Dividend_Announcement_and_Share_Prices_A-7.pdf

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Dividend Announcement and Share Prices: A Nepalese Evidence
Jeetendra Dangol
jdangol@gmail.com, Jeetendra.dangol@pyc.tu.edu.np
Reference: Dangol, J. (2016). Dividend announcement and share prices: A Nepalese Evidence.
The Business Review, 5, 9-35
Abstract
This paper examines the abnormal returns of dividend announcements in the Nepalese stock
market using the market model of event methodology after adjustment of existing thin-trading
problem. To examine the abnormal returns of dividend announcements, 139 dividend
announcement samples were partitioned into dividend-initiation (good-news), dividend-increase
(good-news), dividend-decrease (bad-news), and no dividend-change (no-news) sub-samples.
The positive abnormal returns were found much higher on the dividend announcement day in the
dividend-initiation and dividend-increase cases. The dividend-decrease sub-sample shows the
highest negative abnormal returns on the dividend announcement day. The no dividend-change
announcements sub-sample shows that the entire 21-days event-window has insignificant
abnormal returns. The percentage of dividend changes is only the influential factor to determine
abnormal returns during the dividend announcement day, whereas the variables such as dividend
yield, size of firm, market-to-book ratio, market conditions and time specification have no
explanatory power on the share prices around the dividend announcement day. The dividend
announcements have a signalling effect in the Nepalese stock market. The study also found that
the Nepalese stock market supported the semi-strong form of market efficiency.
Key words:
Efficient market hypothesis, Dividends announcement, Event methodology, Signalling effect,
Abnormal returns

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Dividend Announcement and Share Prices: A Nepalese Evidence
1. Introduction
One of the major premises of efficient market theory is that the market quickly and correctly
impounds any publicly available information, including macroeconomic information that might
be used to predict stock prices. The term efficiency is used to describe a market in which relevant
information is impounded into the price of financial assets. In general terms, the theory of
efficient markets is concerned with stock prices at any point in time fully reflect available
information (Fama, 1970, 1991).
Over the last four and half decades, the Efficient Market Hypothesis has been one of the studied
topics in the field of finance. The Fama (1970) classifies the market efficiency into Weak form
efficiency, Semi-strong form efficiency and Strong form efficiency. After twenty years of market
efficiency literature published in 1970, Fama (1991) proposed to change the categories of market
efficiency, namely: (1) Using tests for return predictability instead of weak-form tests, (2) Using
event studies instead of semi-strong-form tests and (3) Using test for private information instead
of strong-form tests.
According to Shleifer (2000), the theory of market efficiency is based on the three assumptions.
First, the all investors are rational and valued security price rationally. Second, if some investors
are not rational, their trades are random and cancel each other without affecting prices. Third, if
investors are irrational, the arbitrageurs eliminate their influence on securities prices. So, the
market participants are unable to generate abnormal returns.
Theoretical investigations and empirical studies have been conducted to find rational
justifications for dividend payments, in order to understand their true role in the firm’s valuation.
These justifications have a basis of the main market imperfections, like taxes, agency costs and
information asymmetry. The study is also concerned with the information asymmetry and the
dividend policy. It can refer to the signalling theory and the free cash flow hypothesis. The
signalling theory, associated to the dividend content information hypothesis, holds that dividend
policy acts as a vehicle for transmitting information from firm’s authority to the market. The

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second theory postulates that the dividends work as a vehicle to drain excess cash-flows.
Bhattacharya (1979), John and Williams (1985) and Miller and Rock (1985) developed the
signalling models based on the information asymmetry hypothesis. On the other hand, Jensen
(1986) proposed a theory which is widely known as the free cash flow hypothesis. The theory
predicts that the stock prices will increase (decrease) if there is increase (decrease) in unexpected
dividend payments.
There are various factors that affect stock market price behaviours; they bring out over- or under-
reaction in the market. The study of events and stock price behaviour occupies an important
place in financial management. As such, this study is focused on the independence of stock
returns and the short-run effect on stock price caused by announcement of unanticipated
corporate dividend announcements. Similarly, investors perceive the dividend-announcements in
different ways, viz., as good-news, bad-news and no effect-news.
2. Objectives
The main objective of the study is to test semi-strong form of market efficiency. The study
examines the market reaction that would follow immediately to the new unanticipated dividend
announcements in the context of Nepalese stock market. The specific objectives of the study are
as under:
• To examine the abnormal returns before and after dividend announcements in the
Nepalese stock market.
• To assess the time duration, i.e., speed of price adjustment of market reaction to
announcement of new unanticipated dividend information in the Nepalese stock market.
• To evaluate the abnormal return on the equity shares during the announcement of
changes in the dividends and influence of firm specific variables as well as market trends
and time effects in the Nepalese stock market.
3. Review of Literature
The primary hypothesis for Efficient Market Hypothesis is that the prices accurately and quickly
reflect all available information in such a way that one cannot predict future returns for earning

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abnormal returns. In general terms, the theory of efficient market is concerned with whether
prices at any point in time fully reflect available information (Fama, 1970, 1991).
Dhillon and Johnson (1994) find that the information content hypothesis is consistent with
positive reaction to a dividend increase. It is so because dividend increases are perceived as
good-news by the investors. In context of Nigeria, Adelegan (2003) has provided evidence on
negative excess returns for the dividend paying samples before the day of announcements, and
positive after the announcement date. It indicates that the dividend announcement is positive
(good-news) to investors and increases share prices.
The majority of the empirical tests done on the dividend signalling hypothesis domain explore
the effects of the dividend change announcements on share prices (Pettit, 1972, Aharony &
Swary, 1980, Asquith & Mullins, 1983, Dhillon & Johnson, 1994, Lonie et al., 1996, Viswanath
et al., 2002, Abdullah et al., 2002, McCluskey et al., 2006, Gurgul et al., 2006, Chen et al., 2009,
Dasilas & Leventis, 2011). The results are mixed. Although it is well documented that there is a
strong positive association between dividend changes and share price reactions in the days
surrounding the dividend change announcements (Pettit, 1972, Aharony & Swary, 1980, Asquith
& Mullins, 1983, Dielman & Oppenheirmer, 1984, Impson & Karafiath, 1992, Dasilas &
Leventis, 2011). Their conclusions emphasise on existence of dividend information content, or
signalling effect. Nevertheless, several studies including Benartzi, Michaely and Thaler (1997),
Chen, Firth and Gao (2002) and Abeyratna and Power (2002) have not supported the existence of
a positive relationship between dividend changes and the market reaction.
Similarly, studies have not supported these relations between dividend changes announcement
and stock prices (Chen et al., 2002, Abdullah et al., 2002, Adelegan, 2003, Mallikarjunappa &
Manjunatha, 2009). Some studies also showed that the price adjustment has occurred during the
announcement day, indicating that the market is efficient in semi-strong form and accepting
dividend signalling hypothesis (McCluskey, 2006, Joshipura, 2009). The study deals with
investigation of the semi-strong form of market efficiency including dividend signalling
hypothesis using dividend announcements as a proxy variable.

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However, Mollah (2007) has found that in the Bangladesh stock market, the dividend-signalling
hypothesis was rejected indicating that dividend announcements convey no information. In Saudi
Arabia, Uddin and Osman (2008) have reported that the information signal of dividend
announcements is weak, and the market does not react to dividend announcements according to
information content hypothesis. Chen et al. (2009) found the Chinese market reacting positively
to both dividend increases and dividend decreases, showing partial compliance with the dividend
signalling hypothesis. The empirical results are mixed regarding the dividend signalling effects
to the value of stocks.
The similar results were found also by Dangol (2008a) in the case of Nepalese stock market.
Dangol (2008a) explained that the percentage change in the dividend was strongly positive
correlated with security abnormal returns; however, the payout ratio change was not a significant
explanatory variable. The study results of Impson and Karafiath (1992) and Dangol (2008a) are
attributed to the information content of dividend. These studies provided a message that the
payout ratio changes are only an artifact of an earnings-stream that is more variable than the
dividend-stream; it hints at having no significant shifts in the managerial policy.
In Nepal, Bhatta (2008) evaluated the effect of cash dividend announcements on stock returns
and did not find any dividend signalling effect, and rejected the semi-strong form of market
efficiency. Similarly, Dangol (2009) examined the abnormal returns of dividend announcements
in the Nepalese stock market using the market model of event methodology. The overall 49
dividend announcement samples were partitioned into dividend-increase (good-news), dividend-
decrease (bad-news), and no dividend-change (no-news) sub-samples between 1998 and 2006.
The average abnormal returns around the dividend announcement days (0, +1) were found to be
positive and statistically significant. The abnormal returns were found much higher around the
dividend announcement day. The dividend announcements had a signalling effect on Nepalese
stock market. The study found inefficiency of the Nepalese stock market at the semi-strong level.
Similarly, in the previous study of Dangol (2008b) also found the similar results supporting
information content hypothesis and rejecting efficiency of semi-strong form in the Nepalese
stock market.

