intercontinental bank, access bank and GTB. (have trading present as at 2005)

•

New generation basks i.e bank PHB and bank and sterling bank. ( have trading present as at 2006)

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This make a sample of 10 commercial banks out of the 21 listed commercial banks on Nigeria stock exchange market. This study covers the period from 2006 to 2008. Two different market participants were examined to describe their investment behaviuor. Including: -

Stock broken firms

-

Individual investors

30 stock broken firms will be selected and 70 individual investors. All together 100 respondents made the sample.

3.4

Method of Data Analysis. Descriptive statistics such as frequency, ranking simple percentage, and measure

of central tendency e.g. mean, statistical analysis e.g. correlation, regression and quantities techniques (ROA, ROE, EPS, EVA, MVA, PER etc) were employed in this study.

3.4.1

Describe the investment behaviour of different market participants on Nigeria stock exchange (NSE). Descriptive analysis was used to achieve this objective which includes frequency, percentage, ranking, mean and ttest.

3.4.2

Determine banks that have created or destroyed shareholders value (in term of EVA) during the period under review. To achieve this objective EVA was consider. Positive Economic Value – Added (EVA) figure mean or indicate that bank has created shareholders value. Negative indicate destruction of value. 18

EVA was calculated as follow; EVA =

Capital invested X (Return on capital invested – cost of capital)

=

(Return on capital invested) – (Capital invested X cost of capital)

=

NOPAT – (Capital invested X cost of capital)

EVA =

NOPATt – (Capital investedt-1 X cost of capital)

This study also follows the suit in Franker (2006) by making the two most common adjustments for a bank and one for any financial institution to produces and unbias EVA. 1.

Loan loss provision and reserve

2.

Tax provision

3.

General risk provision

3.4.3

Analyse the relationship between the behavious of EVA and an accounting-based performance measures. Correlation matrix will be used to achieve this objective. The performance measures are calculated as follow.

EVA = NOPAT – (capital investedt-1 cost of capital). Return on Assets (ROA)

=

Net Income Total Assets

Return on Equity

=

After tax profit Equity Stock

Earning power

=

Profit Before tax Total Assets

Earnings Per Share (EPS)

=

Net Profit Tax (kobo) No of ordinary shares

19

Price Earning Ratio (PER)

=

Net Income

=

Net interest margin 3.4.4

Market Price of Ordinary Shares EPS

Net Profit After Tax

=

Analyze the performance measures that best correlate with market adjusted returns market value added. Regression analysis was used to achieve this objective. Market adjusted returns was regressed against standardize EVA, four accounting performance and one bank traditional performance measures. Market adjusted returns follow Biddle et al. (1997).while for Standerdised EVA see Uyemura et al., (1996). The general model is MAR = α + β(X), then following equation were developed. MAR = α + ß (st.EVA) + e ………………………………………………... (1) MAR = α + β (ROA) + e ……………………………………………….... (2) MAR = α + β (ROE) + e ………………………………………………...… (3) MAR= α + β (NI) + e ………………………………………………….……(4) MAR= α + β (EPS) + e ..…………………………………………………... (5) MAR= α + β (NITMAR) + e.…………………………….………………… (6) This research study also takes extensive approach to consider change in market

value added (MVA) and change in performance measures. ∆MVA = α + ß∆(st.EVA) + e ……………………………………………. (1) ∆ MVA = α + β∆(ROA + e ……………………………………………… (2)

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∆ MVA = α + β∆(ROE) + e. …………………………………………….. (3) ∆ MVA= α + β∆(NI) + e .…………………………………………………. (4) ∆MVA= α + β∆(EPS) + e ..………………………………………………. (5) ∆MVA= α + β∆(NITMAR) + e ………………………………………… (6) α

= alpha

β

= beta

e

= error term

MAR = Market adjusted returns. MVA = Market value added. ROA = Return on assets ROE = Return on equity NI

= Net income

EPS

= Earnings per share

NEITMAR = Net interest margin.

