A stock exchange is an exchange where stock brokers and traders can buy and sell shares of stock, bonds, and other securities. All listings are included in the Nigerian Stock Exchange All Shares index. In terms of market capitalization, the Nigerian Stock Exchange is the third largest stock exchange in Africa. Objectives: The paper assesses the impact of Nigerian Stock Market (all share index, market capitalization, and number of equities) on Gross domestic product (Economic Growth). Materials and Methods: Regression analysis and ordinary least square technique were employed. Result and Discussion: The series was stationary at 1%, 5%, and 10% α level ; the residuals were normally distributed but not serially correlated at 5% α level . All Share Index, Market Capitalization and Total Number of listed Equities have a joint and individual significant effect on Economic Growth (Gross Domestic Product) with Total Number of listed Equities having a negative (opposite) linear relationship with the Gross Domestic Product. The Durbin-Watson statistics (R^{2} = 0.9910 < DW = 1.3686) suggest that the model is not spurious and it is devoid of positive and negative autocorrelation (DW = 1.3686 > d_{l} = 1.07 and DW = 1.5033 < 4 - d_{u} = 2.17) . Therefore , it can produce meaningful result when used for forecasting a positive relationship between gross domestic product, all share index and market capitalization with a 99.1% R-square value. Significant Positive connection between all share index, market capitalization, the number of equities and gross domestic product suggests that government policies and bills aimed towards rapid development of the capital market should be initiated.
Capital Market is a financial market involving institutions that deal with securities with a life of more than one year. The Nigerian Capital Market of Nigerian Stock Exchange is a major player in the market for long-term funds. The instruments or securities traded in the capital market are known as capital market instruments. However, the capital market has both securities based segment (i.e. the stock exchange) and non-securities based segment (market for long term loans) [
The data for this study was extracted from Central Bank of Nigeria Annual reports and Statistical Bulletin (Various Issues) from the National Bureau of Statistics. The time series data cover a period of 1961 to 2017. In an attempt to investigate the impact of the Nigerian stock market on (all share index, market capitalization, and number of equities) Nigerian economy the following models were employed;
The model is specified based on Demirguc-Kunt and Levine (1996) theory on the relationship between stock market earning and economic growth [
Y 1 = f ( X 1 , X 2 , . . . , X k , e ) (1)
where; Y_{1} is Dependent variable, X_{1}, X_{2}, …, X_{k} are the Independent variables, e is the error term. Thus, the specific multiple linear regression model is formulated as:
GDP t = f ( MC t , TR t , ASI t , MCR t ,NOD t , VOT t , VR t ,TNL t ) (2)
The model be explicitly stated as:
GDP t = β 0 + β 1 MC t + β 2 ASI t + β 3 TR t + β 4 MCR t + β 5 NOD t + β 6 VOT t + β 7 VR t + β 8 TNL t + e t t (3)
On taking natural logarithm of the variables to fit the model, the resulting estimation equation is given as:
log GDP t = β 1 log MC t + β 2 log ASI t + β 3 log TR t + β 4 log MCR t + β 5 log NOD t + β 6 log ( VOT t − 1 ) + β 7 log VR t − + β 8 log TNL t + e t t (4)
where the priori expectation is β_{1} > β_{2} > β_{3} > β_{4} > β_{5} β_{6} > β_{7} > β_{8} > 0.
GDP, ASI, MC, MCR, TR, VR, NOD represents Gross Domestic Product, All Share Index, Market Capitalization, Market Capitalization Ratio, Turnover Ratio, Total Value of Shares Traded Ratio, Total Number of Deal, Value of Transaction, Total number of listed equities respectively.
An augmented dickey-fuller test is a test for a unit root in a time series sample [
Testing Procedure
H_{0}: γ = 0; H_{1}: γ < 0
DF T = γ ^ SE ( γ ^ ) (5)
Once a value for the test statistic above, is computed it can be compared to the relevant critical value for the Dickey-Fuller Test. If the test statistic is less (this test is non-symmetrical so we do not consider an absolute value) than the (larger negative) critical value, then the null hypothesis of γ = 0 is rejected and no unit root is present [
The Breusch-Godfrey test is based on the idea of Lagrange multiplier testing, it is sometimes referred to as LM test for serial correlation [
Consider a linear regression of any form, for example
Y t = α 0 + α 1 X t , 1 + α 2 X t , 2 + u t (6)
where the residuals might follow an AR ( p ) autoregressive scheme, as follows:
u t = p 1 u t − 1 + p 2 u t − 2 + … + p p u t − p + ε t (7)
Breusch and Godfrey proved that, if the following auxiliary regression model is fitted
u ^ t = α 0 + α 1 X t 1 + α 2 X t 2 + p 1 u t − 1 + p 2 u t − 2 + ε t (8)
And if the usual R 2 statistic is calculated for this model, then the following asymptotic approximation can be used for the distribution of the test statistic [
n R 2 ~ X p 2 (9)
when the null hypothesis H 0 : { p i = 0 foralli } holds (that is, there is no serial correlation of any order up to p). Here n is the number of data-points available for the second regression, that for u ^ t
n = T − p (10)
where T is the number of observations in the basic series. Note that the value of n depends on the number of lags of the error term (p).