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The majority of the above studies showed that the dividend signalling hypothesis was accepted in
the developed markets and stock prices were adjusted effectively during the announcement day.
On the contrary, dividend announcement-effect has not been observed effectively in the
emerging stock markets. Similarly, in the emerging markets, the leakage of dividend
announcement-news is also possible to a great extent. The major inference of almost all the
studies concerning with the event window is either positive or negative abnormal returns. Good-
news announcement affects investors’ confidence positively towards the stock market. It creates
positive abnormal market returns to shareholders. On the contrary, announcements of bad-news
lead investors towards the future uncertainties so that investors tend to lose their confidence in
the stock market, and it generates negative abnormal market return. In the context of Nepal, there
is the need to study whether the dividend announcements generate immediate market reactions or
not.
4. Hypotheses
The study has formulated hypotheses on the basis of the dividend signalling assumptions. First,
the study analyses the relationship between dividend change announcements and the stock price
movements around dividend announcements. The study has considered the effects of dividend
announcements to stock price in the different portfolio, for example, on the basis of dividend
changes (increases, decreases and no-changes), Market-to-book ratio as a proxy for growth
opportunity, firm size (market capitalisation) as a proxy for firm’s information environment,
stock market condition as a proxy for short-term investment risk, and dividend yield as a proxy
of returns on investment, year-by-year analysis for market development proxy (market reaction
is time specific).
4.1 Hypothesis 1: Relation between dividend announcements and the market reaction
The current study has started with analysis of the relationship between dividend change
announcements and the share price movements on the dividend announcement period. To do so,
the following hypotheses have been formulated:
Null hypothesis, H0: “The dividend changes are not associated with a subsequent share
price-reaction in the same direction during the dividend announcement period”

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Alternative hypothesis, H1: “The dividend changes are associated with a subsequent share
price-reaction in the same direction during the dividend announcement period”
This hypothesis reflects the signalling theory assumption that dividend announcement conveys
information to the market about firms future profitability. So, if the null hypothesis is rejected,
the results support the dividend information content hypothesis. If stock price adjust effectively
within the day of dividend announcement, then it fulfils the notion of market efficiency in semi-
strong form.
4.2 Hypothesis 2: Relations between dividend announcements and firm-specific factors
According to the information content hypothesis, the strength of the market reaction to dividend
change announcements is a function of how much information is exposed. Asquith and Mullins
(1983), Dasilas et al. (2009), Chen et al. (2009) and Kosedag and Qian (2009) have documented
the relationship between the valuation effect of dividend changes and firm specific variables.
Dasilas et al. (2009) and, Kosedag and Qian (2009) found negative relationship between firm
size and abnormal returns around the dividend announcement date. Ghosh and Woolridge (1988)
concluded that the most significant factors are the percentage change of dividends, the firm’s
size and the share performance before the announcement date. Kosedag and Qian (2009) and
Chen et al. (2009) documented about dividend yield has a significantly positive relationship with
the cumulative abnormal returns around the dividend announcement period.
The study has formulated an alternative hypothesis with the purpose of analysing if there are
firm-specific factors that influence the market reaction around dividend change announcement
period. This prediction can be tested through the following hypotheses:
Null hypothesis, H0: “Firm-specific factors do not affect the market reaction around the
dividend change announcement period”
Alternative hypothesis, H1: “Firm-specific factors affect the market reaction around the
dividend change announcement period”

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If the study finds out firm-specific variables significantly associated with price changes in the
dividend announcement period, such as dividend yield, firm size, and market-to-book value, it
will have evidence of firm-specific factors influencing the market reaction to dividend
announcement. It would form the evidence that the Nepalese market would not be efficient in
semi-strong form of market efficiency.
5. Research Methods
5.1 Population
As the size of the population, the study has considered those listed companies that have
announced dividends from mid-July 2000 to mid-July 2011 in Nepal Stock Exchange (NEPSE).
5.2 Sample selection
In event studies, the objective is to examine the market response through the observation of
securities prices around such dividend events. For events, it is related to the release of new
unanticipated information to market participants through the economic news reports appearing in
the national media. Normal or predicted returns for an asset are those returns if no event occurs.
Thus, a measure of the event’s economic impact can be assessed using security prices observed
over a relative short time period (MacKinlay, 1997).
In this connection, the significance of the abnormal return states that the event has a significant
impact on the value of the firm. The inference of significance relies on the following
assumptions as suggested by McWilliams and Siegel (1997): (1) markets are efficient, (2) the
event is unanticipated, and (3) there are no confounding effects during the event windows.
Keeping the above-mentioned points in view, the sample companies of the study should fulfil the
following criteria:
• The company should be the one listed at the Nepal Stock Exchange Ltd (NEPSE).
• The company should not be the one that has remained de-listed for a long period of time.
• The company should be the one that has already paid dividends (cash or stock or both) at
least one time in its life.

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• The company should be the one that has not dividend events with other potentially
contamination announcements, i.e., rights-share issue, merger or acquisition, investment
decision, and capital gain tax changes announcements occurring within 10 days
(Confounding effect before and after 10 days of divided announcement).
• The securities of the company should be the one traded on at least 50 per cent of the floor-
days during the estimation period. This can avoid the sample traded very infrequently.
• The company should not have missing data (on dividend announcement date, and annual
reports.)
The study has considered the dividend announcements between 2000/011
and 2010/11. During
the period, total dividend events are 561 company-observations. On the basis of the above
criteria, the total sample for the analysis has been fixed at 139 firm dividend announcements.
The selected sample size has been found statistically adequate according to the calculation based
on the formula devised by Cochran (1999). The sample includes dividend events: dividend
initiation, dividend increase, dividend decrease and dividend no-change. The table 1 summarise
the population and sample data.
Nepalese stock market is small, under developed, with a smaller number of listed firms and
fewer dividend events. The previous studies have also worked with smaller samples. For
example, in the US, Petit (1972) worked with 135 dividend changes, Impson and Karafiath
(1992) with 77 observations of dividend increases and 39 of dividend decreases. In the Malaysia,
Abdullah et al. (2002) had 40 observations each for dividend increases, decreases and no-
changes. Dasilas et al. (2009) analysed the cases of 38 dividend initiations in the Greek market.
In the Pakistan, Akbar and Baig (2010) used 79 dividend events. Similarly, Joshipura (2009)
have analysed a sample of 59 dividend announcements and Raja and Sudhahar (2010) studied the
43 cases of dividend events in the Indian market.

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Table 1: Sample selection
The table reports the number of dividend events (population) and samples for analysis, classified by sample
selection criteria as well as the frequency by years (Panel A). Dividend events in terms of dividend initiation,
dividend increase, dividend decrease and dividend no-change as well as its types categorised into only cash
dividend, only stock dividend and, both cash-and-stock dividend are shown in Panel B. Similarly, Panel C
presents sample companies by industry breakdown.
Panel A: Sample and its frequency by year
Fiscal
years
Total
number of
dividend
events
Dividend events with other
potentially contamination
announcements occurs within
10 trading days (Confounding
effect before and after 10
trading days of divided
announcement)
Infrequent trading
(stock trade less
than 50% (90
days) during the
estimation period
Dividend
events
with
missing
data
Total
excluded
dividend
events
Total
number of
dividend
events for
analysis
Percentage
(%)
2000/01 41 6 24 5 35 6 4.32
2001/02 49 7 31 7 45 4 2.88
2002/03 37 5 20 6 31 6 4.32
2003/04 44 8 16 12 36 8 5.76
2004/05 33 2 14 10 26 7 5.04
2005/06 52 6 23 15 44 8 5.76
2006/07 61 5 34 11 50 11 7.91
2007/08 69 4 41 10 55 14 10.07
2008/09 68 6 30 15 51 17 12.23
2009/10 51 5 16 6 27 24 17.27
2010/11 56 2 18 2 22 34 24.46
Total 561 56 267 99 422 139 100.00
Panel B: Dividend events and its classification
Dividend events
Type of Dividend
Cash Stock Cash and Stock Total
Percentage
(%)
Dividend Initiation 13 14 3 30 21.58
Dividend Increased 27 10 18 55 39.57
Dividend Decreased 18 6 13 37 26.62
Dividend No-changed 6 8 3 17 12.23
Total 64 38 37 139 100.00
Percentage (%) 46.04 27.34 26.62 100.00
Panel C: Sample by industry breakdown
Type of companies
Number of dividend
announcements Percentage (%)
Commercial Bank 98 70.50
Development Bank 20 14.39
Finance Company 12 8.63
Hydro Power 6 4.32
Others 3 2.16
Total 139 100.00