CHAPTER FOUR 4.1

RESULTS AND DISCUSSION OF FINDINGS

21

This chapter presents the results of the study and the discussion of the findings. The results of descriptive analysis, EVA, correlation and regression analysis were fully discussed in this chapter. 4.1.1: Socio-economics characteristics and investment behavior of sample brokers and individuals investors on Nigeria Stock Exchange market. Table 4.1: Gender distribution of NSE market participants. Gender

User groups Broker

Investor

FEMALE

5 16.7% MALE 25 83.3% Total 30 100.0% Sources: field survey 2009.

9 12.9% 61 87.1% 70 100.0%

From the table above, there are more male respondents among the sample brokers and individual investors with 83.3% and 87.1% respectively. The female counterparts maintain 16.7% and 12.9% for brokers and individual investors respectively. This implies that there are more male stock brokers than female, this may because of time and high level of risk, and stress associated with the work of stock brokers. I also found, that male outpaces their female counterpart in stock investment, the reasons are not far fetch, male bear most of the financial responsibility of their family, hence, the need for investments to make more money. Also, female may not be able to cope with the losses that arise in stock investment at times. Table: 4-2: Age distribution of NSE markets participants. Age I8-30

User groups Broker

Investor

7 23.3%

10 14.3% 22

31-43 44-56

16 53.3% 7 23.3%

35 50.0% 21 30.0% 2 2.9% 2 2.9% 70 100.0%

57-69 70 ABOVE Total

30 100.0% Sources: field survey 2009.

As presented above, respondents of 31-34 years age group claim highest among stock brokers and individual investors with 53.3% and 50% respectively. While there are no stock broker of age 57 years and above, there 2.9% individual investor within 57-69 and 70 years above age group. This implies that it take active body and mind in stock broking. Also, it reveals, that the people of active work age group invest more in stock. This may be so, because they need to invest against the future when age may no longer permit them to work.

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Table 4-3: Educational background of NSE market participants. Education

User groups Broker Investor SCHOOL CERT. 6 8.6% DIPLOMA 20 28.6% BA/BSC 20 29 66.7% 41.4% MA/MSC 10 15 33.3% 21.4% PHD 0 0 30 70 100.0% 100.0% Sources: field survey 2009. As indicated in the table above, majority of the stock brokers held first Degree with 66.7%, also 41.4% of the sample investors held degree. Follow by master degree with 33.3% and 21.4% for brokers and individual investors respectively. Also 28.6% and 8.6% of the individual investors held diploma and school certificate qualification respectively. It could be inferred that it require higher educational qualification to be a stock broker, this may be because it require advance skill to use sophisticated tools of stock investment analysis. People of higher education invest more in stock, this may be because they understand the market and have good access to information about the market.

Table 4-4: Years of experiences of market participants. Experience 1-6

Broker 10 33.3%

User groups Investor 52 74.3%

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7-12 13-18 19-24

12 40.0% 5 16.7% 3 10.0%

25 above Total

30 100.0% Sources: field survey 2009.

10 14.3% 1 1.4% 1 1.4% 6 8.6% 70 100.0%

As presented above, majority of the investors with 74.3% had up to 6 years experience, while most of the stock brokers had 7-12 yeas experience with 40%. Also 33.3% of the brokers had 1-6 years experience. There are no brokers with 25 years above. The implication of the above findings is that activities become to boom on NSE about 6 years ago this could be attributed to the N25bn. recapitalization exercise in the banking industry that led them to stock market for investor`s money. Also, the job of stock broker require agile and able body which make it difficult if not impossible for the aged, hence years of experience.

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Table 4.5: Whether the inventors have broke or not Do have a broker NO YES

Frequency

Percent 17.0 53.0

17 53

Total

70 100 Sources: field survey 2009.

70.0 100.0

As presented above majority of the sample investors have a stock broker with 53.3%. On the other hand 17% have no broker. This may be because most the investors storm the market about 6 years ago. It could also imply that most of investors are have small amount of investment. It is not surprise that majority of the investors have brokers because it’s expected of all because an individual can not trade or process the CSCS certificate. Table 4.6: Minimum investment require by broker. Minimum investment 50000-250000 251000-500000 501000-750000 751000-1000000 Total

Frequency

18 7 3 2 30 100 Sources: field survey 2009.

