The Response of Stock Price Movements to Dividend Payments on the Ghana Stock Market: An Empirical Assessment.

by Prof.Joseph Magnus FRIMPONG

Department of Accounting and Finance, Kwame Nkrumah University of Science and Technology, School of Business

And

Mr. Gideon BOAKO

Department of Accounting and Finance, Garden City University College, School of Business

ABSTRACT

The signaling hypothesis posits that dividend change announcements are positively correlated with share price movements and future changes in earnings. However, Miller and Modigliani (1961) contend that, dividend policy is irrelevant in arriving at a firm value, if the capital market is perfect. The purpose of this paper is to assess the potency of the dividend irrelevance theory on the Ghana stock market by using the Johansen cointegration methodology on daily data of dividends, earnings and stock prices from January 2011 to December 2013. The results establish that equity price movements in Ghana are not in sync with dividend payments. However, the incorporation of earnings in the cointegration model provides varying results. The findings indicate that equity price movements in Ghana are not responsive to dividend news. The paper presents critical policy implications for capital structure decisions of firms listed on the Ghana stock exchange.

Keywords: Composite Index, dividend irrelevance theory, Johansen cointegration, equity prices.

Correspondence author: Gideon Boako – Department of Accounting and Finance, Garden City University College, School of Business. P.O BOX UP 745, KNUST-Kumasi, E-mail: gboako@aol.com / gboako@gcuc.edu.gh Tel: +233 242 13 75 23.

1.0 Introduction

Generally, investors purchase common stocks with the objective of earning dividend income or realizing capital gains from share price appreciations. And how much an investor intends to pay for a stock is a function of the utility that the investor anticipates to get from the stock. In well efficient capital markets prices of stocks reflect all available information whether public or private. Thus, company specific information about earnings; dividends, etc. are factored into the pricing of stocks barring the possibility of information asymmetry and any other factors that may constitute barriers to trading on the stock exchange. The dividend valuation model suggests that the price of a stock is the present value of all expected future cash flows (dividends). This implies that the pricing of a stock and investors’ choice to purchase is influenced by the kind of dividend pay-out policy adopted by the issuing firm.

During the past few years, the Ghana stock market performance has been very impressive. The equity market in 2013 experienced an outstanding performance of listed firms since its establishment in 1990. The GSE Composite Index (CI), which measures the performance of the entire market, went up by 78.81%, obviously one of the best in Africa between 2010 to 2013. The Ghanaian bourse’s first ten months in year 2013 indicated a bullish performance in capital market activity with the GSE-CI closing the month October at 2,099.90 (or a year-to-date rate of return of 75.3 percent). Compared to an opening index of 992.25 in January 2011, this represents a substantial rise in the Ghana Stock Exchange (GSE) over a relatively short period of time. The exceptional 2013 performance was buoyed largely by increased investor awareness and good operating results of many of the listed companies supported by the renewed investor confidence in the Ghanaian market and economy (Bank of Ghana, 2013).

Even though tests on the dividend irrelevance model appear conventional (See Fama et al., 1969; De Bondt et al., 1985; Aberatna and Power, 2002), not much has been done in emerging and developing markets. In emerging African markets, the few studies conducted have produced mixed results (See Omole, 1997; Osei, 2002; Adelegun, 2004). For an embryonic market like Ghana, available literatures appear unclear about the possible responsiveness of stock price movements to dividend payments. A quick scan through the literatures reveals Asamoah (2010) and Eleke-Aboagye and Opoku (2013). These papers tested the efficiency of company specific information in the determination of prices of shares of some individual listed companies on the Ghana stock market (without using the overall performance of the market), using the event study methodology. Whiles Eleke-Aboagye and Opoku (2013) used 36 listed equities, Asamoah (2010) used just 3 equities. Their results however, may not be reflective of the overall investor sentiments about the relevance of some fundamental factors such as dividends or earnings in their choice and pricing of stocks on the Ghana equity market. This paper addresses the problems inherent in the dearth of extant literature by using the composite performance of the stock market to test the dividend irrelevance theory in Ghana. Using the composite performance for related studies allows for a more concrete and collective conclusion to be drawn for the market other than when individual equities are analyzed. Another, novelty of this paper lies in the methodology employed. Most importantly, the use of the Johansen cointegration which have either not been used before or have not seen much application in the literature. To the best of our knowledge, this is the first time this methodology is being applied in a related study in Ghana. Altering the methodological approach in related studies has the significant consequences of producing relevantly new results. The advantage of the cointegration methodology to the event study methodology is that, the former allows for the inclusion of appropriate lags in the model. This is important because of the time delays in the production of information concerning the variables in consideration. Particularly, the transmission and incorporation of information into stock prices are not instantaneous (as the event study methodology posits). This may be because reporting delays may create a lag between the observations of data concerning stock prices or the incorporation of that information into stock prices.