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5.3 Data
The data for the investigation of the proposed hypotheses relate to dividend announcements date
and rate of dividend have been obtained from the individual companies. The required
information relating to dividend yield and market-to-book ratios have been calculated from the
annual reports of the individual company. The daily market indices have been obtained from the
official website of Nepal Stock Exchange (NEPSE). The total number of companies listed in
NEPSE, dividend payers and dividend non-payers companies have been obtained from the
annual reports of Securities Board of Nepal (SEBON).
5.3.1 Methodology to test Hypothesis 1: Relationship between dividend announcements and
the market reaction
The study has chosen the methodology most appropriate to test the hypothesis formulated.
Basically, ‘Market model’ is employed to test dividend announcements effect to stock price. The
methodologies to test pre-stated hypotheses and approaches for testing propose models as under:
To test the relations between dividend announcements and the market reaction, the majority of
the studies have used market model2
, which is already known as the event study3
, thus:
Rit = αi + βi Rmt + eit ....................................................................................................(1)
The market model makes no explicit assumption about how equilibrium stock prices are
established (Strong, 1992). The basic assumption of the market model are (i) error term (eit) is a
mean zero, independent disturbance term in period t, (ii) linear relationship between overall
market returns (Rmt) and the individual stock returns (Rit), and (iii) the effect of firm-specific
events is meant to be fully captured in the unsystematic component (eit) and the information
signal, i.e., dividend announcement and market returns (Rmt) are independent.
Dangol (2012) discovered that the Nepalese stock market suffered from the thin trading
(infrequent trading) problem. First, such problems lead to autocorrelation structure in the returns
series (Miller et al., 1994). The returns series are required to correct without autocorrelations in

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the series. Second, these effects have centred on price-adjustment delays and trading frictions
which cause the observed returns on stocks to depart from their true value (Strong, 1992). Third,
price-adjustment delays result in an error-in-variables problem in the ordinary least squares
market model regression model resulting in biased and inconsistent beta estimates. Strong (1992)
argued that the biased beta estimates have the potential for resulting in biased estimates of
abnormal returns and consequently misspecification test statistics in the event studies.
To remove the problem of thin-trading and its effect on event methodology4
, the study applies a
correction to the observed overall index by using a methodology proposed by Miller et al.
(1994). Thus, the proposed model to investigate about abnormal returns on stock due to dividend
announcements is as under:
Rit = αi + βi
adj
mt
R + eit ...............................................................................................(2)
Where, Rit = the return of stock i on day t = Ln (
1
-
t
t
P
P
)
adj
mt
R = the adjusted market return on day t5
Rmt = the unadjusted market return on day t = Ln (
1
-
mt
mt
NEPSE
NEPSE
)
eit = a random error term for stock i on day t
αi and βi = firm independent coefficients to be estimated
Here, the returns series are taken in logarithm as suggested by Strong (1992). Theoretically and
empirically, these reasons to take logarithm returns are justified. Theoretically, logarithmic
returns are analytically more tractable when linking returns over longer intervals. Empirically,
logarithmic returns are more likely to be normally distributed, which is a prior condition of
standard statistical techniques.
The market model is estimated for each company in the sample using 180 daily returns. The
estimated period starts 200 days before the announcement date and ends of 21 days before the
announcement date (or day t = - 200 to day t = -21). The length of the estimation period used in

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this study is consistent with prior studies of capital market responses (Bosch & Hirchey, 1989,
Hovav & D’Arcy, 2003, Dasilas & Leventis, 2011). The estimated parameters and the realised
returns on the adjusted overall NEPSE market index have been used to predict normal returns
before and after the event period.
The study confined to six separate events periods for a 21 days around the event announcement
(i.e. –10 days to +10 days) as suggested by Cheng and Leung (2006). Event day t = 0, is the date
when firm i makes the announcements of dividend6
. The shorter event window is selected to test
the effects of dividend events, are quickly incorporated into stock prices. McWilliams and Siegal
(1997) argued that the assumption of market efficiency is difficult to reconcile with the use of a
long event window.
Figure 1: Parameter estimation and event periods
The figure reports parameter estimation and different major dividend event periods. The total event period
is for 21 days around the dividend event announcement (i.e. –10 days to +10 days). The market model has
estimated its coefficient for each sample company using 180 daily returns. The estimated period starts 200
days before the announcement date and ends 21 days before the announcement date (or day t = - 200 to
day t = -21). The category of event periods covers the complete event window in major three separate
segments: (1) the pre-event period (-10, -2), ten trading days prior to the information announcement, t –
10, to two day prior to the date of announcement day (i.e. day t = -10 to t = -2; (2) the announcement
period (-1, +1), one trading day prior to the dividend information announcement, t – 1, to one trading day
after the date of dividend announcement (i.e. day t = -1 to t = +1) and (3) the post announcement period
(+2, +10), two trading days after the announcement, t + 2, to ten trading days after the dividend
announcement, t + 10; (i.e. day t = +2 to t = +10). Event day t = 0, is the date when firm i makes the
announcement of new unanticipated dividend information.
t = -200
days
t = -21
days
t = -10
days
t = -5
days
t = -2
days
t = -1
days
t = 0
Event
day
t = +1
days
t = +2
days
t = +3
days
t = +5
days
t =+10
days
Estimation periods
(-200, -21)
Event periods (-10, +10)
Pre-event period
(-10, -2)
Announcement
period
(-1, +1)
Post-event period
(+2, +10)
The coefficient estimates from regression equation are used to predict normal returns for the six
events periods: (-10, -2), (+2, +10), (-10, +10), (-5, +5), (-3, +3) and (-1, +1). Prediction errors

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during the event periods, i.e., deviations of realisation returns from normal returns, are estimates
of abnormal returns (AR). Thus, the market model is used to calculate an abnormal return for the
common stock of a firm i on event day t, as under:
)
R
β̂
α̂
(
-
R
AR Adj
mt
i
i
it
it +
= ………….………………………………….(3)
The null hypothesis to be tested is that the average abnormal returns and cumulative abnormal
return are equal to zero for any given event period. More formally, for a sample of N securities,
the mean abnormal returns on any given day t is:

=
=
N
1
i
it
t AR
N
1
AR …………………………….…………………………...….…..(4)
To measure abnormal returns over a specific time interval or holding period, the sample mean
abnormal returns are summed to derive the sample mean cumulative abnormal returns as under:

=
=
2
1
T
T
t
t
t AR
CAR ….…………….…………….………………….……………(5)
where, T1 and T2 identify beginning and ending days of sample-specific event periods within the
overall 21 days t = -10 to t = +10 event period. The test t-statistic for the significance of t
AR is
calculated as under:
t – statistic (for AR) 7
=
)
AR
(
Ŝ
AR
t
t
……………………………………………(6)
where,
)
AR
(
Ŝ t = 
=
=
21
-
t
200
-
t
2
t
t
179
)
AR
-
AR
(
…………....…………………………………..(7)

=
=
=
21
-
t
200
-
t
t
AR
180
1
AR ……………………….………..……………………....…….(8)

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where, t = -200 to t = -21 is the 180 days estimation period. The interval test statistic for each
sample and each holding period of T days in length is assumed to be approximately unit-normal
and can be written as under and follows a t-statistic distribution:
1
T
-
T
)
AR
(
Ŝ
CAR
CAR)
(for
statistic
t
1
2
t
t
+
=
− …………………………………(9)
The method discussed to this point is parametric in nature, in that specific assumptions have been
made about the distribution of abnormal returns. Alternative non-parametric approaches are
available, which are free of specific assumptions concerning the distribution of returns. So, the
significance of daily and cumulative average abnormal returns is further tested using a non-
parametric binominal statistic calculated as under:
P)
-
(1
NP
E
-
A
Z = ………………………………………………………………...(10)
where, A is the actual number of positive abnormal returns, E is the expected number of positive
returns (i.e., equal to N × P), N is the number of observations, and P is the expected percent of
positive abnormal returns. Under the null hypothesis of no effect, P = 0.5. The binomial Z
statistic tests whether the proportion of positive to negative returns exceeds the number expected
from the market model. This binomial Z statistic is more conservative than the t-statistic test and
does not require the assumption of normality.
Similarly, the investigation of dividend announcements effect on equity price starts with the
defining of the dividend process as a martingale, i.e., assumption of investors to expect future
dividends to be unchanged: E[Di,t] =Di,t-1 where E[Di,t] stands for the expected dividend of
company i for year t and Di,t-1 is last year’s dividend. A dividend announcements is considered to
be a positive surprise for market participants if a
t
i,
D > E[Di,t], neutral if a
t
i,
D = E[Di,t] and a
negative if a
t
i,
D < E[Di,t], where a
t
i,
D denotes the announced dividend of company i for year t.

