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Secion 1: Abstract

Ordinarily, all information that relates to a firm is not immediately known by all stakeholders due to information asymmetry. Further, the rate at which this information is incorporated by the market is usually not immediate due to variations in investors’ sentiments and their reaction to news. These factors result in the differences in market efficiency, which varies from weak form, semi-strong form, and strong form. Announcements, such as dividends and earning announcements disclose some of the information that may be unknown in the market. This paper is a proposal for the evaluation of the effects of earnings and dividends announcements of on the performance of its securities for 150 companies in the NYSE. There will be a 31-day event window, 15 days post and pre-declaration. Tests for abnormal returns will be done during this period. The capital asset pricing model (CAPM) will be used in this study. The results will enable me to identify the relationship of earnings and dividend announcements with prices of securities in the NYSE, and also the form of market efficiency (EMH) of the NYSE market.
Keywords: stock, investors, market efficiency, investment, CAPM
 

Section 2: Introduction

A stock index is a mirror of all events happening in the market. Therefore, it is expected to reflect all available and new information that relates to the market. Unfortunately, it has been found that it does not always immediately reflect all the happening in the market. New data is continually entering into the market from various stakeholders such as the government, a company, economic reports, public surveys, and political statements, and since by nature or will there exist some degree of information asymmetry, not all information is instantaneously incorporated by the market. Announcements such as those on earnings and dividends can affect the prices of securities; however, the extent of the effect the announcements depend on investors sentiments, their speed of reaction, and the level of variation between the information that was available in the market and the new information.
According to the efficient market hypothesis (EMH), information is immediately incorporated into securities, and shown by the adjustments in their prices. In this regard, the EMH relates to how quickly and accurately the market incorporates new information. Simply, EMH is a relationship between stock prices and information, and it examines the rate at which this information is reflected in the security prices. If the relay and incorporation of all available and private information in the capital market is efficient, investors cannot outperform the market by adopting specific investment strategies. By definition, EMH implies that the use of fundamental or technical analysis cannot help investors’ make higher than market average returns than they would earn by having a randomly selected portfolio (Malkiel, 2003, p. 61). Since securities in an efficient market quickly adjust to reflect the new information, there can never exist undervalued stocks perfect market (strong-form EMH).
The efficient market hypothesis (EMH), was first developed by Fama (1970, p. 301), and is widely accepted in various academic circles and by professional investment managers. According to Fama (1970, p. 292), the stock market is efficient, and any information regarding individual stocks and the market as a whole is quickly reflected in the stock prices. Over the years, numerous theoretical and empirical studies have been conducted to support Fama’s hypothesis. Malkiel (2003, p. 60); Karz, (2011) all share a similar opinion in their studies, explicitly noting that “efficiency” represents a market situation in which all the relevant information will be fully incorporated into share prices at any given time. Despite the popularity of this model, studies conducted by Chaudhury (1991, p. 18); Kim, Nelson, and Startz (1991, p. 518) do not support the existence of market efficiency, even weak form of efficiency in some capital markets.
Since the EMH suggests that a security incorporates all information at any specific time, it has vast implications for investors and individuals who trade in securities. Usually, most investors trade under the notion that a security is underpriced and they have a chance of making a profit in the future. If the EMH model is correct, an investor can only make profits by chance and not as a reward for his/her market analysis. Fama (1960) suggests that there are three versions of the efficient market hypothesis (EMH), which are: weak form, semi-strong form, and strong form.

  1. In weak form efficiency, historical securities fully reflect the past information. This form of EMH implies that a person cannot fully interpret mispriced assets, which makes it impossible for anyone to earn additional profits based on the historical data.
  2. The semi-strong form efficiency claims that prices of financial assets demonstrate all the publicly available information. By examining the speed of adjustment of stock prices to newly revealed information, we can test this form of the efficient market hypothesis.
  3. The strong-form of efficiency asserts that information that is known to any participants, both public and private information, is reflected in the market. Further, in this EMH, the stock prices adjust to the market anticipated future developments, which mostly relies on insider information.