According to the dividend signaling hypothesis, dividend change announcements trigger share price increases because they convey information about management’s assessment of firms’ future prospects. However, Miller and Modigliani (1961) sustains that, dividend policy is irrelevant in arriving at a firm value, if the capital market is perfect. Thus, in a world of frictionless markets, dividend payout policies do not affect the market value (price) of the firm; and that the firm derives its value solely from the intrinsic profitability of its assets and the competence of its management team. Even though, the Ghana stock market is imperfect (Frimpong and Oteng-Abayie, 2008), assessing whether dividend payments affect the valuation of shares in such a market enables us to ascertain with precision under what conditions dividend policy will matter in capital structure decisions of firms in a market with frictions such as transactions cost, taxes, asymmetric information, and other market imperfections. The beckoning question then is; does the behavior of the Ghana stock market follow the dividend signaling theory or the Miller and Modigliani (1961) hypothesis? This study seeks to answer the question by empirically testing for stock price responsiveness to key fundamental variables. This issue is important due to its recognizable implications for risk diversification, asset pricing, academic research, and efficient allocation of investment resources. The finding of the paper also throws more light on the efficiency level of the Ghana stock market, and corroborates the empirical findings of Frimpong and Boako (2014) .

Equity prices may be considered non-responsive to dividend payments when the price movements show systematic departures from corresponding dividends. Such departures may be due to mispricing or speculative bubbles that drive prices away from fundamental values (e.g. dividends). The notion that dividends are irrelevant in determining the value or price of a firm appears to be a contradiction. After all, the discounted cash flow model and the rational valuation formula, asserts that the fundamental price of an asset is the present value of all future cash flows associated with that security. Continuous departure of ex-post stock prices from fundamental values can be explained by the presence of rational expectations (RE) in stock prices. Rational expectations are characterized by the fact that positive abnormal returns are persistent and increasing due to the self-fulfilling beliefs of market participants, causing stock prices to diverge from their fundamental values (Barberis, 2011). This assumption is usually motivated by Kahneman and Tversky (1974)’s representativeness heuristics. According to this heuristics, people expect even small samples of data to reflect the properties of the parent population. As a result, they draw overly strong inferences from these small samples and this leads to over-extrapolation of asset prices.

There are several traditional methods to detect the divergence of stock prices movements from fundamental values, such as, the present value model (PVM), variance bounds test (VBT), Phillip/Wu/Yu and West’s two tests, etc. However, these methods have crucial shortcomings . Commonly employed methods compare actual prices to fundamentals, which are believed to determine price, using traditional unit root and cointegration tests. For instance, Shiller (1981), West (1987) and Rangel and Pillay (2007) find evidence of departure after comparing stock prices to dividends. Cointegration implies that stock prices and fundamental variables (e.g. dividend) determining asset prices are attracted to each other in the long-run, if they follow integrated processes of order 1 and the transversality condition holds (Campbell and Shiller, 1987).

Some studies (see for example: Horvath-Watson, 1995 etc.) have applied the unit roots and cointegration techniques to examine possible stock price divergence from their fundamental values. While some of the prior studies show consistent results others produce results of varying nature (see for example: Froot & Obstfeld, 1991). For instance, using the Dickey-Fuller stationarity test for the S&P 500 series, Diba and Grossman (1998a) found both dividend and price to be non-stationary at first difference, signifying a lack of evidence in support of stock price departures from their fundamental values. A follow-up test using cointegration revealed that both prices and dividends cointegrated. A similar conclusion was arrived at by Campbell and Shiller (1987) except that they opined the results are dependent on the discount factor used. Diba and Grossman (1998a) theorized that if stock prices and dividends are linearly cointegrated, then rational expectations (bubbles) are absent, and that actual prices are in line with their fundamental values.

In a related development, Blancard and Raymond (2004) show no cointegration between prices and dividends. Their results do not change when an additional earnings fundamental variable is included; however, it is inconsistent with Lee (1996) and Jirasakuldech et al., (2008) who find that prices, dividends and earnings are cointegrated. Moreover, Abeyratna and Power (2002) do not show any significant relationships between dividend change announcements and subsequent share price reactions. A few studies in Ghana (e.g. Asamoah, 2010; and Eleke-Aboagye and Opoku, 2013)using the event study methodology concur in their conclusions that respectively, dividends and earnings announcements do not influence the pricing of stocks in Ghana.

This paper proceeds as follows: Section 2 describes the Euler equation and rational valuation model. Section 3 presents the data and econometric techniques. Section 4 carries out the empirical analysis, and Section 5 concludes the paper and brings out some policy implications.

2.0 The Euler Equation and the Rational Valuation Model

The rational valuation model (RVM) provides a simple framework to measure the effect of dividend income in stock prices. To investigate how the market price of equities may deviate from their fundamental values, Cuthbertson & Nitzsche (2005) and Diba & Grossman (1998b) show that the market prices of assets are determined by future discounted dividends. Their models investigate for bubbles by analyzing the stationarity properties of stock prices and their fundamentals. Their test is based on the assumption that, for the no bubbles hypothesis to be accepted, dividends and unobserved variables, as well as stock prices must be non-stationary at levels and first difference. The Euler equation is given by

〖 P〗_t= 1/((1 +k) ) [P_(t+1) + D_(t+1) ] E_t (1)

where k denotes a constant real rate of return on the asset required by investors, Pt is the stock price at period t, Dt+1 is the dividend for period t and Et denotes the conditional expectation on the information at time t.