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Assumption about the dividend process has its origin in the reluctance-to-change dividends
hypothesis, which states that companies are typically averse to changing dividends unless
substantial changes in the economic situation of the firm appear to make it necessary.
On the basis of the above-mentioned dividend process, average cumulative abnormal returns are
tested during the dividend announcement period to dividend-increases (good-news), dividend-
decreases (bad-news) and constant-dividend (no-news) sub-samples.
5.3.2 Methodology to test Hypothesis 2: Relation between dividend changes announcements
and firm-specific factors
The study has employed regressions to get better insight about which variables influence the
price reaction to dividend announcements. The cumulative abnormal returns obtained from
market model are the dependent variable while dividend yield, size of firm, percentage change in
dividend, Market-to-book ratio, dummy for market conditions and time specific are the
independent variables.
Thus, the model has regressed the cumulative abnormal returns on the event period (CAR-1 to +1)
obtained from market model independent variables, such as dividend yield (DY), firm size
(SIZE), percentage change in dividend (ΔD), Market-to-book ratio (MB), dummy for market
conditions (MC) and dummy for time specific (YEAR).
The model is reported as follows:
CARi,-1 to +1 = α + β1 ΔDi + β2 DYi + β3 SIZEi + β4MBi + eit .……..………………..(11)
CARi,-1 to +1 = α + β1 ΔDi + β2 DYi + β3 SIZEi + β4MBi + β5MCi + β6YEARi + eit ...(12)
where,
CARi,-1 to +1 = Cumulative abnormal return for share i, during announcement
period (-1,+1)
ΔD = the percentage change in the dividend from year to year
DY = dividend yield estimated as the ratio of the annual dividend over
the price one day prior to the dividend announcement day
SIZE = the firm size as measured by the logarithmic market capitalisation

17
one day prior to the dividend announcement day
MB = Market-to-book ratio one day prior to the dividend announcement
day
MC = Dummy variable of market conditions, value 1 if up market
condition, zero otherwise
YEAR = Dummy variable of year specification, value 1 if time period is
classify current period, zero otherwise
Interpretation of the signs of variables differs depending on the dividend changes direction. The
independent variables are explained below:
Percentage change in dividend (ΔD)
Following Asquith and Mullins (1983), the percentage change of dividends has been considered
as a proxy for the information content of dividend changes. Assuming that a bigger change
reveals more information, the coefficient of this variable is expected to be positive.
Dividend yield (DY)
According to Dasilas and Leventis (2011), dividend yield is the main driver of abnormal returns
on dividend dates. It means that the higher the dividend yield, the more attractive the share to
investors. Therefore, the expected coefficient is to be a positive sign.
Firm size (SIZE)
Firm size is associated with information asymmetry, since less information is available to the
market about smaller firms, which attract less institutional interest. The information content of
dividend announcements will be greater for small firms than that for large firms. Smaller firms
have less information available in the market, hence, when they announce dividend changes, it
generates greater market surprises that lead to a big market reaction, i.e., small firm earn higher
abnormal returns than large firms. Therefore, the coefficient has expected a negative sign.
Market-to-book ratio (MB)
The market-to-book ratio is an indicator of investors’ expectation of a firm’s growth prospects or
investment opportunities, and thus as a proxy for firm maturity and for firm’s growth

18
opportunities. Market-to-book ratio is calculated by dividing the market price per share at the
dividend change announcement date by the book-value per share at the end of the year before the
dividend change year. A high ratio value means that a firm has strong growth prospects. Firms
with fewer investment opportunities will have more free cash flows and so pay higher dividend.
Furthermore, by paying more dividends, they will reduce agency cost. Assuming the
assumptions of free cash flow hypothesis of Jensen (1986), the market reaction to be a dividend
increase must be higher for firms with fewer investment opportunities, so the coefficient of this
variable is expected to be negative.
Dummy variable for market conditions (MC)
The market conditions, i.e., up and down markets, is an important influencing factor for the
valuation of share during dividend-change announcements. From a signal-effect perspective, it
would expect that in down markets, dividend increases should create higher price reactions than
that in up markets, and dividend decreases would have lower price reactions in down markets
than that in the up markets. Thus, the coefficient is expected to be a positive sign.
Dummy for time specific (YEAR)
This variable is the proxy to verify the effect of possible year effects. Therefore, it cannot
determine, a priori, the direction of the relations between this variable and the market reaction to
dividend change announcements.
The independent variables, abbreviations and the expected signal of the regression coefficients
are as follows:
Variables Abbreviations Expected sign
Dividend yield DY +
Firm size SIZE -
Percentage change in dividend ΔD +
Market-to-book ratio MB -
Dummy variable for market conditions MC +
Dummy for time specific YEAR + or -

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6. Empirical test results
6.1 Test results of the hypothesis 1: Relations between dividend change announcements
and the market reaction
6.1.1 Abnormal returns
The possible differences, abnormal returns (prediction errors), in the effects of dividend-
initiation (good-news), dividend-increase (good-news), dividend-decrease (bad-news) and no
dividend-change (no-news) dividend announcements are considered. During the study period, the
average daily prediction errors from day t = -10 to day t = +10, and t-statistic are shown in
Tables 2, 3, 4 and 5. The tables also report the distribution of cumulative average abnormal
returns, and t-statistic, with event periods of different length such as (-10, -2), (+2, +10), (-10,
+10), (-5, +5), (-3, +3) and (-1, +1).
These tables depict average daily abnormal returns in panel-A and cumulative average abnormal
returns in panel-B for the dividend initiation announcements. The prior expectations such as,
dividend initiations and dividend-increase (good-news) announcements cause strong positive
average abnormal returns, and dividend decrease (bad-news) announcements cause strong
negative average abnormal returns either daily or cumulative. Similarly, there is no significant
average abnormal return in the case of dividend no-change (no-news). The dividend initiations
and increase-announcements are bound to introduce substantial certainty about the future course
of the firm business and the share market. It has enhanced the investors’ confidence. Thus, a
positive value-effect may be expected from the dividend initiations and increase announcements.
Similarly, the dividend decrease announcements are bound to introduce substantial uncertainty
about the future course of the firm business and its returns, and therefore, it results in loss of
investors’ confidence. Thus, a negative value-effect might be expected from the dividend-
decrease announcements.
Abnormal returns: Dividend initiation
According to Table 2, the highest positive abnormal returns among the event window is 0.028
per cent with statistically significant at the 1 per cent level in both parametric t-test (t = 5.275)

20
and non-parametric Z-test (Z = 4.017) on the day of the dividend announcements. It indicates that
the dividend announcement with the dividend initiation (good-news) is the strong positive signal
effect to the Nepalese stock market. The result explains the positive effect of the dividend-
initiations (good-news) announcement is only for the announcement day. The average abnormal
return on day t = 0 (0.028 per cent) is larger than the average return on any day of ten prior or ten
subsequent days.
In case of the cumulative average abnormal returns over the pre-announcement period, the figure
(-10, -2) is 0.011 per cent without being statistically significant. The cumulative average
prediction error improved to 0.035 per cent (t-statistic = 3.902, Z = 2.921, significant at the 1 per
cent level in both tests) during the announcement period (-1, +1). It reduced to 0.005 per cent on
the post-event period (+2, +10) without being statistically significant. It indicates that 86 per cent
of the positive abnormal returns during the announcement period (-1, +1) has been cancelled
out by the post-event period (+2, +10). Hence, there is a strong positive valuation effect on
dividend-initiation (good-news) sub-sample to the share market around the dividend
announcement periods.
The other three overlapping event periods (-10, +10), (-5, +5) and (-3, +3) have also produced
strong positive cumulative average abnormal returns. During the event period (-10, +10), the
cumulative average abnormal return is 0.052 per cent (t-statistic = 2.172, Z = 2.556, significant at
the 5 per cent level). The cumulative average abnormal return over the period (-5, +5) reduced
to 0.036 per cent (t-statistic = 2.090, significant at the 5 per cent level). Similarly, the cumulative
average abnormal return over the period (-3, +3) has again fallen down to 0.033 per cent (t-
statistic = 2.049, significant at the 1 per cent level). It means that the dividend initiation sub-
samples show higher positive abnormal returns around the announcement event period. Thus, the
dividend initiations sub-sample of the dividend announcements has placed the positive valuation
effects around the announcement period.
Abnormal returns: Dividend increase
Table 3 shows the abnormal returns during dividend increases announcement events. On the day
of the dividend announcements, the highest positive abnormal returns among the event window
is 0.029 per cent with statistically significant at the 1 per cent level in both parametric t-test (t =