Percent 18.0 7.0 3.0 2.0 30.0 100.0

As deduce from the table, 18% of the most stock broker require N50000-250000 from the client as the minimum investment before they could manage their investment or accounting. Only a few brokers require between N750000-1000000 as minimum investment. There is no surprise as the investment houses are different in size, capital base and reputation therefore some may charge higher than others.

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Table 4-7: Level of importance attached to the following items in stock investment. Broker (30) Items

Rank

Mean

Investors (70)

FUNDAMENTAL ANALYSIS TECHNICAL ANALYSIS BOTH FUNDAMENTAL AND

1 5 2

4.4333 3.9 4.2

Std. Error of Mean 0.132902 0.146609 0.121296

TECHNICAL ANALYSIS NOISE IN THE MARKET PORTFOLIO ANALYSIS NEWS PAPER MEDIA INSTINCTS EXPERIENCE FOREIGN MARKET GOVERNMENT POLICY

9 6 8 4 7 3

2.1333 3.2667 2.3333 3.9667 2.6 4

0.171091 0.11679 0.120662 0.139649 0.156102 0.172873

rank 3 1 2 8 4 7 5 9 6

Sources: field survey 2009. *

Significant at 1% level

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Mean

Whole sample (100)

4.214286 4.642857 4.242857

Std. Error of Mean 0.08845 0.05768 0.05910

Rank

Mean

t

2 1 3

4.28 4.42 4.23

(1.267) 5.715* 0.472

2.9 4.157143 3.5 3.971429 1.957143 3.928571

0.1 0.07233 0.11822 0.06426 0.11767 0.10439

8 6 7 4 9 5

2.67 3.89 3.15 3.97 2.15 3.95

4.945* 6.629* 5.487* 0.140 (3.108)* (0.365)

The table above outlines the perceptions of the two user groups regarding the level of importance they attached to a list of nine factors in their approach to stocks valuation. On average respondents rank technical analysis (4.42), follow by fundamental analysis (4.28), while both fundamental and technical analysis claim the third position (4.23), respondents consider noise in the market (2.67) and foreign market as the least important approaches in stocks valuation. This agrees with the findings of Maditinos D, et al (2007), where noise in market is second to the last among the six-user group. Since the ttest show that there are significant differences between user groups` responses, it becomes interesting to examine separately the perceptions of each group. Fundamental analysis was rank first (4.43) by broker while individual investors rank technical analysis first (4.64). Both fundamental and technical analysis was rank second by the two user group. While the stock broker rank government policy third (4.0) investors could only place it on six position (3.92). I also, found that the two user groups rely more on fundamental and technical analysis and less on portfolio analysis. This is in support of the findings of Maditinos D., et al (2007).

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4.1.2

Value creation and destruction by commercial banks in Nigeria.

Table 4.8: Value creation and destruction by sample commercial banks in Nigeria. Banks

2006

rank

2007

rank

2008

rank

First bank

(EVA) 10,090,236,100

1

( EVA) 10,137,942,00 6

( EVA) 25,137,457,440

2

Union bank

5,142,996,000

4

0 10,272,873,60

5

(8,817,905,920)

10

1

12,933,444,000

7

UBA

3,891,641,900

6

0 23,974,444,80

Afribank Access bank

7,722,042,205 (916,426,216)

3 10

0 9,455,923,044 10,335,620,94

7 4

13,654,108,012 15,237,930,872

6 5

Diamond bank (693,858,155) intercontinental 8,066,937,020

9 2

2 3,378,465,984 17,973,718,72

9 2

7,256,642,942 21,911,028,800

8 3

GTB

8,445,626,956

7

6 10,825,586,98

3

17,486,919,715

4

PHB 1,990,322,562 Sterling 4,584,379,287 Sources: field survey 2009.