Equation (1) can be iterated forward under the rational expectation conditions (RE) to yield

〖 P〗_t= P_t^f= ∑_(i=1)^∞▒1/(1 +k)^i E_t D_(t+1) (2)

In this case it is assumed that the transversality condition holds (i.e. lim [(1/ (1 + k)iEtDt+1)] = 0, as n → ∞. Equation (2) satisfies the discounted dividend model (DDM), which states that the fundamental value of an asset is equal to the present value of all expected dividend payments. The transversality condition ensures a unique price given by equation (2) which is denoted as the fundamental value Pft. And this rules out the possibility of any bubble. The entire class solutions, without imposing the transversality condition is〖 P〗_t^f+ B_t, where pf is the fundamental value andB_t= E_t (B_(t+1)/(1+k)).

Diba & Grossman (1998)’s specification of the actual market price is thus,

〖 P〗_t= ∑_(i=1)^∞▒(1/(1 +k))^i E_t D_(t+i)+ B_t = P_t^f+ B_(t ) (3)

and Bt is the ‘rational bubble’. Thus, the actual market price Pt deviates from its fundamental value Ptf by the amount of the rational bubble Bt. It follows from equation (3) that if the value of the bubble (Bt) exceeds that of the fundamental value (Ptf), the actual price (Pt) can deviate substantially from the fundamental value.

The solution of equation (3) is the sum of the fundamental component and the bubble term. The bubble process then follows a stochastic difference equation,

B_(t+1)- (1+k) B_t= k_(t+1) (4)

The component kt+1 is a random variable and has expected future value of 0. A non-zero kt+1 means stock prices deviate from their fundamentals and the relationship breaks down. If the realization of k is negative, then the deviation will be negative and the negative deviation will increase gradually until it causes the stock price to be negative in the long run. Diba and Grossman (1998b) further theorized that a non-zero kt+1 will yield the following process:

(1-L)^n [1- (1+k)L] B_t= (1-L)^n k_t (5)

where L denotes the lag operator and the bubble process is non-stationary in differences. Even though, Diba and Grossman (1998) employ the Dickey-Fuller test; this paper employs the Augmented Dickey-Fuller (since the latter is a modification of the former) and Phillip-Peron tests for unit roots; and analyzes the autocorrelation patterns (for the obvious reasons as explained in section 3.01).

3.0 Data Sources and Methodology

In this study, we draw upon theoretical propositions and existing empirical work as motivation in selecting our data. Our set of data consists of daily GSE-Composite Index (CI) as a proxy for stock price (Pt) from the Ghana Stock Exchange (GSE) and its corresponding dividend yield (DY) and price earnings ratio (PE) of listed equities of the Exchange from 4 January 2011 to 20 December 2013, excluding non-trading days. This involves 738 observations. We obtain dividends (Dt) and earnings (Yt) from the relation D_t= P_(t-1) X 〖DY〗_t and Y_t= P_(t-1) / 〖PE〗_(t.) respectively. The calculations are done in accordance with prior studies (see, for example, Jirasakuldech et al., 2008; Rangel & Pillay, 2007).

The choice of data period and use of composite indices rather than the All-Share Indices (ASIs) are influenced by two reasons. First, data for dividend yield and price earnings ratio are not available for most parts of the period prior to 2010, except 2009 and 2010. However, these datasets are readily available from 2011 to 2013 . In order to have a large sample size, it is prudent to use the period 2011 to 2013. Using a data period from 2011 to 2013 could not allow us to use the All-Share index (ASI) since the GSE effective from January 2011 no longer calculates ASI but CI. Also, because the composite index relies on the volume weighted average price (VWAP) other than just the day’s closing price (as in the All-Share-Index) in its computation, it is believed the CI reflects the stock market’s performance better than the ASI.

3.01 Unit Root Test

To avoid spurious results, unit root test of augmented Dickey-Fuller (ADF) and Phillip-Peron are performed to determine the time series properties of the data employed in the analysis. The auxiliary regression is run with an intercept and is specified as:

∆y_t= φ_0+ φ_1 y_(t-1)+ ∑_j^n▒〖π_j ∆y_(t-j)+ 〖ε_t〗_ 〗 (6)

where, yt is the variable whose time series properties are being investigated, ∆ is the difference operator, and ε_t is the random error term with t=1 … n assumed to be Gaussian white noise.

The augmentation terms are added to convert the residuals into white noise without affecting the distribution of the statistics under the null hypothesis of a unit root. As noted by Alba (1999), the ADF and PP tests have a null unit root against the alternative of trend stationary. The usefulness of the PP test over the ADF is that the latter allows for the possibility of hetereoskedasticity error terms (Hamilton, 1994). The ADF test adjust the DF test to take care of possible serial correlation in the error terms by adding the lagged difference terms of the regressand. Phillips-Peron (1989) use non-parametric statistical methods to take care of the serial correlation in the error terms without adding lagged difference terms.