Where n is the number of observations and k is the number of regressors when examining residuals to an equation.
JB = n − k 6 ( S 2 + 1 4 ( C − 3 ) 2 ) (11)
LM = [ ∂ l ∂ θ ] ! [ − E [ ∂ 2 l δ θ ( δ θ ) ! ] ] − 1 [ ∂ l ∂ θ ] ~ X p − 1 2 (12)
Under the null hypothesis of Homoscedasticity.
1) Statement of Hypothesis
H_{o}: There is unit root in the series.
H_{1}: There is no unit root in the series (the series are stationary)
2) Decision Rule
Reject Null Hypothesis if the p-value is less than the level of significance (Figures 1-9).
From
The descriptive statistics
The correlation matrix shows the nature and strength of the linear association or relationship between all the variables entered [
From
Group unit root test: Summary | ||||
---|---|---|---|---|
Series: ASI, GDP, MC, NOD, MCR, TNL, TR, VOT, VR | ||||
Sample: 1961 2015 | ||||
Exogenous variables: Individual effects | ||||
Automatic selection of maximum lags | ||||
Automatic lag length selection based on SIC: 0 to 10 | ||||
Newey-West automatic bandwidth selection and Bartlett kernel | ||||
Method | Statistic | Prob.** | Cross-Sections | Obs |
Null: Unit root (assumes common unit root process) | ||||
Levin, Lin & Chu t* | 5.67259 | 1.0000 | 9 | 376 |
Null: Unit root (assumes individual unit root process) | ||||
Im, Pesaran and Shin W-stat | −9.12436 | 0.0000 | 9 | 376 |
ADF-Fisher Chi-square | 214.151 | 0.0000 | 9 | 376 |
PP-Fisher Chi-square | 294.143 | 0.0000 | 9 | 404 |
**Probabilities for Fisher tests are computed using an asymptotic Chi-square distribution. All other tests assume asymptotic normality.
ASI | GDP | MC | NOD | MCR | TNL | TR | VOT | VR | |
---|---|---|---|---|---|---|---|---|---|
Mean | 14298.43 | 15123.82 | 3855.149 | 749285.0 | 0.165418 | 257.8333 | 63.30438 | 355040.8 | 13.35541 |
Median | 7551.550 | 3888.050 | 386.1500 | 190016.0 | 0.104411 | 264.0000 | 60.89449 | 21112.55 | 6.674824 |
Maximum | 57990.20 | 80222.13 | 19077.42 | 3535631. | 0.638113 | 310.0000 | 175.5881 | 2350876. | 69.11109 |
Minimum | 127.3000 | 67.90000 | 6.600000 | 20525.00 | 0.058581 | 192.0000 | 10.19290 | 225.4000 | 0.775713 |
Std. Dev. | 15049.24 | 22708.33 | 5822.270 | 994532.3 | 0.126874 | 30.16173 | 38.05071 | 588414.2 | 15.91670 |
Skewness | 1.040999 | 1.745152 | 1.358914 | 1.464166 | 2.013925 | -0.72285 | 0.649929 | 1.906407 | 1.984217 |
Kurtosis | 3.481675 | 4.859729 | 3.474663 | 4.259655 | 7.564662 | 2.968790 | 3.732958 | 6.098016 | 6.879386 |
JarqueBera | 5.708408 | 19.55101 | 9.514861 | 12.70232 | 46.32464 | 2.613824 | 2.783575 | 30.16907 | 38.49762 |
Probability | 0.057602 | 0.000057 | 0.008588 | 0.001745 | 0.000000 | 0.270655 | 0.248630 | 0.000000 | 0.000000 |
Sum | 428952.8 | 453714.5 | 115654.5 | 22478550 | 4.962548 | 7735.000 | 1899.131 | 10651223 | 400.6622 |
SumSq.Dev | 6.57E+09 | 1.50E+10 | 9.83E+08 | 2.87E+13 | 0.466815 | 26382.17 | 41987.84 | 1.00E+13 | 7346.902 |
Obs | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
ASI | GDP | MC | NOD | MCR | TNL | TR | VOT | VR | |
---|---|---|---|---|---|---|---|---|---|