Given the complexity of the implications of the EMH in capital markets, I present a few scenarios that point out to its possible weaknesses.

  1. Although the EMH claims that investors cannot outperform the market average, some have proven to profit from market anomalies.
  2. All investors have different views on markets, which makes them have varying valuations of stocks.
  3. Stocks usually take time to act on new information, which gives investors who react to these data much quickly a chance to make gains.
  4. People are usually emotional in their decision making and prone to making errors. These issues affect how individuals invest, which in turn affects the market performance. Investors can be irrationally optimistic or pessimistic.

Section 3: Aims and Context of the Project

The aim of this project is to establish whether earnings and dividend announcements for firms that trade in New York Stock Exchange (NYSE) affect their stock prices. The information on how the company’s stock prices react to the announcements will enable me to know the form of the market efficiency of the NYSE. To examine the NYSE EMH, the market model, which is based on the capital asset pricing model (CAPM) will be used. Importantly, the information from this study will enable me to expand on previous studies of the effects of earnings and dividend announcements on stock prices.
Announcements, both financial and non-financial, have the potential of having some impact on the value of a company’s stocks. Since financial information such as earnings and dividends indicate the health and viability of businesses, it inevitably affects investor’s sentiments about the company and their willingness to hold or sell their securities in it. Since security prices are also subject to the demand equation; therefore, they are affected by the announcements on earnings and dividends. As such, stock prices act as both indicators of an organizations strength, profitability, and also investors’ sentiments on its future viability.
Although various studies have evaluated the effects of announcements on share prices, few have focused on examining both the effects of earning and dividend announcements on a single company’s security. This study will be particularly essential for investors who participate in the NYSE market in enabling them know whether they can outperform the market by strategically timing when to purchase or sell securities depending on earnings announcements.  Overall, findings of this research will give investors insight on opportunities that they can exploit, especially by identifying any market anomalies in the NYSE. In addition to the above benefits, this project will establish a basis for more study of effects of earnings and dividend announcements on the NYSE, and also in the identification of the strength of efficiency of this market.

Research Question

When a corporate event happens, it does not matter the nature of the announcements (good news or bad news), a considerable amount of information is released, and this information is utilized to determine how the market reacts. Therefore, the primary research question of this report is to test the efficient market hypothesis; more specifically, this paper will use the event study methodology to evaluate whether the NYSE falls into the semi-strong form efficiency category by assessing the effectiveness of the capital market regarding earnings and dividend announcements. A market model, which is based on CAPM will be used to calculate the abnormal returns of the event day as well as abnormal returns before and after the event day to determine whether there is a significant difference between these time windows. The use of two events (earnings and dividends) will enable this research to have a multilayered analysis of corporate events, which enable it to draw more accurate results. Quantitative analysis will be done on each event. Past literature on related findings will be used to explain the results of my analysis. Accordingly, my project will offer a comprehensive research paradigm to answer my research question.

  1. Does the New York Stock Exchange (NYSE) have a semi-strong market efficiency?
  2. Do announcements on earnings affect the stock prices in the NYSE?
  3. Do announcements on dividends have an effect on the stock prices in the NYSE?

Contribution to Knowledge

One of the primary importance of this research is expanding the existing knowledge on market efficiency. Through the analysis of the form of efficiency that exists in the NYSE, I will be able to know whether indeed the efficiency market (EMH) hypothesis holds. Further, the research will enable me to improve and enhance the events study model by identifying any research gaps or assumptions that should be rectified. Importantly, the improvement of the EMH model will lead to a more accurate analysis of efficiency in capital markets.
Since there have only been few studies on the NYSE, this research creates a platform through which investors can have a better view of how this market operates. By nature, this study will point out if there is any significant government or insider interference in the market that can hurt investors’ interest. Additionally, it will show regulators any inefficiencies that may be undermining their efforts to create a level playing field for all investors. In this regard, this research will enable investors and analysts to have a better view of the NYSE, which can inform them of its suitability for their investments.