3.02 Cointegration Test

Two variables will be cointegrated if they have a long term relationship between them. In order to select the lag length for the cointegration, the VAR lag order selection criterion, based on SIC and AIC is used (though unreported). We examine a bivariate cointegration between prices and dividends (Pt and Dt, respectively) and multivariate cointegration among prices, dividends and earnings (Pt, Dt and Yt, respectively). The use of dividends as a fundamental variable is justified by the Euler equation and RVM (See Cuthbertson and Nitzsche, 2005). Similarly, earnings is included as an additional fundamental variable due to the substantial evidence of earnings as an important determinant of equity pricing. If stock prices and fundamental variables are integrated of order 1 and cointegrated, then it means prices movements are responsiveto fundamental variables. On the other hand, if price series contains explosive bubbles that drive prices away from their fundamental values, then one should expect the absence of cointegration between stock prices and fundamental variables that determine prices.

The Johansen-Juselius (Johansen and Juselius, 1992) multivariate cointegration vector autoregressive approach is used because of its unique applicability of providing estimates of all cointegrating relationships that may exist within a vector of non-stationary variables or a mixture of stationary and non-stationary variables (Gujarati and Porter, 2009). Moreover, the specification of lags helps to overcome the possible time delays in the production of information concerning the variables under consideration.

Following Johansen (1990), a q-dimensional vector autoregression (VAR) of order k[VAR (k)] can be specified as follows:

Z_t=d+ ∏_1 Z_(t-1)+⋯+ ∏_k Z_(t-k)+ φ_t (t=1…T) (7) This expression can be rewritten as,

∆Z=d+ ∏_k Z_(t-k)+ ∑_(i-1)^(k-1)▒〖θ_i ∆Z_(t-i) 〗+ φ_t (8)

where ∆ is the difference operator, ∏ and θ_ are q-by-q matrices of unknown parameters and φ_t is a Gaussian error term. The relationship between stock prices and dividends; and among prices, earnings, and dividends in Ghana is contained in the impact matrix ∏. A full column rank of the matrix ∏ implies that all variables in Zt are stationary. On the other hand, when the matrix ∏ has zero column rank, the expression is a first differenced VAR involving no long-run elements. If the rank of ∏ is however intermediate, it means that 0 ˂ rank (∏) = r ˂ q, there will be r cointegrating vectors that make the linear combinations of Zt become stationary or integrated.

Of the two Johansen cointegration tests, the maximum likelihood equation procedure provides a likelihood ratio test, called a trace test, which evaluates the null hypothesis of, at most, r cointegrating vectors verses the general null of q cointegrating vectors. The next, likelihood ratio test is the maximum eigenvalue test, which evaluates the null hypothesis of r cointegrating vectors against the alternative of (r + 1) cointegrating vectors. The trace test and maximum eigenvalue test equations are shown below:

J_trace= -T∑_(i=r+1)^n▒ln(1- λ ̂_i ) (9)

J_max (r,r+1)= -Tln(1-λ ̂_(r+1) )(10)

4.0 Empirical Analysis

4.01 Descriptive Statistics

To be able to understand fully the overall behavior of the Ghana stock market, we present some stylized evidence of the Ghana stock market composite index, as well as, the two fundamental variables of interest –dividends and earnings. All discussions in this section refer to Table 1.

The Jacque-Bera statistic shown in Table 1 rejects the null hypothesis of normality at a 1% significance level. Even though both dividends and earnings show positive mean growth rates of 0.11% and 0.15% respectively, the level of unsystematic risk associated with the dividend variable is greater as a result of the higher standard deviation of 23.53% compared to 9.97% for earnings. Investors could therefore easily suffer the risk of uncertainty about the prospects of investing in the stock market due to such high standard deviations. This uncertainty could influence investors to either overestimate or underestimate the precision of their forecasts (Daniel et al., 1998) and their actions or inactions could push stock prices to react abnormally to earnings or dividend news.

The positively skewed Pt, Dt, and Yt implies that for the sample period, the Ghana stock market was characterized by many small losses and a few extreme gains. Generally, investors should be attracted by the positive skewness because the mean return falls above the median. This is because relative to the mean return, positive skewness amounts to a limited, though frequent, downside compared with a somewhat unlimited, but less frequent, upside. Also, in the sample period, stock prices, Pt, exhibit leptokurtic features (i.e. being more peaked than normal). This means that, prices on the Ghana stock market have distributions that show a greater percentage of small deviations from the mean return (more small surprises) and a greater percentage of extremely large deviations from the mean return (more big surprises). Most investors would perceive a greater chance of extremely large deviations from the mean as increasing risk.For risk-averse investors, this could dissuade them from purchasing the stock. Again, the Ljung-Box Portmanteau test statistic identifying the presence of twenty-sixth and thirty-sixth-order autocorrelation indicates the existence of temporal significant linear dependencies at 1% significance level. This statistics suggests that departures from fundamental values are found to be more likely when price changes follow the same direction.