21
8.770) and non-parametric Z-test (Z = 4.180). The t-value and Z-value are much higher in the
case of dividend-increase than that of dividend initiation events on the event day. It indicates that
the dividend announcement with the dividend increase (good-news) is the strong positive signal
effect to the Nepalese stock market than dividend initiation event. In both cases of dividend
initiation and dividend increases, there are statistically significant positive abnormal returns in
the dividend announcement day as per expectations. The results are similar to the notion of the
efficient market hypothesis. The result explains that the statistically positive effect of the
dividend-increase (good-news) announcement is only for the announcement day. The average
abnormal return on day t = 0 (0.029 per cent) is bigger than the average return on any day of ten
prior or ten subsequent days.
In case of the cumulative average abnormal returns over the pre-announcement period, the figure
(-10, -2) is 0.001 per cent without being statistically significant. The cumulative average
abnormal returns has improved to 0.032 per cent (t-statistic = 5.729, Z = 2.832, significant at the
1 per cent level in both tests) during the announcement period (-1, +1). It has reduced to -0.006
per cent on the post-event period (+2, +10) without being statistically significant. It indicates that
the 119 per cent of the positive excess returns during the announcement period (-1, +1) are
cancelled out by the post-event period (+2, +10). Hence, there is a strong positive valuation
effect on dividend-increases (good-news) sub-sample to the share-market around the dividend
announcements periods.
The other three overlapping event periods (-10, +10), (-5, +5) and (-3, +3) have also produced
strong positive cumulative average abnormal returns. During the event period (-10, +10), the
cumulative average abnormal return is 0.028 per cent without being statistically significant. The
cumulative average abnormal return over the period (-5, +5) is 0.034 per cent (t-statistic = 3.143,
significant at the 1 per cent level). Similarly, the cumulative average abnormal returns over the
period (-3, +3) has increased to 0.036 per cent (t-statistic = 4.235 and Z = 3.101, significant at the
1 per cent level in both tests). It means that the dividend-increase sub-samples appear to the
higher positive abnormal returns around the announcement event period. Thus, the dividend-
increase announcement has placed the positive valuation effects around the announcement
period.

22
Table 2: Summary of average daily abnormal returns for the dividend initiation
sample of dividend announcements over the period July 2000 to July 2011
The table reports the average daily abnormal returns for day t = -10 to day t = +10. The sample
consists of a total 30 yearly dividend initiation announcements for the companies listed with the
NEPSE for the period covering July 2000 to July 2011. The market model is considered for the
normal returns. Average abnormal returns is the simple average abnormal return for the specified
day of the event time; and cumulative average abnormal returns is the simple cumulative average
abnormal return for the specified event window. The event time is measured in days relative to the
dividend announcement date.
Panel A: Average daily Abnormal Returns
Day Average
Abnormal
Returns
(%)
t-Statistic for
Average
Abnormal
Returns
Percentage
Positive
Abnormal
Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
-10 0.001 0.152 36.67 -1.461
-9 0.004 0.810 53.33 0.365
-8 0.002 0.358 50.00 0.000
-7 -0.007 -1.291 36.67 -1.461
-6 0.008 1.451 70.00 2.191
-5 0.002 0.403 63.33 1.461
-4 0.003 0.534 63.33 1.461
-3 -0.003 -0.669 43.33 -0.730
-2 0.002 0.408 50.00 0.000
-1 0.002 0.444 50.00 0.000
0 0.028 5.275* 86.67 4.017*
1 0.005 1.039 46.67 -0.365
2 0.002 0.358 53.33 0.365
3 -0.003 -0.483 43.33 -0.730
4 -0.004 -0.788 46.67 -0.365
5 0.002 0.411 43.33 -0.730
6 0.009 1.770 66.67 1.826
7 0.001 0.116 53.33 0.365
8 0.001 0.276 53.33 0.365
9 0.001 0.286 53.33 0.365
10 -0.005 -0.908 36.67 -1.461
Panel B: Cumulative average abnormal returns
Period
Cumulative
Average
Abnormal
Returns (%)
t-Statistic for
Cumulative
Average
Abnormal Returns
Percentage
Positive
Cumulative
Abnormal Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
(+2, +10) 0.005 0.346 56.67 0.730
(-10, +10) 0.052 2.172** 73.33 2.556**
(-5, +5) 0.036 2.090** 63.33 1.461
(-3, +3) 0.033 2.409** 66.67 1.826
(-1, +1) 0.035 3.902* 76.67 2.921*
(-10, -2) 0.011 0.719 60.00 1.095
** Significant at the 5% level (two-tail test)
* Significant at the 1% level (two-tail test)

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Table 3: Summary of average daily abnormal returns for the dividend increase
consists of a total 55 yearly dividend-increase announcements for the companies listed at the
NEPSE for the period of July 2000 to July 2011. The market model is considered for the normal
returns. Average abnormal returns is the simple average abnormal return for the specified day of
the event time; and cumulative average abnormal returns is the simple cumulative average
Day Average
Abnormal
Returns
(%)
t-Statistic for
Average
Abnormal
Returns
Percentage
Positive
Abnormal
Returns
Z-Statistic for
Percentage
Positive Abnormal
Returns
-10 -0.002 -0.647 43.64 -0.944
-9 0.001 0.388 50.91 0.135
-8 0.002 0.480 49.09 -0.135
-7 -0.003 -0.848 52.73 0.405
-6 0.002 0.493 50.91 0.135
-5 0.000 -0.091 41.82 -1.214
-4 -0.001 -0.277 47.27 -0.405
-3 0.002 0.509 43.64 -0.944
-2 0.001 0.426 49.09 -0.135
-1 0.005 1.442 52.73 0.405
0 0.029* 8.770 78.18* 4.180
1 -0.001 -0.289 40.00 -1.483
2 0.003 0.817 52.73 0.405
3 -0.002 -0.470 43.64 -0.944
4 -0.005 -1.440 38.18 -1.753
5 0.003 1.027 49.09 -0.135
6 -0.003 -0.826 40.00 -1.483
7 -0.001 -0.431 60.00 1.483
8 0.000 0.114 56.36 0.944
9 0.000 0.027 52.73 0.405
10 -0.002 -0.693 49.09 -0.135
Period
Cumulative
Average
Abnormal
Returns (%)
t-Statistic for
Cumulative
Average
Abnormal Returns
Percentage
Positive
Cumulative
Abnormal Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
(+2, +10) -0.006 -0.625 40.00 -1.483
(-10, +10) 0.028 1.851 50.91 0.135
(-5, +5) 0.034* 3.143 61.82 1.753
(-3, +3) 0.036* 4.235 70.91* 3.101
(-1, +1) 0.032* 5.729 69.09* 2.832
(-10, -2) 0.001 0.145 49.09 -0.135

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Table 4: Summary of average daily abnormal returns for the dividend decrease
consists of a total 37 yearly dividend decrease announcements for the companies listed at the
NEPSE for the period of July 2000 to July 2011. The market model is considered for the normal
returns. Average abnormal returns is the simple average abnormal return for the specified day of
the event time; and cumulative average abnormal returns is the simple cumulative average
Day Average
Abnormal
Returns
(%)
t-Statistic for
Average
Abnormal
Returns
Percentage
Positive
Abnormal
Returns
Z-Statistic for
Percentage
Positive Abnormal
Returns
-10 0.002 0.446 48.65 -0.164
-9 0.001 0.122 40.54 -1.151
-8 -0.003 -0.582 37.84 -1.480
-7 -0.003 -0.595 51.35 0.164
-6 0.005 1.121 56.76 0.822
-5 -0.005 -1.092 37.84 -1.480
-4 0.009 1.929 62.16 1.480
-3 -0.002 -0.505 51.35 0.164
-2 0.004 0.725 56.76 0.822
-1 0.006 1.127 51.35 0.164
0 -0.011 -2.250** 29.73 -2.466**
1 0.006 1.157 59.46 1.151
2 -0.002 -0.448 48.65 -0.164
3 0.001 0.272 62.16 1.480
4 0.001 0.207 56.76 0.822
5 -0.004 -0.887 40.54 -1.151
6 0.001 0.184 40.54 -1.151
7 -0.001 -0.255 48.65 -0.164
8 0.001 0.105 45.95 -0.493
9 0.000 -0.090 43.24 -0.822
10 0.006 1.153 62.16 1.480
Period
Cumulative
Average
Abnormal
Returns (%)
t-Statistic for
Cumulative
Average
Abnormal Returns
Percentage
Positive
Cumulative
Abnormal Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
(+2, +10) 0.001 0.080 45.95 -0.493
(-10, +10) 0.009 0.402 51.35 0.164
(-5, +5) 0.001 0.071 45.95 -0.493
(-3, +3) 0.000 0.030 45.95 -0.493
(-1, +1) 0.000 0.020 35.14 -1.808
(-10, -2) 0.008 0.523 48.65 -0.164