Statement of Significance

Information from this research will invaluable in informing regulators on ways they can enhance their supervision of the NYSE. By definition, the EMH implies that the market is perfect; that is, there is no information asymmetry, and all relevant and available information is immediately reflected in the market. Unfortunately, such an ideal market is always difficult to attain given that insiders always have the upper hand when selecting investment portfolios. To create a level playing field, regulators require insiders not to participate in the trade or investment in specific stocks, especially where they have more information than the rest of the parties in the market. Therefore, the analysis of whether the NYSE has some form of semi-strong efficiency will also give information about any inefficiencies that may exist, which can harm investor’s interest.
More importantly, the study will inform investors on any investment opportunities that exist in the market. The knowledge of the form of efficiency in the Saudi Arabia capital market will enable investors to identify any opportunities that exist for them to make more than average returns in the market. In particular, the knowledge of whether the NYSE has a semi-strong market efficiency will enable the investors and analysts to know if this market reflects all publicly available information and how security prices adjust to reflect new information. Moreover, they will also establish whether their analysis can enable them to make more than average market returns. Noteworthy, in a semi-strong market, the market reflects all publicly available information, while in a strong-form EMH the market considers all public information and some future anticipated changes. Keite and Uloza (2005, p. 2) note that a semi-strong form of EMH provides investors with opportunities of profiting from market anomalies that may be due to the speed at which the market adjusts to reflect new publicly available information. Therefore, buying or selling securities before they reflect this information can enable an investor to make capital gains in his/her portfolio.
In this backdrop, my study examines whether the Saudi Arabia capital market, the NYSE, has a semi-strong form of efficiency. The findings of my research will be necessary for all stakeholders in the market, especially investors, companies, and regulators. The rest of the paper is organized as follows: the second section reviews related literature, the third section explains the methodology of this study, the fourth section concludes the analysis.

Section 4: Literature Review

According to the efficient market hypothesis, it is impossible for individuals to predict the changes in stock prices using available public information since the stocks are assumed to have already incorporated this information. The only factor that can change securities is only new information that can change investors’ sentiments about a value of a firm. This theoretical framework is based on the fact that in an efficient market, stock prices readily reflect all publicly available information, which results in investors not having a chance to outperform the market through timing or stock selection (Hamid et al., 2010, p. 127).
Despite being hailed for enhancing the study on market performance, the EMH has generated many controversies in financial and economic discussions. According to critics, the EMH is an idealistic model that fails to represent the realities in the real investment world (Mankiw, 2009, p. 109). Critics have given various arguments that contradict the EMH theory, and show that it does not hold up (Shleifer, 2000, p. 122; Barber & Odean, 2000, p. 18). Most of their arguments are based on behavioral science on finance. Overall, the critics suggest that stock prices are not information efficient since some investors in the stock market can be irrational in their reactions to new information and make wrong investment decisions on their portfolios (Dima & Milos, 2009, p. 3). In response, proponents for the EMH argue that even in cases where the stock market is not informational efficient it reflects information that is close to what can exist in a perfect market since irrational decisions of some market players are balanced by those of rational players (Yadirichukwu & Ogochukwu, 2014, p. 1203).