The presence of excess kurtosis, skewness, and non-normality of returns implies that stock price movements show systematic departures from their fundamental values (Yanik and Ayturk, 2011; and Nartea et al., 2013).Therefore, the evidence of skewness, excess kurtosis, non-normality and autocorrelation in the dataset, as reported in Table 1, is indicative of the likelihood existence of stock price departures from fundamental values in the Ghana equity market.

Table 1: Summary statistics of stock prices, dividends and earnings

N Mean Std. Dev. Min. Max. Skewness Kurtosis Jacque-Bera

Panel A: Overall sample period

(4th Jan. 2011 to 31st Dec. 2013)

Pt 736 0.1049 0.5719 -2.7054 2.7033 0.3323 7.0367 497.9118*

Dt 735 0.1051 23.5322 -322.206 460.6503 6.0815 261.106 1986308*

Yt 735 0.1534 9.9657 -168.7454 183.2862 2.1409 277.6456 2244593*

Panel B: Autocorrelation of Overall sample period

ρ_1 ρ_2 ρ_3 ρ_4 ρ_5 Q (26) Q (36)

Pt 0.180 0.183 0.130 0.107 0.151 242.97* 307.82*

Dt -0.006 -0.016 -0.001 -0.001 0.007 92.965* 118.92*

Yt -0.053 0.038 0.010 -0.002 -0.001 153.73* 154.32*

Notes: Pt denotes GSE-CI, Dt denotes dividends, and Ytdenotes earnings. Min. and Max. refer to minimum and maximum value, respectively. Asymptotic standard error of coefficient is (6/N)1/2. Jacque-Bera tests statistics test for departure from normality. * indicates significance at 1%.

4.02 Unit Root and Cointegration Results

Following the descriptive statistics, we further examine the time series properties of stock prices, earnings and dividends by looking at unit root and cointegration analysis.

The results in Table 2 indicate that stock prices, earnings, and dividends possess unit roots at 1% significance in their levels. This happens with both trend and constant plus trend. This suggests that all series do not have mean reverting properties, giving an indication thatstock price changes respond to changes in fundamental variables, at their levels. However, consistent with Diba and Grossman (1998a) stock prices and fundamental variables are differenced stationary, rejecting the null hypothesis of unit roots at the 1% significance level. This suggests that stock prices and fundamental variables are realizations of I(0) process. Rangel and Pilay (2007) attribute the possibility of differenced-stationarity to the fact that price deviations from fundamental variables are periodic and not continuous. The typical situation on the Ghana stock market exhibits this behavior as it shows periodic boom and bust cycles over years .

Because results from the unit root tests in Table 2 on the possibility of stock price changes responsiveness to dividend payments on the stock market appear inconsistent at levels and first difference, we proceed to conduct a more robust check using the Johansen cointegration methodology.

Table 2: ADF and PP unit root tests for stock prices, dividends, and earnings

LEVELS

ADF PP

Variable τ_μ τ_τ τ_μ τ_τ

Pt 2.4662(2) -0.0571(2) 1.8641(17) -0.3239(17)

Dt -1.8854(2) -2.2181(2) -2.7346(2) -2.9908(1)

Yt 2.4662(2) -0.0571(2) 1.8641(17) -0.3239(17)

FIRST DIFFERENCE

∆Pt -6.9033(5)* -14.6334(1)* -25.7653(17)* -25.3902(16)*

∆Dt -22.3112(1)* -22.2955(1)* -29.0658(10)* -29.0406(10)*

∆Yt -6.9033(5)* -14.6334(1)* -25.7653(17)* -25.3902(16)*

Notes: * denotes rejection of null hypothesis at the 1% level of significance. The numbers within parenthesis for the ADF statistics represents the lag length of the dependent variable used to obtain white noise residuals. The lag lengths for ADF equation were selected automatically using Schwarz Information Criterion (SIC). The numbers within brackets for the PP statistics represent bandwidth selected automatically using Bartlett kernel based on Newey-West method. ∆ = first difference operator. τ_μandτ_τ are constant and constant & trend, respectively.

4.03 Cointegration Analysis

Given that stock prices, earnings, and dividends are I(0) at first difference, the cointegration hypothesis among the variables is examined using the methodology developed in Johansen (1991) and Johansen (1995) in order to specify the relationship between stock prices and fundamental variables to ascertain the certainty or otherwise of price responsiveness to fundamental variables on the Ghana stock market.

The results in Panel A of Table 3 indicate that the null hypothesis of no cointegrating vector (r = 0) cannot be rejected by both trace statistics and maximum eigenvalue statistics at the 5% significance level. Thus, stock prices and dividends were found to be I (0), and are not cointegrated over the sample period. The results mean that stock prices and dividends do not have any long-run equilibrium relationship. Thus, stock prices do not respond to dividend news in the long term (this is consistent with Blanchard and Raymond, 2004; Rangel and Pilay, 2007; and Asamoah, 2013).

