Many dividends theories imply that a change in the dividends signals to the market that a firm is now processing future expectations which can then cause stock price movements. This study investigates market reactions to regular cash dividend distributions for the period 2010 – 2016 on USA markets. In particular, this paper studies the effect of dividend announcements on both stock price and trading volume in high growth and low growth industries. Research results indicate that in low growth industries, the stock price moves significantly upward after increasing dividends. Moreover, the market absorbs the negative news of decreasing dividends which can still result in positive abnormal return. High growth industries experience higher price volatility and negative abnormal return after decreasing their dividends payout. The trading volume is significantly high around the announcements dates for both high and low growth industries. These results are consistent with the theory as dividend announcements convey information that significantly impacts share prices.
The principal finance goal of managers is to maximize the value of the firm and the shareholder’s investment value. Mangers take different investment and financing decisions to maximize the shareholder’s value. One of these decisions is distributing dividends to shareholders as a reward for their investments with an implied intention to reduce agency problem (Jensen and Meckling, 1976). Assuming that mangers have inside information about the firm’s future prospective, they may use various ways to signal information to the market. Dividends and earnings announcements are the most important devices to signal a change in the mangers expectations about the firm’s future prospective (Ahorny and Swary, 1980).
The effect of a firm’s dividend policy on stock returns is important to corporate managements, investors and to economists who try to understand the function of financial capitals markets. Asquith and Mullins (1983) find a significant positive abnormal return after the initial announcement of dividends. Dielman and Oppenheimer (1984) documented increase (decrease) of abnormal return after unanticipated dividend increase (decrease) announcements.
This paper examines whether the information revealed by dividend change announcements affect the valuation and abnormal return of high and low growth industries. Research that examines the dividend change impact in a corporate market value has not previously studied the growth of the industries1. Many well-published papers examine the stock market reaction around dividend announcements. However, the basic hypothesis for this paper is documenting that high growth industries have more stock price volatility. Also, this paper hypothesizes that abnormal return decreases (increases) after announcing dividend decreases (increases) in high growth industry. Moreover, following a dividend increase, low growth industry shows a higher increase in abnormal return than high growth industry. Finally, we expect low growth industries tend to maintain positive abnormal return when dividends are announced.
The remainder of the paper proceeds as follows. In Section II literature review, Section III Data, sample selection and methodology. In Section IV results and discussion. Finally, section V conclusion.
II. Literature review:
Dividends and Abnormal Returns:
There have been a large number of studies documenting the statistically significant stock price reaction following dividends changes. The abnormal return direction and magnitude are positively related to the degree and size of the dividends changes (Pettit (1972), (1976), Dielman and Oppenheimer (1984). Studies has also find that a significant abnormal return increase for the companies that initiate dividends for the first time and significant decrease for the companies that omitted dividends after previously paying them (Mitra & Owers 1995).
Lintner (1956) and Carroll (1995) find a positive relationship between unexpected dividends changes and abnormal returns. One explanation for that is that the changes in dividends signal cash flow and earnings changes in future. Kim and Verrecchia (1991a, 1991b, 1992) provide analysis of the trading behavior around expected events. Kim and Verrecchia’s model predicts an increase in stock price volatility and the trading volume during the announcement period. Quarterly dividend announcements contain useful information beyond quarterly earnings numbers and if these announcements convey useful information it will reflect immediately in the stock price. (Healy and Palepu, 1988). (Grullon, Michaely, Benartzi and Thaler, 2005) support these findings with empirical methods showing that dividend changes are negatively correlated with future changes in earnings and result in decreasing abnormal return. Pettit (1972) argues that dividends announcements convey more information than earnings numbers. Academicians like Ariff and Finn (1986), Stevens and Jose (1989), Lee (1995) find above market return following the cash dividends announcements. On the other hand, Sinclair and Easton (1989) find a negative market return following the cash dividends announcements. The positive relationship between the market return and dividends announcement is interpreted as the information effect of dividends, while the negative relationship between the market return and the dividends announcement is interpreted as the income tax effect. Gordon (1963) argues that shareholders prefer cash dividends rather than capital gain to reduce the risk in the future dividends stream and prefer a high dividends policy than uncertain future investment. Miller and Rock (1985) argue that it’s unwise for bad expectation firms to pay high level dividends, and only good expectation firms without uncertain long-term operations can pay high level dividends.
Behbahani and Rezvani (2016) find a negative and significant relationship between growth opportunities and cumulative abnormal return. They argue that, capital markets evaluate the performance and financial situations of firms with high growth opportunities helps for avoiding investors withdrawing confidence. Skinner (1994, 1997) find that firms with high growth opportunities frequently preannounced negative earnings news. This is consistent with Gulen and Schill (2009) finding that there is a strong negative relationship between high growth firms and stock return while they document a return premium of 20% per year.