8 5

2 7,599,804,724 1,438,154,963

8 10

25,473,376,475, 6,321,835,267

1 9

As presented above, banks were rank base on value creation and destruction in parenthesis, in the year 2006 first bank Nig. Plc create the highest value (EVA), and follow by intercontinental bank and Afribank to claim second and third respectively. During the year access bank Nig. Plc and diamond bank destroyed value and where rank on 10 and 9 position respectively. As at the year 2007, united bank for Africa produce the highest EVA and intercontinental bank plc maintain the second position, while GTB improve to claim the third position, access bank grab the next position while diamond and sterling bank claim 9 and 10 respectively. The year 2008 bring changes as PHB improve tremendously from 8 position in the

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previous year to claim first, first bank Nig. Plc. also bounce back to second while intercontinental drop slightly to third. Union bank plc destroy value in the year 2008. It could be inferred that intercontinental bank maintain good shareholder value during the period under review as could be categories as the most consistent bank in shareholders value creation. First bank plc is also a bank to recon with in term of shareholder value creation there is no doubts as it declares good dividends and bounce from time to time. Access bank also improves between 2007 and 2008. Diamond bank display poor shareholder value during the period under review.

4.1.3

Relationship between the behavior of (EVA) and traditional performance measure.

Table 4.8: Correlation of EVA and the traditional performance measure. 2006 EVA/EPS 0.48 EVA/ROA 0.57 EVA/ROE 0.45 EVA/PER 0.19 EVA/NIM 0.69 EVA/EP 0.60 Sources: correlation analysis.

2007 0.88 0.26 0.04 0.42 0.35 0.43

2008 0.53 0.22 0.44 0.14 0.25 0.22

As presented in table 4-8, among the commonly used traditional methods there is strong correlation between EVA and EPS than others, with (0.4) in 2006, (0.88) in 2007 and (0.53) in 2008. This seems not to agree with the findings of Verna B. P., (2003) with found that EPS display poor correlation with EVA. Return on equity (ROE) of 0.45 in 2006, 0.04 in 2007 and 0.53 in 2008 also display appreciable and stable correlation with EVA. This may because conceptual underpinning EVA of that take the cost of capital into consideration and cost of equity for banks.

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Price earning ratio displays poor correlation with EVA with (0.19) in 2006, 0.42 2007 and 014 in 2008, however, this result support the findings of Verna B.P., (2003) 4.1.4

Association between performance measure and market adjusted returns

Table 4.10: Regression of market adjusted returns and performance measures. Variables Alpha ROE 0.557 EVA 0.487 NETINMAR 0.857 ROA 0.661 NI 0.627 EPS 0.572 Sources: field survey 2009.

Beta (0.235) (0.162) (0.441) (0.4250) (0.398) (0.317)

R2 5.5% 2.6% 19% 18% 15.8% 10.1%

Std. error 0.234 0.190 0.334 0.214 0.204 0.200

As presented above, net interest margin display the highest association with market adjusted return, with R2 of 19%, follow by return on assets (ROA) with R2 of 18%. While net income displays R2 of 15%, EPS displays R2 of 10.1%. EVA displays the lowest R2 of 2.6%. This result indicate that EVA does not dominate traditional performance measures in explaining stock return as it could only explain 2.6% of the changes in market adjusted returns returns. This result support the findings of Biddle et al., (1997 and 1999) which analysed a sample of firms by comparing adjusted R2 obtained regressing stock market adjusted returns against EVA, Residual Income (RI), accounting earnings (namely, Earning Before Extarordinary Item - EBEI) and Operating Cash Flow (CFO). According to their results, EBEI has the highest adjusted R 2 and EVA has a smaller adjusted R2. I also found that ROA outperform EVA in explaining stock returns and this is inline with Dodd and Chen (1996) which found that stock returns and EVA are correlated as advocated by EVA adopters. However, the correlation was far from perfect and that ROA explained stock returns better than EVA. Biddle, Bowen and Wallace (1997) also found that traditional accounting measures, generally, outperformed EVA in explaining stock returns. Worthington and West (2001), Keef and Rush (2003), Turvey et al. (2000), found

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similar results. Therefore contrary to EVA proponents that EVA outperform and dominate the traditional accounting performance in explaining stock market returns, I found that EVA weakly associate with stock market returns and ROA,EPS, NI and ROE generally, dominate EVA in association with stock market returns. Also bank traditional performance measure (net interest margin) dominate EVA and slightly outperform ROA, NI and EPS in explaining stocks returns.