However, the use of earnings, in addition to dividends varies the results, as shown in Panel B. The λ t r a c e and λ m a x test statistics provide evidence of a cointegrated relationship between equity prices and fundamental variables. The null hypothesis of r = 0 is rejected in favour of r = 1 by both λ t r a c e and λ m a x test statistics at the 5% significance level. The result in Panel B is inconsistent with Blanchard and Raymond (2004) but consistent with Lee, 1996; Jirasakuldech et al.,(2002). The inconsistency may arise from methodological differences and also the multivariate regression. It is possible that dividend had a dominant effect on the other variables within the sample period, and perhaps a bivariate coitegration between earnings and stock price may show a different result . Evidence of a cointegrated relationship is indicative of equity price responsiveness to fundamental variables. However, this conclusion should be interpreted with some caution in view of the weaknesses associated with earnings in determining the value of a stock. While companies report total and per-share earnings, these “bottom-line” numbers may include extraordinary items that are nonrecurring. Higher earnings will lower the P/E ratio and perhaps suggest that the stock is undervalued, especially if the average P/E ratio is higher. If the gain is excluded and EPS are lower, the P/E ratio will be higher. The higher P/E ratio may indicate that the stock is not undervalued and investors’ preference for the stock may vary.

Table 3: Results of Johansen Cointegration Test

H0 H1 Eigenvalue λ t r a c e 5% CV λ m a x 5% CV VAR

Statistics Statistics

Panel A: Bivariate cointegration between Pt and Dt

r = 0 r = 1 0.0158 11.9650 15.4947 11.2347 14.2546 4

r ≤ 1 r = 2 0.0010 0.7307 3.8415 0.7307 3.8415

Panel B: Multivariate cointegration among Pt, Dt and Yt

r = 0 r = 1 0.0507 47.9094** 29.7971 37.0169** 21.1316

r≤ 1 r = 2 0.0141 10.8926 15.4947 10.1111 14.2646

r ≤ 2 r = 3 0.0011 0.7815 3.8415 0.7815 3.8415

Notes: VAR is order of the var lag selection. H0 and H1 denote the null and alternative hypothesis and r denotes the number of cointegrating vectors. Both Trace and Max-Eigenvalue test indicate no cointegration between Pt and Dt at the 0.05 level. ** denote significance at 5% significance level signifying 1 cointegration among Pt, Dt and Yt.

Even though, the results in Panel A corroborate the Miller and Modigliani (1961) dividend irrelevance hypothesis, it is somewhat surprising for a nascent and imperfect market like Ghana. The findings show that changes in price movements of stocks of equities listed on the Ghana stock exchange are unaffected by changes in dividends paid by these equities to shareholders in the long term. It can therefore be inferred that Ghanaian equity investors do not overreact to dividend announcements. The results seem to be a general phenomenon in underdeveloped and emerging equity markets as similar results were found for Singapore and Malaysia (Rangel and Pilay, 2007). The phenomenon however, is likely to wane in the future as listed firms take steps to increase and improve their dividend pay-out policies.

For some time now the Ghana stock exchange has been responding to international market norms with greater non-resident foreign investors (NRFIs) participation. For instance, in 2007 the total value traded by NRFIs was GHc422.85 million, which represented about 80% of total volume traded. Similarly, in 2012, a Bank of Ghana (BoG) 3-year fixed rate bond auction of GHc300 million was heavily oversubscribed, with more than 50 percent of the bids coming from offshore investors . With increased cross-listings and listings in the international register by Tullow oil, Golden Star Services Ltd, and Anglogold Ashanti; it is expected that the Ghana stock market will follow the behavior of those in the developed markets. With this, increased and good dividend pay-out policies are expected to increase patronage of shares of listed equities leading to increases in share prices.

A myriad of reasons can be adduced in support of why the findings support the dividend irrelevance theory. One such reason is the fact that most investors in Ghana are passive, naïve, and low liquidity level investors who do not properly understand the operations of the stock market. For them once shares are purchased, they leave the “chips to fall where they may” and make little or no attempt to follow news about the stocks in order to respond appropriately. Moreover, lack of transparency,proper and efficient legal, regulatory and institutional framework are possible channels that may necessitate insider trading which has the potency to erode any significant signals that dividend change announcements must convey to investors for appropriate response.

The interpretation of the findings of this paper and prior studies (example Asamoah, 2010) that stock price changes do not overreact to dividend news appears somewhat acute because there have been periodically very large price changes on the stock market such as the rise in the GSE-ASI from 1018.016 in 2005 to a peak of 10431.64 by December 2008. The possible cause of this, other than dividend payment announcements is partly the “Peso ” problem. Cuthbertson and Nitzsche (2005) explains this as that; suppose investors in the market had information, within a sample period that dividends might increase rapidly in the future, but in the real sense, the event did not occur and dividends increased at their “normal” rate, the stock price would rise substantially (because of rational expectations), but there would only be a moderate increase in dividends. Stock prices would look as if they have overreacted to (current) dividends. This might be the reason accounting for some seasonal jumps and slumps in the prices on the market, other than ex-ante dividends.