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Table 5: Summary of average daily abnormal returns for the dividend no-change sample
of dividend announcements over the period July 2000 to July 2011
consists of a total 17 yearly dividend no-change announcements for the companies listed at the NEPSE
for the period covering July 2000 to July 2011. The market model is considered for the normal returns.
Average abnormal returns is the simple average abnormal return for the specified day of the event time;
and cumulative average abnormal returns is the simple cumulative average abnormal return for the
specified event window. The event time is measured in days relative to the dividend announcement
date.
Day Average
Abnormal
Returns
(%)
t-Statistic for
Average
Abnormal
Returns
Percentage
Positive
Abnormal
Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
-10 -0.006 -0.838 41.18 -0.728
-9 0.006 0.852 58.82 0.728
-8 0.001 0.197 47.06 -0.243
-7 0.006 0.883 47.06 -0.243
-6 0.007 1.051 52.94 0.243
-5 0.001 0.137 47.06 -0.243
-4 0.009 1.256 47.06 -0.243
-3 0.001 0.153 41.18 -0.728
-2 0.000 0.072 41.18 -0.728
-1 -0.007 -1.003 35.29 -1.213
0 0.006 0.813 47.06 -0.243
1 0.004 0.624 47.06 -0.243
2 0.009 1.348 41.18 -0.728
3 0.004 0.632 64.71 1.213
4 0.008 1.195 58.82 0.728
5 -0.004 -0.597 47.06 -0.243
6 0.007 0.951 58.82 0.728
7 0.001 0.209 41.18 -0.728
8 0.002 0.292 52.94 0.243
9 0.005 0.774 58.82 0.728
10 0.014 2.097 58.82 0.728
Period
Cumulative
Average
Abnormal
Returns (%)
t-Statistic for
Cumulative
Average
Abnormal Returns
Percentage
Positive
Cumulative
Abnormal Returns
Z-Statistic for
Percentage Positive
Abnormal Returns
(+2, +10) 0.047 2.300** 70.59 1.698
(-10, +10) 0.076 2.422** 47.06 -0.243
(-5, +5) 0.032 1.396 52.94 0.243
(-3, +3) 0.018 0.997 47.06 -0.243
(-1, +1) 0.003 0.251 29.41 -1.698
(-10, -2) 0.026 1.254 52.94 0.243

26
Abnormal returns: Dividend decrease
Table 4 shows average daily abnormal returns (panel A) and cumulative average abnormal
returns (panel B) for the dividend-decrease (bad-news) announcements. The dividend-decrease
announcements cause strong negative average abnormal returns. On day t = 0, the strong
negative average abnormal returns of 0.011 per cent (| t | statistic = |-2.250| = 2.250 and Z = -
2.466, both significant at the 5 per cent level) has been found, and it is similar with the prior
expectation as a negative average abnormal returns during the bad-news announcements. The
average excess return on day t = 0 (-0.011 per cent) is larger than the average return on any day
of ten pre-event or ten subsequent days. Then after, on day t = +1, it drifts to positive average
abnormal returns of 0.006 per cent. The one noticeable fact is that the positive returns (0.006 per
cent without significant) in the one day prior to the dividend announcement day. The results
explain that the strong negative valuation effect to dividend-decrease (bad-news) sub-sample
only in the day of dividend announcements. Such a result is similar with the notion of the
efficient market hypothesis.
The cumulative average abnormal returns over the pre-announcement period (-10, -2) is positive
0.008 per cent without being statistically significant. The cumulative average abnormal returns
are 0 per cent (not significant) during the announcement period (-1, +1). Similarly, during the
post-event period (+2, +10), the negative cumulative average abnormal returns is 0.001 per cent
(not significant). It indicates that the positive cumulative average abnormal returns earned during
the pre-event (-10, -2) drifts to less positive returns on the post-event period (+2, +10). Hence,
the negative valuation effect of dividend-decrease (bad-news) announcements on share market
has been found.
In the case of the overlapping event periods (-10, +10) and (-5, +5), it has produced positive
cumulative average abnormal returns and event period (-3, +3) reports zero. During the event
period (-10, +10), the cumulative average abnormal returns is 0.009 per cent (not significant).
The cumulative average abnormal returns over the period (-5, +5) is 0.001 per cent and zero per
cent during the period of (-3, +3), but these are statistically insignificant.

27
The results show that the longer the length of overlapping event period, higher the cumulative
positive abnormal returns, which are reduced to zero with shorter event windows. It means the
dividend decrease sub-sample cancelled out the positive abnormal returns by negative valuation
after the event day. Thus, the dividend-decrease announcements sub-sample placed the negative
valuation effects during the announcement and the post announcement periods as per prior
expectation.
Abnormal returns: Dividend no-change
In case of dividend no-change (no-news) announcements abnormal returns— either daily or
cumulative— are usually expected in advance. Table 5 shows average daily abnormal returns
(panel A) and cumulative average abnormal returns (panel B) for the dividend no-changes (no-
news) announcements. As per prior expectation, there is no statistically significant (at 5 per cent
level) abnormal return in announcement day or any days of the 21 event periods or 3 days
announcement period (day t = -1 to day t = +1). It indicates that no excess returns (zero average
abnormal returns) generated during the day of dividend no-changes (day t = 0) and dividend
announcement period. The results supported the philosophy of efficient market hypothesis.
The cumulative average abnormal returns over the pre-announcement period (-10, -2) is 0.026
per cent (not statistically significant). The positive cumulative average abnormal return is 0.003
per cent (not statistically significant) during the announcement period (-1, +1). It indicates that
market has no reaction towards the dividend no-changes events. Similarly, during the post-event
period (+2, +10), the cumulative average abnormal return is 0.047 per cent (t-statistic = 2.300),
which is statistically significant at the 5 per cent level. It indicates the cumulative average
abnormal return earned during the pre-event period (-10, -2) has improved on the post-event
period (+2, +10). Hence, there is a positive valuation effect on dividend-no-change (no-news)
announcement to share market on the post event period.
In the case of the overlapping event periods (-10, +10), (-5, +5) and (-3, +3) produced positive
cumulative average abnormal returns. During the event period (-10, +10), the cumulative average
abnormal return is 0.076 per cent (t-statistic = 2.422, statistically significant at the 5 per cent
level). The cumulative average abnormal returns are 0.032 per cent over the period (-5, +5) and

28
the period (-3, +3) is positive 0.018 per cent, but these are statistically insignificant. The longer
the length of overlapping event period, higher the cumulative positive abnormal returns will be.
It means that the valuation effect around the announcement date is not strong.
Graphical analysis of abnormal returns
The Figure 2 presents graphs of the daily average abnormal returns for dividend-initiation,
dividend-increase, dividend-decrease, and dividend-no-change) sub-samples.
Graphical presentations can now provide more evidences. The average abnormal returns in the
twenty-one days around the event announcement date are shown in the Figures 2 (i), (ii), (iii),
and (iv). Out of twenty-one days, 10 days are pre-event periods and other 10 days are post-event
period and remaining one day as the event announcement day. In the context of dividend
initiations, Figure 2(i) shows the average abnormal returns are randomly distributed around the
zero per cent and few of the observations are reported negative on the post-event period. The
abnormal returns on dividend announcement day (t = 0) is positive and much higher than pre-
and post- dividend announcement periods. The Figure 2(ii) shows the daily average abnormal
returns in the case of dividend-increase (good news) sub-sample. The returns are randomly
distributed around the zero per cent before the event announcement and the abnormal returns on
dividend announcement day (t = 0) is positive and higher in comparison to pre- and post-
dividend announcement periods.
Figure 2(iii) shows the daily average abnormal returns in the case of dividend-decrease (bad
news) sub-sample. The majority of average abnormal returns are positive prior to the
announcement of event, which drifted into the negative on the announcement day; then it
becomes positive one day after the event announcement. The returns are randomly distributed
around the zero per cent on the rest of the post-event period.
Similarly, Figure 2(iv) shows the average abnormal returns in the case of dividend no-change
(no-news) sub-sample. The average abnormal returns are, mostly, positive prior to the
announcement of event, which remains positive on the post-event period. The 9 out of 10
observations of the post-event are in the positive average abnormal returns. It indicates that the
dividend no-change announcement is also a good signal to market.