ASI | 1.000000 | 0.706603 | 0.846723 | 0.873031 | 0.908835 | 0.004468 | 0.655509 | 0.809969 | 0.819825 |
GDP | 0.706603 | 1.000000 | 0.942002 | 0.656189 | 0.485947 | −0.604801 | 0.427905 | 0.824907 | 0.438062 |
MC | 0.846723 | 0.942002 | 1.000000 | 0.823674 | 0.721172 | −0.413788 | 0.518279 | 0.923671 | 0.653361 |
NOD | 0.873031 | 0.656189 | 0.823674 | 1.000000 | 0.866097 | 0.014404 | 0.782894 | 0.924371 | 0.939214 |
MCR | 0.908835 | 0.485947 | 0.721172 | 0.866097 | 1.000000 | 0.203256 | 0.617928 | 0.710672 | 0.899938 |
TNL | 0.004468 | −0.604801 | −0.413788 | 0.014404 | 0.203256 | 1.000000 | 0.043691 | −0.263364 | 0.242926 |
TR | 0.655509 | 0.427905 | 0.518279 | 0.782894 | 0.617928 | 0.043691 | 1.000000 | 0.668873 | 0.825388 |
VOT | 0.809969 | 0.824907 | 0.923671 | 0.924371 | 0.710672 | −0.263364 | 0.668873 | 1.000000 | 0.783735 |
VR | 0.819825 | 0.438062 | 0.653361 | 0.939214 | 0.899938 | 0.242926 | 0.825388 | 0.783735 | 1.000000 |
Dependent Variable: LOG (GDP) | ||||
---|---|---|---|---|
Sample (adjusted): 1985 2015 | ||||
Included observations: 30 after adjustments | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 11.14131 | 2.068004 | 5.387471 | 0.0000 |
LOG (ASI) | 0.516532 | 0.103574 | 4.987065 | 0.0000 |
LOG (MC) | 0.438354 | 0.072694 | 6.030117 | 0.0000 |
LOG (TNL) | −1.826293 | 0.413947 | −4.411904 | 0.0002 |
R-squared | 0.991091 | Mean dependent var | 8.071192 | |
Adjusted R-squared | 0.990063 | S.D. dependent var | 2.195769 | |
S.E. of regression | 0.218882 | Akaike info criterion | −0.077006 | |
Sum squared resid | 1.245637 | Schwarz criterion | 0.109820 | |
Log likelihood | 5.155096 | Hannan-Quinn criter. | −0.017239 | |
F-statistic | 964.1522 | Durbin-Watson stat | 1.368608 | |
Prob (F-statistic) | 0.000000 |
Equities having a negative (opposite) linear relationship with the Gross Domestic Product. R-square supposes that All Share Index, Market Capitalization, and Total Number Of Listed Equity explains the variation in Gross Domestic Product by 99.10% while adjusted R-square gives the percentage of variation (99%) explained by only those independent variable that in reality affects the dependent variable. The Durbin-Watson statistics (R^{2} = 0.9910 < DW = 1.3686) suggest that the model is not spurious and it is devoid of positive and negative autocorrelation (DW = 1.3686 > d_{l} = 1.07 and DW = 1.5033 < 4 − d_{u} =2.17) therefore can produce meaningful result when used for forecasting.
From
1) Statement of Hypothesis:
H_{o}: Residuals are Normally Distributed
H_{1}: Residuals are not Normally Distributed.
2) Decision Rule:
Reject Null Hypothesis if the p-value is less than the level of significance (5%).
From
The standardized residual graph in
Model | Sum of Squares | Df | Mean Square | F | Sig. | |
---|---|---|---|---|---|---|
1 | Regression | 26.137 | 3 | 8.712 | 964.152 | 0.000^{b} |
Residual | 0.235 | 26 | 0.009 | |||
Total | 26.372 | 29 |
a. Dependent Variable: GDP; b. Predictors: (Constant), ASI, TNL, MC.
that there is no potential outlier in the observations that will distort the relationships and significant tests.