Relationship between market value added and performance measures. Table 4.11: Regression and market value added (MVA) performance measure Variables EVA EPS ROA ROE NI NETINTMAR

Alpha 3.201 6.011 6.201 3.011 4.011 4.511

Beta (0.444) (0.509) (0.452) 0.301 (0.097) (0.076)

R2 19.7% 25.9% 21.3% 9.1% 0.9% 0.6%

Std. error 6.101 1.7011 2.011 7.091 2.411 5.211

As presented above change in EPS explain 25% change in market value added, while change in ROA explains 21% and EVA explain 19.7%. Net interest margin is the most poorly associated, follow by Net income to explain 0.6% and 0.9% respectively. Change in ROE explains 9% change in market value added. This implies that EPS outperform EVA in explaining change in market value added (EVA). ROA also slightly perform better than EVA. This finding disagrees with the argument of EVA proponent that EVA outperforms the traditional performance measures in association with change in market value added. This result disagree with the findings of Taub (2003) that change in EVA explain 35% of the change in market value-added (MVA) or even seven times more than growth, consequently

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the changes in earnings per share (EPS) explaining only about 3% of change in market valueadded (MVA), Milunovich and Tseui (1996) found that MVA is more highly correlated with EVA than with EPS, EPS growth, ROE, FCF or FCF growth. Uyemura et al. (1996) studied the relationship between MVA and four traditional performance measures: EPS, NI, ROE and ROA. They provided evidence suggesting that the correlation between MVA and those measures are: EVA 40 per cent, ROA 13 per cent, ROE 10 per cent, NI 8 per cent and EPS 6 per cent. However, this results support the findings of Fernalez (2001) that’s observe a low (and sometime negative) correlation between EVA and MVA and concluded that traditional tools present higher level of correlation with the increase in MVA. Riceman et. al (2000) also found similar result.

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CHAPTER FIVE 5.0 5.1

SUMMARY, CONCLUSION AND RECOMMENDATION. Summary and Policy Implication of Research Findings. Result of the various analysis conducted in this study provided important insight into the

performance of commercial banks in Nigeria, it reveal important decision made investors and stock brokers on Nigeria stock market. There are more male respondents among the sample brokers and individual investors with 83.3% and 87.1% respectively. The female counterparts maintain 16.7% and 12.9% for brokers and individual investors respectively. On the base of age, 31-34 years age group claim highest among stock brokers and individual investors with 53.3% and 50% respectively. While there are no stock broker of age 57 years and above, there 2.9% individual investor within 57-69 and 70 years above age group. This implies that stock broking require active and able body. People of active work age group invest more in stock. Majority of the stock brokers held first Degree with 66.7%, also 41.4% of the sample investors held degree. The policy implication is that government and broker should encourage the less educated to people to invest in stocks as a form of provision for “raining days”.

Majority of the investors with 74.3% had up to 6 years

experience, while most of the stock brokers had 7-12 yeas experience with 40%. Majority of the sample investors have a stock broker with 53.3%. On the other hand 17% have no broker. Most stock broker require N50000-250000 from the client as the minimum investment before they could manage their investment or accounting. Importance they attached to a list of nine factors in their approach to stocks valuation. On average respondents rank technical analysis (4.42), follow by fundamental analysis (4.28), fundamental and technical analysis claim the third position (4.23), respondents consider noise in the market (2.67) and foreign market as the least important