29
The Figure 3 depicts cumulative average abnormal returns for the dividend initiations, increase,
decrease and no-change around the 21 event window from day t = -10 to day t = +10. In the
announcement period and post-event period, the cumulative abnormal returns drift upward to the
positive in case of dividend initiation and dividend increase sub-samples. On the contrary, in
case of dividend decrease (bad-news) sub-sample, the cumulative abnormal returns have drifted
downward to the zero per cent. The cumulative abnormal returns are continuously in upward
drift pre- and post-event periods for dividend no-change firms. After the announcement day,
average abnormal returns have gone steady on the post-event period in the case of dividend
initiation, increase and decrease. The characteristics of such curves are as per prior expectations
except for the dividend no-change firms.
The Figure 4 reports cumulative average abnormal returns of dividend announcements for the
dividend initiation, increase, decrease and no-changes sample to the 12 days event periods such
as (-1, +10). These figures report the positive effect on the dividend announcements whether the
announcements are dividend initiation, increase and no-change to the announcement day. But
negative effect in the announcement day has been found in the dividend decrease firms as per
prior expectations. The dividend initiation and dividend no-change sub-samples show higher
positive average abnormal returns as well as gradual rise. The bad-news sub-sample shows
gradually drift downward to the negative over the post-event period. The dividend decreases sub-
sample has negative average cumulative abnormal returns (slightly below the zero per cent), and
is relatively stable, as would be expected. Similarly, the average cumulative abnormal returns are
shown in stable patterns for dividend increases firms in post-event period. The dividend no-
change (no-news) sub-sample’s graph line lies between the dividend initiation, dividend increase
(good-news) and dividend decrease (bad-news) announcements up to day t = +7. These findings
are similar with the earlier results as reported by MacKinlay (1997) – who investigated
cumulative average abnormal returns in the case of the earnings announcements into three
groups, good-news, bad-news and no-news, applying market model and constant-mean-return
model.

30
Figure 2: Average abnormal returns of dividend announcements for dividend-initiation,
dividend-increase, dividend-decrease and dividend-no-change sub-samples
The figures report average abnormal returns of dividend announcements for 21 day-event period from day t = -10
to day t = +10 for dividend-initiation, dividend-increase, dividend-decrease and dividend-no-change sub-samples.

31
Figure 2: Average abnormal returns of dividend announcements for dividend-initiation, dividend-
increase, dividend-decrease and dividend-no-change sub-samples (Contd.)

32
Figure 3: Cumulative average abnormal return of dividend announcement of dividend initiation,
dividend increase, dividend decrease and dividend no-change
sub-samples for 21 days event periods from day t = -10 to day t = +10
Figure 4: Cumulative average abnormal return of dividend announcement of dividend initiation,
dividend increase, dividend decrease and dividend no-change
sub-samples for 12 days event periods from day t = -1 to day t = +10

33
The behaviour of abnormal returns for dividend announcement events with dividend
initiation/increase (good-news), dividend decrease (bad-news) and dividend no-change (no-
news), however, provide the strongest evidence in favour of immediate market response to
dividend information for the valuation of firms.
As per Fama (1991) stock prices get adjusted within a day to event announcements. The fact that
quick adjustment is consistent with efficiency is noted. The present empirical evidences accept
the Efficient Market Hypothesis. First, the positive (negative) abnormal returns with statistically
significant has shown only in dividend announcement day for dividend initiations, increases
(decreases). In other words, market is able to identify the dividend changed on the day of
dividend announcements, i.e., dividend initiation and dividend-increase report statistically
significant positive abnormal returns on the dividend announcement day. Similarly, dividend-
decrease firms experience statistically significant negative abnormal returns on the event day.
The dividend changes and abnormal returns move in the same direction strongly. However, there
is no significant abnormal returns (nearly zero) reported in the dividend no-change firms. It
indicates that the stock price adjustment has made within day of dividend announcement
considering dividend initiation/increase (good-news), dividend decrease (bad-news) and
dividend no-change (no-news). Second, there are no leakages of the dividend announcement
information (i.e. insider information or private information) since no statistically significant
abnormal returns have been found before announcement days (i.e., day t = -10 to day t = -1) for
all dividend events (initiation, increase, decrease and no-change). Third, there is no statistically
significant returns during post announcement event days (i.e., day t = +1 to day t = +10) for all
dividend events.
The study results with respect to dividend announcements is similar with the previous study by
Pettit (1972) – who provided evidences on the hypothesis that changes in dividend levels- give
out important information to market participants, i.e., changes in dividend payments in assessing
the value of a security.
It is noted that the study result is consistent with Kwan (1981), Aharony and Swary (1980), and
Dhillon and Johnson (1994) from the viewpoint of information content dividend hypothesis.

34
Dhillon and Johnson (1994) reported that the information content hypothesis is similar with
positive reaction to a dividend increase. It is so because dividend increases are perceived as
good-news by the investors. Ghosh and Woolridge (1991) opined that the rational investors react
only to the unexpected news content of dividend announcements. Thus, the study results are
supported the alternative hypothesis showing that the dividend changes are associated with a
subsequent share price-reaction in the same direction during the dividend announcement period.
The Nepalese investors are found to be rational to dividend events. The result is the evidence of
efficiency of the Nepalese stock market at the semi-strong level. Similarly, the results are
consistent with McCluskey et al. (2006) from the market efficiency viewpoints.
6.2.1 Test results of the hypothesis 2: Relations between dividend change announcements
and firm-specific factors
To evaluate whether firm-specific factors affect the market reaction in the dividend
announcement period, the study has tested the relationship between the cumulative abnormal
returns in the dividend announcement period (day t = -1 to day t = +1) and the firm specific
variables, estimating the regression equation 11. Apart from this, the equation 12 has also been
employed to test the effect of market conditions and time specific effect. The results are shown
in Table 6.
The pooled least squares have been first regressed for abnormal returns in the announcement
period (CAR-1,+1) with percentage of dividend changes (model 1). The DW statistic is 2.054,
indicating that the model is free from the autocorrelation problem and F value is 14.659, which is
statistically significant at 1 per cent level. The model is found to be good fit. The constant term is
statistically significant at 1 per cent level, showing a significant impact of dividend no-change
announcements on the market reaction. So is not predicted by the dividend-signalling hypothesis.
The coefficient of percentage of dividend change (ΔD) is positive and statistically significant at 1
per cent level. It indicates that the dividend changes are associated with a subsequent share price
reaction in the same direction during the dividend announcement period.
Then, regression has been run for abnormal returns in the announcement period (CAR-1,+1) with
percentage of dividend change (ΔD) and dividend yield (model 2). The DW statistic is 2.052,

35
indicating that the model has no autocorrelation problem and F value is 7.209, which is
statistically significant at 1 per cent level. It indicates that the model is statistically fit for further
analysis. The constant term is statistically insignificant, showing no impact of constant dividend
announcements on the market reaction, as predicted by the dividend-signalling hypothesis. The
coefficient of percentage of dividend change (ΔD) is positive and statistically significant at 1 per
cent level, and dividend yield (DY) is insignificant. It indicates that the percentage of dividend
changes is the dominating factor to determine abnormal returns during the dividend
announcement period.
In model 3, abnormal returns in announcement period (CAR-1,+1) have been regressed with
percentage of dividend change (ΔD) and firm’s size (SIZE). The DW statistic is 2.059, indicating
the model is free from autocorrelation problem and F value is 7.222, which is statistically
significant at 1 per cent level. It indicates that the model is statistically fit for further analysis.
The constant term is statistically insignificant, showing no impact of announcements of
unchanged dividend on the market reaction, as predicted by the dividend-signalling hypothesis.
per cent level and firm’s size (SIZE) is insignificant. It indicates that the percentage of dividend
changes is the influential factor to determine abnormal returns during the dividend
announcement period, and firm’s size has no explanatory power.
Then after, by regressing abnormal returns in the announcement period (CAR-1,+1) with
percentage of dividend change (ΔD) and Market-to-book ratio (MB) (model 4), the DW statistic
has been found to be 2.031. It indicates that there is no autocorrelation problem in the model and
F value is 7.483, which is statistically significant at 1 per cent level. It all indicates that the
model is statistically good enough for further analysis. The constant term is statistically
insignificant, showing no impact of constant dividend announcements on the market reaction,
which is predicted by the dividend-signalling hypothesis. The coefficient of percentage of
dividend change (ΔD) is positive and statistically significant at 1 per cent level and market-to-
book ratio (MB) is insignificant. It indicates that the percentage of dividend changes is the main
factor to determine abnormal returns during the dividend announcement period, and the market-
to-book ratio of the firm has no explanatory power.