1) Statement of Hypothesis:
H_{o}: Residuals are not serially correlated
H_{1}: Residuals are serially correlated
2) Decision Rule:
Reject Null Hypothesis if the p-value is less than the level of significance (5%).
From
1) Statement of Hypothesis:
Null Hypothesis: Residuals are not Heteroscedastic.
Alternative Hypothesis: Residuals are Heteroscedastic.
2) Decision Rule:
Reject Null Hypothesis if the p-value is less than the level of significance (5%).
From Tables 7-9, we conclude that the residuals are homoscedastic (i.e. the variance of error or probability distribution of error is the same across all the levels of the independent variables) at 5% level of significance.
This study attempted to assess the impact of Nigerian All Share Index, Market
Breusch-Godfrey Serial Correlation LM Test: | ||||
---|---|---|---|---|
F-statistic | 1.396825 | Prob. F(2.24) | 0.2668 | |
Obs*R-squared | 3.127961 | Prob. Chi-Square(2) | 0.2093 | |
Sample: 1985 2015 | ||||
Included observations: 30 | ||||
Presample missing value lagged residuals set to zero. | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | 0.282962 | 2.278287 | 0.124199 | 0.9022 |
LOG (ASI) | 0.014903 | 0.119559 | 0.124650 | 0.9018 |
LOG (MC) | −0.009399 | 0.083254 | −0.112900 | 0.9110 |
LOG (TNL) | −0.063450 | 0.469886 | −0.135033 | 0.8937 |
RESID (−1) | 0.296479 | 0.207199 | 1.430889 | 0.1654 |
RESID (−2) | −0.239630 | 0.232319 | −1.031469 | 0.3126 |
R-squared | 0.104265 | Mean dependent var | 4.12E-16 | |
Adjusted R-squared | −0.082346 | S.D. dependent var | 0.207251 | |
S.E. of regression | 0.215615 | Akaike info criterion | −0.053784 | |
Sum squared resid | 1.115760 | Schwarz criterion | 0.226455 | |
Log likelihood | 6.806762 | Hannan-Quinn criter. | 0.035867 | |
F-statistic | 0.558730 | Durbin-Watson stat | 1.809616 | |
Prob (F-statistic) | 0.730397 |
Heteroskedasticity Test: Breusch-Pagan-Godfrey | ||||
---|---|---|---|---|
F-statistic | 2.054522 | Prob. F (3.26) | 0.1308 | |
Obs*R-squared | 5.748958 | Prob. Chi-Square (3) | 0.1245 | |
Scaled explained SS | 5.618181 | Prob. Chi-Square (3) | 0.1317 | |
Sample: 1985 2015 | ||||
Included observations: 30 | ||||
Variable | Coefficient | Std. Error | t-Statistic | Prob. |
C | −0.885524 | 0.611163 | −1.448916 | 0.1593 |
LOG (ASI) | −0.068391 | 0.030610 | −2.234313 | 0.0343 |
LOG (MC) | 0.043400 | 0.021484 | 2.020162 | 0.0538 |
LOG (TNL) | 0.224843 | 0.122335 | 1.837927 | 0.0775 |
R-squared | 0.191632 | Mean dependent var | 0.041521 | |
Adjusted R-squared | 0.098359 | S.D. dependent var | 0.068124 | |
S.E. of regression | 0.064687 | Akaike info criterion | −2.514956 | |
Sum squared resid | 0.108794 | Schwarz criterion | −2.328130 | |
Log likelihood | 41.72434 | Hannan-Quinn criter. | −2.455189 | |
F-statistic | 2.054522 | Durbin-Watson stat | 2.205782 | |
Prob (F-statistic) | 0.130840 |
obs | Actual | Fitted | Residual | Residual Plot |
---|---|---|---|---|
1985 | 4.21804 | 4.62157 | −0.40353 | | * . | . | |
1986 | 4.23555 | 4.60596 | −0.37041 | | * . | . | |
1987 | 4.65586 | 4.73692 | −0.08106 | | . * | . | |
1988 | 4.93519 | 4.86203 | 0.07316 | | . | * . | |
1989 | 5.37898 | 5.04292 | 0.33605 | | . | . * | |
1990 | 5.58912 | 5.20285 | 0.38627 | | . | . * | |
1991 | 5.74332 | 5.95776 | −0.21444 | | * | . | |
1992 | 6.27777 | 6.17920 | 0.09857 | | . | * . | |
1993 | 6.52781 | 6.38822 | 0.13959 | | . | * . | |
1994 | 6.80228 | 6.69186 | 0.11042 | | . | * . | |
1995 | 7.56693 | 7.56298 | 0.00395 | | . * . | |
1996 | 7.90201 | 7.92845 | −0.02644 | | . *| . | |
1997 | 7.93809 | 7.96116 | −0.02307 | | . *| . | |
1998 | 7.90411 | 7.86450 | 0.03961 | | . |* . | |
1999 | 8.06903 | 7.85702 | 0.21201 | | . | * | |
2000 | 8.42991 | 8.33438 | 0.09553 | | . | * . | |
2001 | 8.46064 | 8.63135 | −0.17071 | | .* | . | |
2002 | 8.84107 | 8.76804 | 0.07303 | | . | * . | |