Efficient Market Hypothesis

The theoretical literature on the EMH, as presented by Fama (1991, p. 1579) is divided into three categories: studies on the predictability of returns, studies on events that may lead to changes in asset prices, and studies on private information (Dima & Milos, 2009, p. 3). The studies on the predictability of returns mainly aim at identifying whether investors and analyst can speculate about their future incomes based on current and past market performance. Research on events that can result in changes in assets’ prices examines how activities such as the distribution of dividends, change in capital structure, and investment decisions affect the performance of securities. Finally, research on private information assesses whether investors, in general, have private information that is not available to the public.
According to Fama (1991, p. 1981), it is not entirely possible to test the market efficiency without having an equilibrium model. In this regard, it is only possible to examine if the information is rightly incorporated into the market if there is an adequate model of price formation. Since markets do not become efficient on their own, this model suggests that all investors are rational. Damodaran (1996, p. 89) opines that an efficient market is one that has a self-corrective mechanism where all inefficiencies appear regularly and also disappear instantly when rational investors exploit these market anomalies.
Fama (1965, p. 37) asserts that three levels of efficiency can exist in a market; weak-form, semi-strong form, and strong form efficiency. The strong form EMH represents the most efficient market. In this market, all information that is relevant to a stock is quickly and accurately reflected in its price. For example, if there is a price anomaly in the market due to some privately held information, holders of this information will exploit this opportunity by either buying or selling some of their securities until the point where the market adjusts to reflect its optimal levels. Although this form of EMH is the most satisfying in a theoretical sense, it is impossibly difficult to analyze due to the difficulty in winning the cooperation of individuals that may have non-public information- insider dealers (Dima & Milos, 2009, p. 4).
The semi-strong EMH postulates that a market is efficient if it quickly reflects all relevant publicly available information. This model opines that markets quickly reflect new information through the price adjustments of securities once new information is released to the market. Although the semi-strong EMH lacks the intellectual vigor of the strong-form EMH, it has more empirical strength since it is less cumbersome to test.
The weak-form EMH is the weakest markets efficient. This form of EMH suggests that only historical prices of securities affect their current price. Therefore, investors cannot make a profit by using past information to predict future prices of stocks since this data is already incorporated in the current prices of stocks (Phan & Zhou, 2014, p. 61). The random walk behavior of security has been suggested as being an efficient model for testing the weak form EMH. Dima and Milos (2009, p. 3) assert that since information randomly appears in the market, changes that occur in an efficient market as a consequence of information should seem random. In this regard, the price movements in a weak-form efficient market are random, and the successive price changes are independent of one another.

Critiques of EMH

Most of the criticism on the practicality of the EMH is based on behavioral science regarding finance. In particular, the researchers argue that capital markets have irrational investors, and individuals are prone to making errors or being affected by human biases, which subsequently affect the performance of the market as a whole. In this regard, the market has a possibility of not accurately reflecting all available public information (Thaler, 2005, p. 51; Shefrin, 2005, p. 89-94). In particular, excess volatility has been shown to be much greater than is supposed to be in an efficient market. Since investors may over or under react to market-relevant information, the prices of securities may contain some anomalies.
A study by Bodie, Kane, and Marcus (2005, p. 89-96) showed that markets are affected by conservative bias since investors are usually slow in embracing beliefs and responding to new information or reacting. The EMH has also been shown not to hold since investors tend to under-react or over-react to financial news (Shleifer, 2000, p. 121-125; De Bondt & Thaler, 1987, p. 564). Noise traders, who are usually speculators, have also been found to make the bulk of trade investments. Due to their significant numbers and volumes of transactions that they create, over time, the market may fail to reflect relevant information based on facts, financial statements, and forecasts (Thaler, 1993, p. 44). The presence of information asymmetry also means that players in the market do not have equal information on the performance of companies (Hong et al., 2005, p. 13; Cohen et al., 2007, p. 2). There is also usually some sunk cost in any investment, which compels investors to continue in their endeavors regardless of newly received information in the market (Moon, 2001, p. 106). Further, the existence of the herd instinct, which implies that investors mostly focus on a specific set of securities and ignore others that have almost similar characteristics. This tendency can result in financial bubbles (Hong et al., 2005, p. 11). In worse cases, it may lead to financial contagions. Besides these discussed issues, there are also factors such as culture, seasonal effects, endowment effects, and whether that can affect an investor’s decisions.
Overall, Lo (2005, p. 32) using the adaptive market hypothesis concludes that markets are only efficient after considering behavioral alternatives such as competition and adaptation. Further, the researcher opines that the EMH is an idealistic model that can exist only if there are no capital markets imperfections such as taxes, limitations in cognitive and reasoning abilities among all investors, transaction costs, or institutional rigidities (Dima & Milos, 2009, p. 4). In practice, market imperfections exist. Lo (2005, p. 33) observes that people are not bounded in their degree of rationality, and they at times make choices that merely satisfy them, even if they are not optimal. The primary component of the adaptive market hypothesis as postulated by Lo (2005, p. 25) are:

  1. Self-interest is the primary motivation for individuals
  2. People make mistakes.
  3. People learn and adapt from past mistakes
  4. Competition is the primary driver for innovation and adaptation
  5. Natural selection shapes the market ecology

Whereas both Lo (2005, p. 28) and Fama (1960, p. 36) models agree that self-interests motivate individuals, the AMH and EMH models components are considerably different on investors’ characteristics. In particular, Lo (2005, p. 28) asserts that environmental conditions and investors distinct groups influence how they invest. Distinct groups of market participants as presented by Lo (2005, p. 28) refers to the type of investor (mutual fund, hedge fund, pension fund, retail investor, or market makers). Enriching the concept of market efficiency, Bowman and Buchanan (1995, p. 3) espouse that markets are neither efficient nor inefficient; instead, they can be viewed as a continuum running from the grossly inefficient market to a perfect market.
Weak-form of EMH has been found to exist even in developed economies. A study by Kim et al. (2011, p. 870) on the US equity market, the Dow Jones Industrial Index (DJIA), from January 1900 to June 2009 observed that the market has weak-form of EMH. These results, in particular, show that the performance of securities varies with time because of the changes in economic fundamentals and market conditions. Similarly, Sheikh and Noreen (2012, p. 516) observed that there is some weak-form EMH in the United Kingdom equity market. Using data from 1990 to 2008 of 50 United Kingdom mutual funds, the researchers established that fund managers are unable to predict the future behavior of various stocks. A study by Cavusoglu (2007) on the Athens Stock Exchange from 1999 to 2007, using the daily FTSE/ASE-20 stock price index, established that this market does not have weak-form of market efficiency (In Yadirichukwu & Ogochukwu, 2014, pp. 1207). The researcher accounted for heteroscedasticity when testing for the EMH. This study also examined for the change in economic conditions on stock returns and conditional volatility.
Research by Dima and Milos (2009, p. 4) to establish whether the Bucharest Stock Exchange has a weak-form of efficiency revealed that there is some informational asymmetry in the market. Accordingly, the Bucharest Stock Exchange does not have weak-form efficiency. The researchers used daily data from April 2000 to April 2009. A study by Barnes and Ma (2001) to examine whether China’s markets are of the semi-strong form efficiency showed that on the overall, they are not. The study analyzed how the market responded to publicly available information on the announcement of bonus issues. The database was from 1994 to 1998, and the markets that were considered were Shanghai and Shenzhen. The research showed that high bonus issuance resulted in more positive returns in the market and low bonus issues were characterized by low yields. Nonetheless, the study rejected the existence of semi-strong form efficiency for China’s markets.
Phan and Zhou (2014, p. 63) investigated the presence of weak-form efficiency in the Vietnam market using weekly returns from July 2000 to July 2013. The researchers’ analytical method entailed the examination of autocorrelation, variance ratio, and run tests. Since the results of random walk tests tended to reject the hypotheses of random walk and efficient market, the study established that the Vietnam stock market has a weak form efficiency. Noteworthy, Phan and Zhou (2014, p. 71) conclusion about Vietnam’s market efficiency appears to be controversial since the researchers point out that random walk of share prices in the analyzed data is acceptable for the period February 2009 to July 2013, and it gradually improved over the last ten years.
