Efficient Market Hypothesis - Essay Example

? Event Study for Efficient Market Hypothesis Ex-dividend Data Finance and Accounting Introduction Today, every media source provides uswith schemes in the stock market to get rich quick. Just follow this strategy, or here’s the hottest new stock guaranteed to make money. A large industry is devoted to providing information to investors so they can make decisions about their investments. An important issue in corporate finance involves the inferences the market draws from managerial decisions. Recent empirical studies document stock price responses to announcements of cash dividend and capital structure changes. A plausible explanation for these findings is that changes in the optimal dividend and debt levels stem from changes in, expected cash flows, and thus, signal a change in firm value. Efficient Market Hypothesis Researchers have developed a hypothesis known as the Efficient Market Hypothesis (EMH) which states that the market prices reflect all information known to the public. Market react to any new information available in the market immediately as reflected in stock prices rather than gradually adjust it. The term ‘efficient market’ was coined by Eugene Fama in 1965. He described an efficient market as a market where at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. The efficient market prices represent the intrinsic value of the securities. The EMH along with the Random Walk Hypothesis (RWH) flies in the face of Wall Street financial analysts. Financial analysts despise even hearing those terms. This is because these hypotheses suggest that there are no future predictions that can be made about how a market will behave. The suggestion that all the information known about past, present and future events is reflected in the current market prices means that the financial analysts are snake oil salesmen. This is why the EMH is such a controversial hypothesis. Types of Market Efficiency There are three primary categorization of EMH given by Fama (1970) according to the type of information reflected in the stock price – 1. Weak-form efficiency - Share prices reflect all past information and thus, rules out the possibility of predicting future stock prices on the basis of past price data alone. 2. Semi strong-form efficiency - A market is semi strong-form if share prices reflect all the relevant publicly available information. It also includes earnings and dividend announcements, technological breakthroughs, mergers and splits, resignation of directors, and so on. 3. Strong-form efficiency -Market in which share prices reflect not only publicly but also the privately available information. It is assumed that all the information is available to everybody at the same time. Even an insider who has private information about a company cannot earn abnormal profits in strong form of market efficiency. Literature Review Event studies have a long history, including the original stock split event study by Fama, Fisher, Jensen, and Roll (1969). Inconsistent evidence with the efficient market, hypothesis started to accumulate in the late 1970s and early 1980s. Evidence on the post earnings announcement effects (Ball and Brown, 1968, and Jones and Litzenberger, 1970), size effect (Banz, 1981), and earnings yield effect (Basu, 1983) contributed to skepticism for Capital Asset Pricing Model as well as market efficiency. According to the theory of information efficiency, security prices should reflect immediately all information available to the efficient capital market. As positive information and trading cost can be expected, this extreme efficiency hypothesis cannot be held. Fama (1998) in his survey studied the various event studies that intend to validate if the stock prices respond to new information. The events studied include announcements such as earnings surprises, stock splits, dividend, mergers, new exchange listings and initial public offerings. It was found that under-reaction to information announcement is as common as overreaction to the information. Healey and Palepu (1988) in their study found out that ex-dividend initiation are associated with positive stock price reactions while dividend omissions are associated with negative stock price reactions. Theoretically, stock splits should be cosmetic corporate events as they merely involve the breakup of one share into a certain number of shares and a reduction of a higher to a lower per share trading price without changing shareholders’ wealth and relative shareholdings. However, although early empirical studies find no abnormal performance after stock splits (Fama, Fisher, Jensen and Roll, 1969), most recent studies find a positively significant market reaction to stock split announcements. Stock splits do not appear to be as cosmetic as they should be. There have been several research works done by various researchers to test the impact of dividend declaration on the stock price. Szewczyk et al. (1997) in their research studied the cumulative abnormal returns for a sample of companies announcing dividend omissions. They concluded that there was no movement in the CAR in the days following the announcement. This implies that the stock price already incorporates the bad news. Various studies (Pettit (1976); Watts (1973, 1976a, 1976b); Laub (1976); Aharony and Swary (1980); Eades (1982); Asquith and Mullins (1983); and Brickley (1983)) have concluded that the stock market’s reaction to dividend announcements is efficient. Eades, Hess and Kim (1984) in their paper “On interpreting security returns during the ex-dividend period” concluded that stock prices, on average, react positively to stock dividend announcements that are uncontaminated by other contemporaneous firm-specific announcements. In addition, they document significantly positive excess returns on and around the ex-dates of stock dividends. Both announcement and ex-date returns were found to be larger for stock dividends than for stock splits. Purpose of the study The purpose of this study is to study the effect of ex-dividend declaration on stocks listed in New Zealand. We want to test whether investors gain any abnormal returns using such surprise information. This will help us in analysing the efficiency of the New Zealand Stock Market. Identification of the event The event we studied is the effect of ex-dividend announcement on the return investors get in the stock market. The event study approach Identify the event. In our case it is companies rolling out ex-dividend Identify the variable to be studied. We will study the variable returns Identify an “event horizon”. The event horizon is a set of days N before the event, and an equal number of days