5.0 Conclusion, Policy Implications and Recommendations

The goal of this paper is to establish whether or not equity prices in Ghana respond to dividend payments. In order to do this, we employ the general descriptive statistics to test for some descriptive features like skewness, autocorrelation and non-normality of the variables used. We also test for the unit root and cointegrating relationship between stock prices and key fundamental variables (earnings and dividend). The acceptance of the null hypothesis of no cointegration could be construed as evidence of stock price divergence from fundamental factors and vice versa. The paper shows strong evidence in support of equity price deviations from fundamental values in the Ghana equity market, as indicated by the cointegration results between price and dividends. However, the introduction of earnings as an additional determinant of stock price alters the result. We report that the Ghana equity market has return distributions that depict excess kurtosis, skewness, non-normality of returns and autocorrelations.

Results from the cointegration test between price and dividends run athwart the common knowledge about stock prices reaction towards dividend announcements or payments. Generally, prices movements respond to dividend news (as indicated by the signaling theory), but the acceptance of the null hypothesis of no cointegration indicates that prices (or investors) on the equity market do not respond to dividend news or payments, as posited by the dividend irrelevance theory. The results, however, seem to be a general phenomenon in underdeveloped and emerging equity markets as similar results were found for Singapore and Malaysia (see Rangel and Pillay, 2007). This phenomenon may usually occur due to the existence of bubbles, mispricing, market infancy, and inefficiency. In order to avert the occurrence, proper steps must be taken by the Securities and Exchange Commission (SEC) and the government of Ghana to ensure that the Ghana stock market is well integrated with other markets by way of increasing cross-listings to attract investors who are more income oriented and would be driven by dividend pay-out policies. The findings fuel the uncertainty about investor forecasts and valuation of equity prices on the Ghana Stock Exchange.

A critical policy implication of the key finding is its impact on capital structure decisions of firms listed on the Ghana stock exchange. Because prices on the stock market are unaffected by signals from dividend news; listed firms must concentrate on best practices to arrive at optimal capital structure decisions without necessarily adjusting dividends. Quoted firms may therefore consider plowing back dividends without entertaining the fear of sending a wrong signal. Perhaps, as the market becomes more efficient, investors will be responsive to dividend announcements and firms can revise their capital structure decisions through dividend policies. Otherwise, in the current state, there is no need to maintain dividend policy at the expense of optimal capital structure, certeris paribus. The findings may also be indicative of the fact that dividend pay-out policies adopted by the listed firms over the years are unattractive to investors, and therefore, regular review of existing policies for ones that will resonate well with investors is recommended.

Results of this study presents a picture about the entire stock market, and that, individual stocks may show results that are coterminous or dissimilar to that of the overall market. It is therefore recommended for further studies to delve into the assessment of equity prices response to dividend news, and the risk-adjusted performance for individual listed firms.

We further recommend for the following actions to be taken:

Compliance with laws regarding insider trading must be ensured by the Securities and Exchange Commission (SEC) and other relevant regulatory bodies.

To address the liquidity needs of the market, efforts ought to be made to increase participation by non-resident foreign investors and institutional investors. These classes of investors generally have adequate capital and knowledge of the dynamics of stock market investments. Their presence would help improve the quality of information assessment and usage on the market.

We further recommend for the provision of an online trading platform to augment the automation system. It is our considered opinion that this would ease investor participation and frequency of trading, capable of improving the efficiency level of the market.

References

[1] Abeyratna, G., Power, D.M., 2002. The Post Announcement Performance of Dividend – Changing Companies: The Dividend Signaling Theory Hypothesis Revisited. Accounting and Finance No. 42: 131 – 151.

[2] Adelugan, O.J., 2004. How Efficient is the Nigerian Stock Market? Further Evidence. African Review of Money, Finance and Banking: 143-65

[3] Alba, J.D., 1999. Are there Systematic Relationships between China’s and Southeast Asia’s Exchange Rates? Evidence from Daily Data. Asian Economic Journal, Vol. 13, No. 1: 73-92.

[4] Asamoah, G.N., 2010. The Impact of Dividend Announcement on Share Price Behaviour in Ghana. Journal of Business and Economic Research, Vol. 8. No. 4: 47-58

[5] Bank of Ghana Monetary Policy Committee Press Release, Nov. 2013.

[5] Barberis, N., (2011). Psychology and the Financial Crisis of 2007-2008. http:faculty.som.yale.edu/nicholasbarberis/cp.10.pdf

[6] Blancard, G.C., Raymond, H., 2004. Empirical Evidence of Periodically Collapsing Stock Price Bubbles. Applied Economics Letters No. 11: 61 – 69.

[7] Campbell, J.Y., Shiller, R.J., 1987. Cointegration and Tests of Present Value Models. Journal of Political Economy No. 95: 1062 – 1088.

[8] Cuthbertson, K., Nitzsche, D., 2005. Quantitative Financial Economics: Stocks, Bonds & Foreign Exchange (2nd Ed.). Wiley Publications: 397-420.

[9] Daniel, K., Hirshleifer, Subrahmanyam, A.D., 1998. Investor Psychology and Security Market Under and Overreactions. Journal of Finance No. 53: 1839 – 1885.

[10] De Bondt, W.F.M., Thaler, R., 1985. Does the Stock Market Overreact? Journal of Finance, Vol. 40: 793-805.