In this paper, event study methodology is used to assess the impact of the dividends announcement on the abnormal return for high growth vs. low growth industries. The data used is from Center for Research in Security Prices (CRSP) daily stock file, and Compustat. A sample of 420 industrial firms listed in both New York Stock Exchange and NASDAQ. Each firm has met the following criteria:
1. Quarterly dividends per share for only regular cash dividends.
2. The distribution doesn’t include initiation or omission dividends.
3. Daily rates of return and declaration dates were available in CRSP for the period of 1/1/2010 – 12/31/2016.
4. The study used only USA firms excluding all the financial firms (SIC codes 6000 – 6999) and utilities firms (SIC code 4900 – 4949).
To empirically examine the abnormal return to quarterly dividends changes, a measure of unexpected dividends change must be derived. In common with other studies2 the expectation naïve model has been used in this study which assumes that the current dividends for quarter (q) is expected to be equal to the previous dividends for same quarter (q-1), that is:
1. E (Djq) = Djq-1
2. E (Djq) = Djq-4
Where E (Djq) = expected dividends per share for the j company in quarter q, and
Djq. = actual dividends per share announced by j company in quarter q
The first model says that expected dividend is equal to the last quarter’s dividend. This model has been used in previous studies (I.e. Aharony and Swary (1980) and Firth (1996)). This model is used for firms that pay equal amounts of dividends each quarter. The second model measures the expected dividends for the current quarter as equal the actual dividends paid four quarters ago. This model is more appropriate if firms vary dividends payment over the quarters. A dividends announcement is considered a positive event if Djq > E (Djq), neutral if Djq = E (Djq) and negative if Djq < E (Djq). Those models derived from the reluctance-to-change dividends say mangers don't change dividends unless they expect a significant change in future earnings. Increasing dividend payments signals a positive change in mangers expectations, whereas decreasing dividend payments indicates a pessimistic mangers' expectation of the firm's future prospects (Aharony and Swary, 1980). Change in dividends are calculated as: (RelDIVj,q )= Dj, q - E(Dj,q) Where (RelDIVj,q ) denote the expected change in dividends of firm j in quarter q. E(Dj,q) is the expected dividends of firm j in quarter q. Dj, q is the actual dividends of firm j in quarter q. An observation had to satisfy the following criteria 1. The dividend change (RelDIV) had to equal or exceed 0.1 or -.1, this filter will remove all the small dividends changes that convey little information to the market. Other researches have omitted small dividends changes (e.g., Firth (1996), Dielman and Opp (1984), Denis, Denis, and Sarin (1994)). 2. For model 1, there are no quarter-to-quarter changes in the prior year. Thus, Djq-1= Djq-2=Djq-3 =Djq-4 3. For model 2, no quarter to prior year quarter change. Thus, Djq-1=Djq-5, Djq-2=Djq-6, Djq-3=Djq-7, Djq-4=Djq-8. This requirement makes changes occuring in quarter q less predictable and helps in interpreting the dividends change as unexpected change. This approach has been used in Firth (1996). B. Abnormal return Methodology: The information dividends hypothesis predicts that the increase in dividends will result, on average, in an increase in abnormal return, while a decrease in the dividends payments should result, on average, in a negative abnormal return. Moreover, stocks with constant dividends (no dividend change) should, on average, have normal return. The dividends change announcement is expected to send negative and positive signals to the market. The daily stock return calculated for the 11-day event period as follow: Rj,d= ln (Pj,d – Pj,d-1) Where R jd is the actual return of share j on day d. Pj,d is the price of share j on day d, while Pj,d-1 is the price of share j on day d-1. To estimate the expected return for each share, ERj,d= j+ jRm,d + ej,d Where ERjd = Expected daily return for security j, in period d Rmd = Daily return on the CRSP, weighted market index j and j are estimated via least squares regression before the dividends announcements. Using OLS regression, the equation is run for each share in the entire study period. Return observations are included for five days before and after the event day. The abnormal stock return is calculated as the difference between the actual return a stock earns and its expected returns over a certain period of time. ARj,d = Rj,d – ERj,d Where the ARj,d is the abnormal return of security j on day d. Then, the daily returns are averaged across the market portfolio as: ARm,d= Where ARm,d is the weighted-average abnormal return portfolio for dividends increasing, decreasing and constant firms. Finally, the abnormal return volume AVj,d is the difference between the trading volume Vj,d of share j on day d, and the expected trading volume EVj,d, divided by the standard deviation of the trading volume over a certain time of period3. C. High and low growth industries: At the time of the investment, investors consider many factors, but the most important two factors according to scholars are risk and return which affect the investors' decisions (Pino, 1994). Growth opportunities of a firm are measured by using the market-to-book ratio. Following Fama and French (2001) the market-to-book ratio is measured as the market value of the firm divided by the total assets of the firm. The market-to-book ratio acts as a proxy to capture the industry growth following de Jong et al. (2008). Firth (1996) finds that an unexpected dividend increase (decrease) for one firm led to increase (decrease) of the stock returns of other firms in the same industry. Therefore, using the 4- digit SIC industry code excluding the utilities (SIC codes 4900 to 4949) and