after over which we expect that the event could have had the major, if not the sole, impact on price. We have collected data for 90 days. 10 days (-5 to +5) have been removed to correct for any statistical anomalies that might be present in a single day of data Identify a set of firms K that have undergone this event. We have identified a set of 50 firms who have gone for ex-dividend in the recent past This is followed by calculating the alpha and beta for the firms as per the Capital Asset pricing model. This is followed by calculation of the expected return on each firm. From the expected return and actual return, the abnormal return is calculated which is the difference between the two. The formula for the same is: The abnormal returns for all the companies from -5 days to +5 days were added for each day to calculate the cumulative abnormal return (CAR). For each day, the CAR for each firm was added and divided by 50 to calculate the mean CAR. The t-statistic is calculated for each day’s CAR The t-statistic is then tested for significance to see if there is any impact on the returns of the announcement. If the t statistics are statistically significant, the event (ex-dividend announcement) affects returns The sign of the excess return determines whether the effect is positive or negative. Data The sample space comprises of 50 companies. We have collected data for 100 days before the event and 5 days after the event. The companies have been chosen randomly. The daily return of all these companies and NZX has been taken for the purpose of analysing the event. The data for the companies has been taken from http://banker.thomsonib.com/ta. Hypothesis The t-test is the appropriate test used here. The hypothesis is: a. Formulation of hypothesis: Null hypothesis H0: Ex-dividend announcement does not affect the gains realized by investors. Alternative hypothesis H1: Ex-dividend announcement affects the gains realized by investors. b. Level of significance: The standard levels of significance for t statistics are: Significance Level One Tailed Two Tailed 1% 2.33 2.55 5% 1.66 1.96 For the purpose of our training, we will use the significance level of 1%. Since we do not intend to test the direction of the difference of the impact on the stock price, therefore we use the two-tailed test. Analysis The table below shows the date wise mean cumulative abnormal return for all the fifty firms: Day CARi? -5.00 -0.13 -4.00 0.03 -3.00 0.20 -2.00 0.10 -1.00 0.30 0.00 0.35 1.00 0.37 2.00 0.43 3.00 0.38 4.00 0.03 5.00 -0.58 The same is displayed in graph below: As can be seen from the graph, the mean cumulative abnormal return does not vary significantly from 0 over the 10 day period. We can see that for the days prior to the dividend date, the CAR is generally more than 0 except for the first day. Similarly, the cumulative abnormal return is high till day +4 of the dividend date. It can be seen that just days after the dividend date, the cumulative abnormal return is high. It can be seen that the CAR is negative for -5 and +5 day of the dividend date. This shows that there is a bit of high abnormal returns after dividend date but the same dies over a period of time. The standard error of the data can be calculated as: The t-statistic for each day is shown in the table below: Day t-statistic -5.00 -0.27 -4.00 0.06 -3.00 0.41 -2.00 0.19 -1.00 0.60 0.00 0.70 1.00 0.74 2.00 0.88 3.00 0.78 4.00 0.07 5.00 -1.17 Our critical t-statistic is 2.55. We see that the t-statistic is less than the critical t-value. This implies that the t-statistic lies in the area of acceptance for all the days. Conclusion We can conclude from the analysis that though on the ex-date there have been signs of abnormal returns but the market stabilises immediately after the announcement and the effect fades off very quickly giving market very less chances to get abnormal returns. We can also infer that the New Zealand stock market is efficient and the stock price reacts to all the information available. Inferences/short comings The event horizon becomes an important variable affecting robustness: the longer the horizon, the noisier the inference. However, some of the event studies are only meaningfully applied over the longer term. References Aharony, J. and I. Swary, (1980). Quarterly dividend and earnings announcements and stockholders’ returns: An empirical analysis, Journal of Finance 35, pp.1-12. Asquith, P. and D. Mullins, (1983). The impact of initiating dividend payments on shareholders’ wealth, Journal of Business, 56, pp. 77-96. Ball, R., & Brown, P., (1968). An Empirical Evaluation of Accounting Income Numbers. Journal of Accounting Research, 6(2), pp 159-178. Banz,R.W., (1981). The Relationship Between Return and Market Value of Common Stocks. Journal of Financial Economics, 9(1), pp. 3-18. Basu, S., (1983). The Relationship between Earnings Yield, Market Value and Return for NYSE Common Stocks: Further Evidence. Journal of Financial Economics, 12. pp 129-156. Brickley, J.A., (1983). Shareholder wealth, information signalling and the specially designated dividend: An empirical study, Journal of Financial Economics, 12, pp. 187-210. Eades, K., (1982). Empirical evidence on dividends as a signal of firm value, Journal of Financial and Quantitative Analysis 17, pp. 471-500. Eades, K., P. Hess and E.H. Kim, (1984). On interpreting security returns during the ex-dividend period, Journal of Financial Economics, 13, pp. 3-34. Fama, E & French, K., (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96, pp. 246-273. Fama, E.F., Fisher, L., Jensen, M.C., & Roll, R. (1969). The Adjustment of Stock Prices to New Information. International Economic Review, 10(1), pp 1-21. Healey, P., and K. Palepu, (1988). Earnings information conveyed by dividend initiations and omissions, Journal of Financial Economics 21, pp. 149-175. Jones, C.P., & Litzenberger, R.H. (1970). Quarterly Earnings reports and intermediate stock trends. Journal of Finance, 25, pp. 143-148. Laub, P.M. (1976). On the informational content of dividends, Journal of Business, 49, pp. 73-80. Pettit. R.R. (1976). The impact of dividend and earnings announcements: A reconciliation, Journal of Business, 49, pp. 86-96. Szewcyk, S.H., Tstsekos, G.P., & Zantout, Z.H. (1997). Do Dividend Omissions Signal Future Earnings or Past Earnings? Journal of Investing, 6(1), pp. 40-53. Watts, R. (1973). The information content of dividends, Journal of Business, 46, pp. 191-211. Watts, R. (1976). Comments on ‘On the informational content of dividends’, Journal of Business 46, ppp. 81-85. Watts, R. (1976). Comments on ‘the impact of dividend and earnings announcements: A Reconciliation’, Journal of Business 49, pp. 97-106. Read More