36
Table 6: Regression of market reaction to dividend-change and other variables
The table reports the regression of market reaction to dividend-change and such other fundamental
variables as dividend yield, size of firm, market-to-book ratio, market condition and time specific effects
considering the dependent variable as CAR-1,+1. The CAR-1,+1 is the cumulative abnormal returns on the 3
day period, i.e., 1 day before and 1 day after the dividend announcement day. ΔDi is the dividend per
share changes for the year t. DY is the dividend yield estimated as the ratio of the annual dividend over
the price one day prior to the dividend announcement day. SIZE is the firm size as measured by the
logarithmic market capitalisation one day prior to the dividend announcement day. MB is the market-to-
book ratio one day prior to the dividend announcement day. MC is the dummy variable of market
conditions with the value 1 if there is the up-market condition, otherwise remains at zero. YEAR is the
dummy variable of year specification with the value 1 if time period is classified as present period
(beyond August 24, 2007), otherwise it remains at zero. The numbers in the parentheses are the p-values.
Dependable variable – CAR-1,+1
CARi,-1 to +1 = α + β1ΔDi + β2 DYi + β3 SIZEi + β4MBi + β5MCi + β6YEARi + eit
Coefficient Pooled OLS
1 2 3 4 5 6 7 8
Constant 0.012*** 0.013 0.001 0.005 0.018 0.006 0.019*** 0.003
(.066) (.283) (.987) (.701) (.798) (.458) (.068) (.970)
ΔD 0.038* 0.038* 0.038* 0.039* 0.038* 0.036* 0.037* 0.035*
(.000) (.000) (.000) (.000) (.001) (.001) (.000) (.002)
DY -0.029 0.142 0.256
(.928) (.713) (.538)
SIZE 0.001 -0.002 -0.001
(.860) (.774) (.904)
MB 0.001 0.002 0.002
(.490) (.430) (.489)
MC 0.017 0.013
(.180) (.396)
YEAR -0.011 -0.009
(.378) (.565)
F 14.659* 7.209* 7.222* 7.483* 3.714* 8.266* 7.660* 2.796**
(.000) (.001) (.001) (.001) (.008) (.001) (.001) (.016)
Adjusted R2
0.130 0.120 0.120 0.125 0.107 0.138 0.128 0.106
Durbin-
Waston
(D-W)
2.054 2.052 2.059 2.031 2.018 2.004 2.047 1.993
N 92 92 92 92 92 92 92 92
* Significantly different from zero at the 1% level
** Significantly different from zero at the 5% level
*** Significantly different from zero at the 10% level

37
To test the joint effect of all firm-specific variables, abnormal returns in announcement period
(CAR-1,+1) have been regressed with percentage of dividend change (ΔD), dividend yield (DY),
firm’s size (SIZE) and Market-to-book ratio (MB) (model 5). The DW statistic is 2.018, showing
the model as free from any autocorrelation problem. Similarly, F value is 3.714, which is
statistically significant at 1 per cent level indicating that the model is statistically fit for further
analysis. The constant term is statistically insignificant, showing no impact of constant dividend
announcements on the market reaction, which is predicted by the dividend-signalling hypothesis.
per cent level and other such firm specific variables as dividend yield (DY), firm size (SIZE) and
Market-to-book ratio (MB) are insignificant. It points to the finding that the percentage of
dividend change is the main element in determining abnormal returns during the dividend
announcement period. It has also been found that the variable of dividend yield (DY), firm’s
size (SIZE), and Market-to-book ratio (MB) do not adequately explain the phenomenon.
To test the effect of the market condition (i.e., up and down market status), abnormal returns in
announcement period (CAR-1,+1) have been regressed with the dummy variable of ‘market
condition’ (model 6). The DW and F value show that the model is fit and has no problem of
autocorrelation. The result of regression finds that the coefficient of ΔD is statistically significant
at 1 per cent level and the coefficient of market condition is statistically insignificant. Similarly,
to test the effect of time specific as present and past, abnormal returns in the announcement
period (CAR-1,+1) have been regressed with the dummy variable of time (YEAR) (model 7). The
DW and F value show that the model is fit without any autocorrelation problem. The constant
term is statistically significant at 10 per cent level, showing a significant impact of dividend no-
change announcements on the market reaction. The result of regression finds that the coefficient
of ΔD is statistically significant at 1 per cent level, and the coefficient of time (YEAR) is
statistically insignificant.
In model 8 of regression, to test the effect of joint effects, abnormal returns in announcement
period (CAR-1,+1) have been regressed with all firm-specific variables, dummy variable of
‘market condition’ as well as dummy variable of time specific. The DW is 1.993 (no
autocorrelation problem) and F value is equal to 2.796, which is statistically significant at 5 per

38
cent level, showing the model is fit. The result of regression finds that the coefficient of ΔD is
statistically significant at 1 per cent level and the coefficient of all other variables are statistically
insignificant.
Overall, it indicates that the percentage of dividend changes is the main explanatory variable in
determining abnormal returns during the dividend announcement period. The significant market
reaction to dividend change announcement is the evidence for agreeing with the “information
content of dividend hypothesis”. The results are similar with Pettit (1972), Aharony and Swary
(1980), Kwan (1981), Dhillon and Johnson (1994), Lonie et al. (1996), Abdullah et al. (2002),
Al-Yahyaee et al. (2011) and Dasilas and Leventis (2011) from the viewpoint of information
content dividend hypothesis. Similarly, the results are consistent with McCluskey et al. (2006)
from the market efficiency viewpoint.
The dividend yield (DY), firm’s size (SIZE) and Market-to-book ratio (MB) has no explanatory
power. Similarly, there is no effect of market conditions and time specific during the dividend
announcement. Thus, the study result supports the null hypothesis, “Firm-specific factors do not
affect the market reaction around the dividend change announcement period”. It indicates that
the Nepalese stock market reacts only to the dividend change announcement around the dividend
announcements date. The results are in agreement with the notion of semi-strong form of market
efficiency, which advocates that the fundamental analysis is unable to earn abnormal returns
from the market, and security prices reflect all publicly available information.
7. Conclusion
The study results are in consonance with the dividend information content hypothesis as well as
with the semi-strong form of efficient capital market hypothesis. On an average; the Nepalese
stock market adjusts in an efficient manner to new dividend information according to the
dividend changes. Almost all of the price adjustments have occurred within the dividend
announcement date. As per the pre-set expectation, the dividend initiation (dividend omission)
and dividend-increase (dividend-decrease) is perceived as good-news (bad-news) with only
significant abnormal returns on the dividend announcement day. No significant abnormal returns

39
are obtained on any day of the event window of 21-days during the announcement of dividend-
no-change, since it is perceived by the market as ‘no-news’ event.
The percentage of dividend changes is the main explanatory variable to determine abnormal
returns during the dividend announcement period rather than such other fundamental variables as
dividend yield (DY), firm’s size (SIZE) and Market-to-book ratio (MB). Similarly, the market
trend and time (specific) period have no effect to adjust stock prices on the day of dividend
announcements.
Thus, the debate over the empirical validity of the dividend signalling hypothesis and efficient
market hypothesis are remains alive in the finance literature.
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42
___________________________________
Notes
1. The first year 2000/01 is conditioned by the availability of information regarding the number as well
as name of firm’s dividend announcement in the annual report of SEBON.
2. Strong (1002) argued that the market model has probably been the most popular benchmark
employed in the event studies.
3. An event study is the name given to an empirical investigation of the relationship between stock
prices and economic events.
4. The thin trading on stock returns series have improved by Miller et al. (1994) model.
5. To separate the effect of thin trading; the study has applied a correction to the observed overall index
by using a methodology proposed by Miller et al. (1994) as follows:
t
1
-
mt
2
1
mt ε
R
α
α
R +
+
=
( )
2
t
adj
mt
α
-
1
ε
R =
6. The Day-zero in the event time is the dividend announcement date reported by the concerned
company. In case, the stock trading is not undertaken at the NEPSE during the time of dividend
announcement date (i.e. announcements made in public holiday, on Friday or after floor-closure, and
closure of the trading due to other reasons), then the next trading day is considered as the dividend
announcement day, i.e., day t = 0.
7. The corresponding t-statistics assumes independent drawings from identically distributed normal
population. It is, therefore, implicitly assumed that the mean effect of the event is identical across
stocks.
8. Dividend change refers to the dividends measured in percentage of differences between the current
and last fiscal years. So it is not applicable in the case of dividend initiations.

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