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Transcript of 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 TOAGRIBUSINESS 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).
ii
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. 30
4.1.4 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 INTRODUCTION
1.1 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’ wealth-
maximization. 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.
5
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.
6
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,
7
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
8
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, Riahi-
Belkaoui and Fekrat (1994) also found that performance measures based on net value-
added had lower variability and higher persistency than many corresponding accounting-
based 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 inflation-
adjusted 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.
16
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)
17
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 un-
bias 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) =
Return on Equity =
Earning power =
Earnings Per Share (EPS) =
19
Price Earning Ratio (PER) =
Net Income = Net Profit After Tax
Net interest margin =
3.4.4 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)
20
∆ 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 9
16.7% 12.9%
MALE 25 61
83.3% 87.1%
Total 30 70
100.0% 100.0%
Sources: field survey 2009.
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 User groups
22
Broker Investor
I8-30 7 10
23.3% 14.3%
31-43 16 35
53.3% 50.0%
44-56 7 21
23.3% 30.0%
57-69 2
2.9%
70 ABOVE 2
2.9%
Total 30 70
100.0% 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.
23
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.
24
Table 4-4: Years of experiences of market participants.
Experience User groups
Broker Investor
1-6 10 52
33.3% 74.3%
7-12 12 10
40.0% 14.3%
13-18 5 1
16.7% 1.4%
19-24 3 1
10.0% 1.4%
25 above 6
8.6%
Total 30 70
100.0% 100.0%
Sources: field survey 2009.
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.
25
Table 4.5: Whether the inventors have broke or not
Do have a broker Frequency Percent
NO 17 17.0YES 53 53.0
Total 70 70.0
100 100.0
Sources: field survey 2009.
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
Frequency Percent
50000-250000 18 18.0251000-500000 7 7.0501000-750000 3 3.0751000-1000000 2 2.0
Total 30 30.0
100 100.0
Sources: field survey 2009.
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.
26
Table 4-7: Level of importance attached to the following items in stock investment.
Broker (30) Investors (70) Whole sample (100)
Items Rank Mean Std. Error of Mean
rank Mean Std. Error of Mean
Rank Mean t
FUNDAMENTAL ANALYSIS 1 4.4333 0.132902 3 4.214286 0.08845 2 4.28 (1.267)
TECHNICAL ANALYSIS 5 3.9 0.146609 1 4.642857 0.05768 1 4.42 5.715*
BOTH FUNDAMENTAL AND
TECHNICAL ANALYSIS
2 4.2 0.121296 2 4.242857 0.05910 3 4.23 0.472
NOISE IN THE MARKET 9 2.1333 0.171091 8 2.9 0.1 8 2.67 4.945*
PORTFOLIO ANALYSIS 6 3.2667 0.11679 4 4.157143 0.07233 6 3.89 6.629*
NEWS PAPER MEDIA 8 2.3333 0.120662 7 3.5 0.11822 7 3.15 5.487*
INSTINCTS EXPERIENCE 4 3.9667 0.139649 5 3.971429 0.06426 4 3.97 0.140
FOREIGN MARKET 7 2.6 0.156102 9 1.957143 0.11767 9 2.15 (3.108)*
GOVERNMENT POLICY 3 4 0.172873 6 3.928571 0.10439 5 3.95 (0.365)
Sources: field survey 2009.
* Significant at 1% level
27
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).
28
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(EVA)
2007 rank( EVA)
2008 rank( EVA)
First bank 10,090,236,100 1 10,137,942,000 6 25,137,457,440 2
Union bank 5,142,996,000 4 10,272,873,600 5 (8,817,905,920) 10
UBA 3,891,641,900 6 23,974,444,800 1 12,933,444,000 7
Afribank 7,722,042,205 3 9,455,923,044 7 13,654,108,012 6
Access bank (916,426,216) 10 10,335,620,942 4 15,237,930,872 5
Diamond bank (693,858,155) 9 3,378,465,984 9 7,256,642,942 8
intercontinental 8,066,937,020 2 17,973,718,726 2 21,911,028,800 3
GTB 8,445,626,956 7 10,825,586,982 3 17,486,919,715 4
PHB 1,990,322,562 8 7,599,804,724 8 25,473,376,475, 1
Sterling 4,584,379,287 5 1,438,154,963 10 6,321,835,267 9
Sources: field survey 2009.
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
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.
29
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 2007 2008
EVA/EPS 0.48 0.88 0.53
EVA/ROA 0.57 0.26 0.22
EVA/ROE 0.45 0.04 0.44
EVA/PER 0.19 0.42 0.14
EVA/NIM 0.69 0.35 0.25
EVA/EP 0.60 0.43 0.22
Sources: correlation analysis.
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.
30
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 Beta R2 Std. error
ROE 0.557 (0.235) 5.5% 0.234
EVA 0.487 (0.162) 2.6% 0.190
NETINMAR 0.857 (0.441) 19% 0.334
ROA 0.661 (0.4250) 18% 0.214
NI 0.627 (0.398) 15.8% 0.204
EPS 0.572 (0.317) 10.1% 0.200
Sources: field survey 2009.
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 R2 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
31
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
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
32
Variables Alpha Beta R2 Std. error
EVA 3.201 (0.444) 19.7% 6.101
EPS 6.011 (0.509) 25.9% 1.7011
ROA 6.201 (0.452) 21.3% 2.011
ROE 3.011 0.301 9.1% 7.091
NI 4.011 (0.097) 0.9% 2.411
NETINTMAR 4.511 (0.076) 0.6% 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
the changes in earnings per share (EPS) explaining only about 3% of change in market value-
added (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.
33
CHAPTER FIVE
5.0 SUMMARY, CONCLUSION AND RECOMMENDATION.
5.1 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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