financial firms (SIC codes 6000 to 6999)", I calculated the median separately for each industry based on the market-to-book ratio of its firms. Next, I calculated the overall median (M) of all industries in the sample. Finally, I used the overall median (M) as a distinguishing tool between the high growth industries and low growth industries. If the industry's median is greater than (M) then it would be considered as a high growth industry, otherwise it considered as a low growth industry. Table 1 represent a summary statistic of the selction sample. IV. Result and Discussions Table 2 shows the abnormal return around different types of dividends changes using the naïve model. The result shows a significant increase in the abnormal return for low growth industry when there is an increase in dividends with an average of (0.13% and 0.17%) at the 5% confidence level in the announcement day and the day after, respectively. The decrease in dividends in high growth industry reflects a negative but insignificant abnormal return in the four days after the announcement day vs. a positive and insignificant abnormal return for the decrease-change in dividends within low growth industry. The negative price change reaction indicates that a dividend decrease conveys negative information to the public for the high growth industries more than it does in the low growth industries. This result is consistent with our hypothesis that, following a dividend increase, low growth industry shows a higher increase in abnormal return than high growth industry. It's also consist with earlier studies that show a positive abnormal return reaction after an increase in the dividends change. Finally, table 2 shows the share price reactions for the firms that didn't change the dividends payments for both industries. These firms didn't provide any additional information to the market. Therefore, they reflect insignificant market reactions for all days around the announcement day, except for day -2 in high growth industry. Moreover, table 2 shows that in both high and low growth industries the number of firms increasing its dividends is significantly higher than firms that cut their dividends or leave them unchanged. Figure 1 refers to the abnormal return around announcement dates. Consistent with Kalay and Loewenstein (1985) findings, on average, the return volatility is higher around announcements days. For firms with high growth opportunities, the stock price reaction to all kinds of announcements negative, positive and no change is more volatile and quickly adjusted to reflect the news. Figure 1: Abnormal return The stock price for high growth firms is affected more by dividend decreases than by dividend increases. Dividend decreases also show a negative abnormal return after the announcement day. For the firms that announce an increase or no change in their dividends payout, we see a significant decrease in the abnormal return before the announcement day which can indicate that the market cautiously looking for new information. Thus, following our hypothesis, high growth firms have more volatile reaction to information signaled by dividends. Firms with low growth opportunities, large firms, seems to have less volatility in their stock prices. A decrease in dividends negatively affects the stock price before the announcement day. The stock price absorbs the negative news quickly after announcement day for low growth firms showing no significant decrease in abnormal returns. Finally, these findings are consistent with the hypothesis that low growth firms have a positive relationship with abnormal return. The results in table 3 show a quick price adjustment for the new information signaled by the dividends announcements. The CAR of days -5 to -1 doesn't show much price adjustments for both high and low growth industries before the announcements day. On the other hand, the CAR of the period (1 to 5 days) after the event is significantly increasing with an average of .161% in high growth industry and .195% in low growth industry in the case of an increase in the dividends change. However, CAR in the same period (1 to 5 days) after the event is significantly decreasing when firms announce a decrease of dividends payments in high growth industry with an average of -.604%, while it's insignificant in the low growth industry. In the case of no change in dividends, high growth industry shows a significant decrease in the days prior the event day with an average of (-.133%), while it was insignificant in the case of low growth industry. Thus, these results are consistent with our hypothesis that low growth industry provide a higher abnormal return following a dividend increase. I also examined the trading volume reaction to the dividends announcements. There is a significant increase in the trading volume around the announcements days. The evidence of an excess of abnormal trading volume around the announcement days reinforces the impression of related information trading. Table 4 shows the abnormal trading volume around dividends announcements. The trading volume is positive and significant in the announcement day and the two days after in low growth industry when firms announced an increase or decrease in their dividends payment. Also, volume is positive and significant in day 1 and 2 after the announcement day when there is no change in the dividends payment. This significant and positive trading volume following a positive abnormal return shows investors' confidence even in the case of decreasing dividends payments in low growth industry. On the other hand, high growth industry shows a significant and positive trading volume in days 1 and 2 when firms increase or pay same dividends of 16.32% and 25.29%, respectively. However, the announcement of dividends decreases in high growth industry sends a bad signal to the market. Table 4 display a significant and positive trading volume in days 0, 1 and 