2003 | 9.04629 | 9.23248 | −0.18619 | | .* | . | |
2004 | 9.34234 | 9.43237 | −0.09002 | | . * | . | |
2005 | 9.58687 | 9.50534 | 0.08153 | | . | * . | |
2006 | 9.82901 | 9.92019 | −0.09118 | | . * | . | |
2007 | 9.93582 | 10.4885 | −0.55264 | |* . | . | |
2008 | 10.0981 | 10.0856 | 0.01253 | | . * . | |
---|---|---|---|---|
2009 | 10.1184 | 9.97046 | 0.14791 | | . | * . | |
2010 | 10.2821 | 10.2177 | 0.06437 | | . |* . | |
2011 | 10.9005 | 10.6483 | 0.25220 | | . | * | |
2012 | 11.0550 | 11.0396 | 0.01541 | | . * . | |
2013 | 11.1731 | 11.2759 | −0.10289 | | . * | . | |
2014 | 11.2926 | 11.3001 | 0.17043 | | . | *. | |
2015 | 11.3558 | 11.4058 | 0.01541 | | . * . | |
2016 | 11.5987 | 11.7720 | −0.10289 | | . * | . | |
2017 | 11.9920 | 11.1221 | 0.17043 | | . | *. | |
Estimation Command: | LS LOG (GDP) C LOG (ASI) LOG (MC) LOG (TNL) |
---|---|
Estimation Equation: | LOG (GDP) = C (1) + C (2) × LOG(ASI) + C (3) × LOG (MC) + C (4) × LOG (TNL) |
Substituted Coefficients: | LOG (GDP) = 11.1413093538 + 0.516531501174 × LOG (ASI) + 0.43835431997 × LOG (MC) − 1.82629256192 × LOG (TNL) |
Capitalization, and Total Number of listed Equities on the Stock market on Gross domestic product (economic growth) between the period of 1961 and 2017, and notable stock market variables were employed, and the connection between stock market and economic growth was found to be positive. The Nigerian stock exchange is undoubtedly one of the most important contributors to the Nigerian economy. That the stock market promotes economic growth is not in doubt. The Capital market serves as an important mechanism for effective and efficient mobilization and allocation of saving, a crucial function for an economy desirous of growth. We conclude that the Nigerian Capital Market contributes positively to Economic Growth. The result suggests that for a significant growth in the economy as to be contributed by the capital market, the focus of policy should be on measure to promote growth in the stock market. Thus, we recommend that:
1) The collective effort of all stakeholders with the Federal Government leads and creates the positive environment. Also, the oversight function of this Honourable House of Representative will surely provide the required investor’s confidence which will positively impact on the market. We should all work hard to ensure that our market is brought back to life by pursuing genuine measures geared towards achieving a robust stock market.
2) The regulatory authority should initiate policies and laws that would encourage more companies and the public to access the market to ensure effective and efficient functioning of the capital market.
3) Securities and Exchange Commission should be more proactive in their surveillance role in order to check sharp practices which undermine market integrity and discourage investors from the capital market.
4) Investment education should be encouraged in all facet of the population and should also be included in curriculum of higher institutions so that investors won’t go in and out of the capital market blindly.
5) The funds raised by government in the form of government securities in the capital market should be put into productive sectors of the economy that will necessitate to growth in all facets of the economy.
6) Abolition of VAT on capital market transactions: VAT should NOT be imposed on capital market investments in any form; it is a disincentive to investment. Taxes should be on consumption. Hence, any form of tax including stamp duties should be removed on listed securities. The governments of Ghana, Zambia etc. have done away with VAT on listed securities to encourage new stock market Listings and Government earned more revenues because Listed companies PAY APPROPRIATE TAX, unlike many private companies.