34

approaches in stocks valuation. The ttest show that there are significant differences between user groups` responses. Fundamental analysis was rank first (4.43) by broker while individual investors rank technical analysis first (4.64). Both fundamental and technical analysis was rank second by the two user group. While the stock broker rank government policy third (4.0) investors could only place it on six position (3.92). The policy implication is that government should make investment friendly policy to support the market and the economy. Banks were rank base on value creation and destruction in parenthesis, in the year 2006 first bank Nig. Plc create the highest value (EVA), and follow by intercontinental bank and Afribank to claim second and third respectively. During the year access bank Nig. Plc and diamond bank destroyed value and where rank on 10 and 9 position respectively. As at the year 2007, united bank for Africa produce the highest EVA and intercontinental bank plc maintain the second position, while GTB improve to claim the third position. The year 2008 bring changes as PHB improve tremendously from 8 position in the previous year to claim first, first bank Nig. Plc. also bounce back to second while intercontinental drop slightly to third. Union bank plc destroy value in the year 2008. The policy implication is that intercontinental bank should maintain consistence, banks like diamond access sterling banks should embark on policy that will increase shareholders value. Among the commonly used traditional methods there is strong correlation between EVA and EPS than others, with (0.4) in 2006, (0.88) in 2007 and (0.53) in 2008. This seems not to agree with the findings of Verna B. P., (2003) which found that EPS display poor correlation with EVA. Return on equity (ROE) of 0.45 in 2006, 0.04 in 2007 and 0.53 in 2008 also display appreciable and stable correlation with EVA.

35

Relationship between performance measure and stocks market adjusted returns, net interest margin display the highest association with market adjusted return, with R2 of 19%, follow by return on assets (ROA) with R2 of 18%. While net income displays R2 of 15%, EPS displays R2 of 10.1%. EVA displays the lowest R2 of 2.6%. Change in EPS explains 25% change in market value added, while change in ROA explains 21% and EVA explain 19.7%. Net interest margin is the most poorly associated, follow by Net income to explain 0.6% and 0.9% respectively. Change in ROE explains 9% change in market value added. This implies that EPS outperform EVA in explaining change in market value added (EVA). ROA also slightly perform better than EVA. This finding disagrees with the argument of EVA proponent that EVA outperforms the traditional performance measures in association with change in market value added.

5.2

Conclusion This implies that there are more male stock brokers than female, I also found, that male

outpaces their female counterpart in stock investment. Stocks broking require active and able body. Also, it reveals, that the people of active work age group invest more in stock. It require higher educational qualification to be a stock broker. People of higher education invest more in stock. The two user groups rely more on fundamental and technical analysis and less on portfolio analysis stock evaluation. Stock brokers rank fundamental analysis highest while investors rank technical analysis highest. Most of the sample banks create valued on annual basis, and there is appreciable growth their shareholder value creation. EVA strongly correlates with EPS then ROA, ROE, NI and traditional bank performance measure.

36

Contrary to EVA proponents that EVA outperform and dominate the traditional accounting performance in explaining stock market returns, I found that EVA weakly associate with stock market returns and ROA,EPS, NI and ROE generally, dominate EVA in association with stock market returns, EPS outperform EVA in explaining change in market value added (EVA). ROA also slightly perform better.

5.3

Recommendation

1.

Individual investors on Nigeria stocks exchange market should improve in the use of fundamental analysis in stocks valuation. Over reliance on technical analysis could result to loss in future, mostly the long term investors should endeavor to use more of combination of fundamental and technical analysis.

2.

The two user group should give more preference to portfolio analysis as diversification of investments will help a lot to reduce losses recommended by theory.

3.

Government should and its agency should always endeavor to make sound policy that will support investment as their policies will significantly affect investment in Nigeria.

4.

Companies should not follow the suggestions of EVA advocates where traditional accounting measures should be completely replaced with EVA and suggested that along with EVA, companies should continue monitoring the traditional measures of accounting profits such as EPS, ROA and ROE. This is consistent with other stock market research suggesting that to explain more completely the variability in stock returns, multiple determinants are required.

37

5.

For banks, EVA may be an effective tool for internal decision making and performance measurement This because EVA is base on economics principles and considered cost of capital in it calculation.

38

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