2 after decreasing dividends of 21.75%, 56.12% and 46.17%, respectively. This high trading volume results in a negative abnormal return displayed in table 2. These findings are consistent with the hypothesis that the observed price reactions reflect information-motivated trading. Seven cross-section regressions been provided to get a better insight of which variables influence the abnormal return reaction to dividends announcements4. (i) For the whole sample around the dividends announcements, three separate regressions for both high growth and low growth industries are as follows: (ii) the sample of dividends decrease, (iii) the sample of dividends increase, and (iv) the sample of no change in dividends payments. The dependent variable is cumulative abnormal return on the event period -1 to 1. The independent variables are systematic risk (BETA), dividends yield (DY), firm size, the average log of volume, percentage change in dividends, abnormal trading volume, year. The choice of the independent variables follows prior research4. j,-1,+1 = Where Beta is the estimated systematic risk. DY is the dividends yield estimated as the annual dividends divided by the price one day before the event. The firm size is the log of market capitalization one day before the dividends announcement day. LOGVOL is the log of normal volume of the window event. DYOY_PERCENT is the year-to-year dividend percentage change. ABVOL is the percentage average abnormal trading volume for the pre-announcement period. YEAR is a dummy variable to control for year affect. Table 5 displays the seven regression results. Panel A shows the whole sample regression. The coefficients of DYOY_Percent and ABVOL are positive and significant indicating that dividends change is the main driver of the abnormal return around the dividends announcement dates. Another main driver variable that is significant is ABVOL which indicates that the market responds quickly to the corporate information conveyed by dividends announcements. Panel C displays the result for dividends increase in high growth industries. The annual percentage change in dividends is positive and insignificant. This result indicates that the greater increase in current dividends when compared to last year, the greater the share price increased. The result in Panel F confirms our expectations that dividend yield has a positive and significant effect on the cumulative abnormal return (t= 2.68). This result implies that a higher of dividends yield is more attractive to investors. Also, the ABVOL also has a positive and significant abnormal trading volume (t= 5.780) when firms announce increases in the dividends payout in low growth industries. The annual dividends change shows a positive and significant effect on the abnormal return for low growth industries which also supports our hypothesis. The empirical findings show that dividend announcements have a clear impact on the corporate market value. Moreover, the impact of dividends changes has an incremental value depending on increasing/decreasing dividends in firms with high growth opportunities. For firms with low growth opportunities the market absorbs the negative news quickly without much effect on the stock price. Finally, looking at the factors beyond this finding, the dividends yield and change in dividends payout are the most influential factors affecting the abnormal return around the dividends announcements dates5. V: Conclusion This paper examines whether the information revealed by dividend change announcements affects the valuation and abnormal return of high and low growth industries. There are many studies that examine the market reaction to dividend announcements. This paper is a first attempt to examine share price reaction and trading volume behavior in high and low growth industries. The results show a significant market reaction on the announcement days. My findings support the dividends signal hypothesis. I find a significant positive relationship between abnormal return and an increase in dividends announcements for both high and low growth industries. Also, there is a negative abnormal return following the dividends decrease announcement in high growth industry. However, the abnormal return displays a positive but insignificant appearance after a decrease in dividends for low growth industry, which reflect investors' confidence. The results show that return volatility is higher around announcements days, which is consistent with Kalay and Loewenstein (1985) findings. High growth industries display a more volatile reaction to information signaled by dividends. However, for firms in low growth industries, the prices have a less volatile reaction to dividends announcements. Moreover, it seems that stock price absorbs the negative news quickly after announcement days. These findings are consistent with the hypothesis that low growth firms have a positive relationship with abnormal return The trading volume is positive and significant on the announcement day in low growth industries for the case of increase or even the case of decrease in dividends. This significant and positive trading volume followed by a positive abnormal return shows investors' confidence. However, the trading volume is significant in the high growth industry only in the case of decreasing in dividends, and it's followed by a negative abnormal return. 1 Suwanna (2012), Firth (1996), 2 (Woolridge (1982), Asquith and Mullins (1983), Impson (1997), Howe and Shen (1998), Alangar and Bathala (1999), Fuller (2003) and Gurgul et al. (2003), Firth (1996) 3 Landsman and Maydew (2002), Dasilas and Leventis(2011) and Alves and Dos Santos (2008) used the same approach of calculating the abnormal return around dividends and earnings announcements. 4 Dasilas and Leventis (2011), Impson (1997), Fuller (2003), Wansley, Sirmans, Shilling and Lee(1991). 5 This is consistent with Dasilas and Leventis (2011), findings