7) Privatization: Government must ensure that its Privatization programme remains on course to kick-start the market; BPE should be energized to perform to expectation.
8) Regulatory Oversight: sound and effective corporate governance; the regulatory authorities of the Nigerian Capital Market and of the whole financial system must ensure that the approved code of corporate governance is adhered to by all entities under their supervision. To guard against market abuses and insider trading, the monitoring units of these agencies must be strengthened and well equipped to perform their functions. Also, SEC (Securities and Exchange Commission) must not ignore its Developmental functions to grow the market; this function must not be left for the stock exchange and market operators alone… for you must bake the cake before you can eat it.
9) Federal Government should Fund SEC 100% SEC as government regulator of the Capital Market should be fully funded by the Federal Government. At the moment, SEC is partly dependent on the market fees and penalties collected from the market operators. This may have the tendency of compromising its regulatory functions.
10) Mergers of Stockbroking Firms; Stock broking firms should be encouraged to come together, either through merger or outright acquisition. This will make them stronger and more viable and it will enhance good corporate governance and professionalism in the affected entities. As at today many of the surviving stockbroking firms that are too weak financially to stand alone may be allowed to practice as Broker/Dealer only without Portfolio Management.
11) Dematerialization: e-dividends, e-certificates; this means the conversion of share certificates from paper form into electronic format as in the CSCS―the Clearing House of the Nigerian Stock Exchange. A specific time frame (3 - 6 months) when the market will be fully dematerialized should be announced by SEC, NSE and Registrars. Same goes for dividend payments.
12) Unclaimed Dividends/Unclaimed Certificates; A large portion of Unclaimed Dividends and Certificates emanated from the 1972 and 1977 indigenization when photocopying machines were not available for people to keep track of their signatures. A lot of those unclaimed instruments are Statute Barred (12 years). There is absolutely no need to establish a new inefficient parastatal for unclaimed dividend. The Law in CAMA is that after 12 years, the money should be utilized by the company concerned to create more wealth for shareholders. In practice, if the beneficiaries of a late investor appear, The Stock Exchange always persuades the company to pay.
13) A strong Government Bail-out as obtained in USA, Britain, Russia, Singapore etc. is the magic wand needed. Asset Management Corporation of Nigeria (AMCON) was set up by CBN to buy these toxic assets (Margin Loans) with the hope of divesting when the market picks up. However, the modus operandi of AMCON in this respect seems unconcerned as far as market operators and shareholders are concerned.
14) Appointment of Market Makers and their Fund Providers; in April 2010, The Nigerian Stock Exchange appointed market makers who would provide market liquidity and stock-lending. The market makers could not take off in 2010 because the CBN did not approve their proposed Fund Providers (Deposit Money Banks). Now that the NSE has re-appointed them, investors need to know more details in this area of market markers recently appointed. What securities are they making market on? Are the selected market markers well-funded to undertake this role of buyer and seller of last resort? Have their Fund Providers been approved by the Regulator? How much money is the Transaction Float? Certainly this policy will encourage new investors, especially the retail investors. This is a quick-win solution…if properly implemented.
15) Listing of Upstream Oil Companies/Telecom Companies; the Federal Government should encourage the Upstream Oil companies and the major Telecoms companies to list on the Daily official list of the Nigerian Stock Exchange. However, the Government should induce them by introducing tax holidays, and other incentives such as Government contracts to make listing attractive to them. The truth is that all these companies are listed in their home countries; why are they refusing to list in Nigeria? In addition, more indigenous quotable companies should be encouraged to seek listing, by giving those incentives like tax holidays, tax rebate and other incentives. This will boost the economy by generating more jobs and government will get more tax revenue. Furthermore, their listing will enhance transparency of financial disclosure in their operations. One incentive that never fails is a policy of Government that ONLY Companies Quoted/Listed on the local Stock Exchange can get Government contracts above certain amount (N2Billion Naira.).
Maxwell, O., Happiness, O.-I., Alice, U.C. and Chinedu, I.U. (2018) An Empirical Assessment of the Impact of Nigerian all Share Index, Market Capitalization, and Number of Equities on Gross Domestic Product. Open Journal of Statistics, 8, 584-602. https://doi.org/10.4236/ojs.2018.83038