[11] Diba, B.T, Grossman, H.I. 1998a. The Theory of Rational Bubbles in Stock Prices. Economic Journal No. 98: 746-757.

[12] Diba, B.T., Grossman, H.I., 1998b. Explosive Rational Bubbles in Stock Prices. American Economic Review, No. 78: 520-530.

[13] Eleke-Aboagye, P.G., Opoku, E., 2013. The Effect of Earnings Announcement on Share Prices in Ghana: A Study of Ghana Stock Exchange. Research Journal of Finance and Accounting, ISSN: 2222-1697, Vol. 4. No. 17: 166-186.

[14] Fama, E.F., Fisher, L., Jensen, M.C., Roll, R., (1969). The Adjustment of Stock Prices to the New Information. International Economic Review, Vol. 10, No. 1: 1-21

[15] Frimpong, J.M., Oteng-Abayie, E.F., 2008. Market Returns and Weak-Form Efficiency: The Case of Ghana Stock Exchange: In: Proceedings of the 9th International Conference of the IAADB, PP 23-29, University of Florida, Gainesville, Florida, May 20-24, 2008.

[16] Frimpong, J.M., Boako, G., 2014. Empirical Investigation of Asset Price Bubbles on the Ghana Stock Market: A Parametric Approach. International Research Journal of Finance and Economics. ISSN: 1450-2887, Issue 124(4): 8-19.

[17] Froot, K.A., Obstfeld, M., 1991. Intrinsic Bubbles: The Case of Stock Prices. American Economic Review No. 81: 1189-1214.

[18] Ghana Stock Exchange Annual Report, 2013.

[19] Ghana Stock Exchange Market Report, December 2013.

[20] Gujarati D.N., Dawn C.P., 2009. Basic Econometrics 5th Edition; McGraw-Hill Education (Asia): 699-849.

[21] Hamilton J. D., 1994. Time Series Analysis. Princeton, N.J: Princeton University Press.

[22] HFC Brokerage Weekly Report, 2012. May 18, 2012: 1

[23] Homm, U., Breitung, J., 2012. Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods. Journal of Financial Econometrics: 1-46.

[24] Horvath, M.T., Watson, W., 1995. Testing for Cointegration When Some of the Cointegrating Vectors are Known. Econometric TheoryNo. 11: 952-984.

[25] Jirasakuldech, B., Emekter, R.J., Rao, R.P., 2008. Do Thai Stock Prices Deviate from Fundamental Values? Pacific-Basin Finance Journal, No.16: 298-315.

[26] Johansen, S., 1991. Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, No. 59.

[27] Johansen, S., 1995. Likelihood-Based Inference in Cointegrated Vector Autoregressive Models. Oxford: Oxford University Press.

[28] Johansen, S., and Juselius, K., 1990. The Full Information Maximum Likelihood Procedure for Inference on Cointegration – with Applications to the Demand for Money. Oxford Bulletin of Economics and Statistics. No. 52.

[29] Johansen, S., Juselius, K., 1992. Testing Structural Hypothesis in a Multivariate Cointegration Analysis of the PPP and the UIP for UK. Journal of Econometrics: No. 53.

[30] Kahneman, D., Tversky, A., 1974. Judgment under Uncertainty: Heuristics and Biases. ScienceNo. 185: 1124 – 1131.

[31] Lee, B.S., 1996. Comovements of Earnings, Dividends, and Stock Prices. Journal of Empirical Finance No. 3: 327 – 346.

[32] Miller, M., Modigliani, F., 1961. Dividend Policy, Growth, and the Valuation of Shares. The Journal of Business Vol. 34 No. 4: 411 – 433.

[33] Nartea, G. V., Bo, H., Baiding H., 2013. Are there Rational Speculative Bubbles in the Philippine Stock Market? The Philippine Economic ReviewNo. 1: 45-56.

[34] Omole, D.O., 1997. Efficient Market Hypothesis and the Nigerian Capital Market under Financial Liberalization: An Empirical Analysis. Unpublished PhD. Thesis, University of Ibadan, Nigeria.

[35] Osei, K.A., 2002. Asset Pricing and Information efficiency of the Ghana Stock Exchange. African Economic Research Consortium (AERC), Research Paper No. 115, Kenya.

[36] Peron, P., 1989. Testing for a Unit Root in a Time Series with a Changing Mean. Journal of Business and Economic StatisticsNo. 8: 153-162.

[37] Rangel, G., Pillay, S.S., 2007. Evidence of Bubbles in the Singaporean Stock Market. Singapore Economic Review Conference, 2007.

[38] Shiller, R.J., 1981. Do Stock Prices Move too much to be Justified by Subsequent Changes in Dividends? American Economic ReviewNo. 71: 421 – 436.

[39] West, K.D., 1987. A Specification Test for Speculative Bubbles. Quarterly Journal of EconomicsNo. 102: 553-580.

[40] Yanik, S., Ayturk, Y., 2011. Rational Speculative Bubbles in Istanbul Stock Exchange. Journal of Accounting and Finance: 175-190.