A study by Leigh (1997, p. 13) confirmed the presence of weak-form and semi-strong form of efficiencies for the Singapore share market. The researcher highlighted the relationship of the stock market behavior to the overall growth of Singapore economy. Using the Granger causality test, Leigh (1997, p. 21) established that the Singapore stock market has a systematic relationship to the overall economy of the country. Accordingly, the stock market is a significant indicator of the economy’s inter-temporal behavior. Wong et al. (2006, p. 124) also established that the Singapore capital market is efficient. The researcher analyzed the capital market from 1993 to 2005 and found that in the long run market anomalies in Singapore market disappear. In this regard, the country’s market is efficient, especially among savvy investors due to the ease in access of information and existence of appropriate technology for investment. Noteworthy, a study by Hellman et al. (2012, p. 12) on the Singapore Straits Times Index from 1993 to 2011showed the existence of the day-of-the-week and month effects. Importantly, the researcher noted that these anomalies presented investors with opportunities for devising strategies to outperform the Singapore market. This aspect, in particular, points to the possible lack of optimal efficiency in the Singapore Straits Times Index.
Udding and Khoda (2009, p. 89) established that the Dhaka stock exchange does not follow a random walk. The researchers used the Augmented Dickey-Fuller (ADF) test to analyze the existence of the random walk hypothesis of daily closing prices of stock of 23 companies in the pharmaceutical sector. A study by Dragota et al. (2009) for the existence of weak-form of information efficiency in the Romanian capital market using daily and weekly data revealed that most of the stocks in the Bucharest Stock Exchange are informationally efficient. The researchers’ used a multiple variance ratio, and their database was from 18 companies that were listed in the first tier of the Bucharest Stock Exchange. The data was also categorized into daily and weekly returns estimated through the use of indexes of the Romanian capital market.
Research by Vosvorda et al. (1998, p. 95) on the EMH in the Prague Stock Exchange from 1995 to 1997 rejected the weak form of market efficiency in the exchange. Kim, Shasuddin, and Lim (2011, p. 870) multiple variance ratio test of the stock market efficiency of nine stocks in Asia that were classified as frontier, emerging, and developed markets showed that that emerging and developed markets have weak form efficiency while frontier markets are not efficient. Research by Hamid et al. (2010, p. 126) using monthly prices from 2004 to 2009 to establish whether there was a weak form of market efficiency for fourteen Asian markets showed that there was no random walk in any of the markets. The researchers used a unit root, variance ratio, autocorrelation, runs, and Ljung-Box Q-Statistic tests.
Although empirical evidence supports the existence of EMH in some markets, a review of past literature shows that results of market efficiency are largely mixed and to some degree depend on the method used. This research proposal forms a basis for an analysis of the existence of semi-strong efficiency in the Saudi Arabia stock market. The findings of the research will be essential to portfolio managers who seek to identify assets the maximum risk-adjusted returns of their clients. Further, the information will be crucial for foreign investors seeking to invest in the NYSE.

Dividends

Financial announcements on dividends resulting in significant price changes in the price of a security. Various researchers, such as Aharony and Swary (1980, p. 3), note that managers at times use dividends as signaling tools on the firm’s performance. According to Bhattacharya (1979, p. 261), there is always some information asymmetry between a firm’s management and its stakeholders (investors, shareholders, suppliers); therefore, the issuance of dividends acts as an important signaling tool on the underlying performance of the organization. The researchers note that where there is information asymmetry, announcements on dividends help shareholders to know a firm’s profitability. This view is supported by Allen and Michaely (1995, p. 794) who note that the decrease or increase in dividends issued notwithstanding, dividends are the least costly tool of signaling investors on the firm’s performance. From one view, dividends can indicate that a firm anticipates to continuously earn profits in the near future. In yet another view, the issuance of dividends is an indication that a firm does not anticipate to have any profitable investment in the future. Therefore, instead of holding the company’s incomes without using them in gainful ventures, it prefers to issue this cash as dividends. Therefore, the impacts of dividend announcements is largely inconclusive since it signals that a firm will be enjoying profitable times or it will not have any significant profitable venture in the future.
According to Graham and Dodd (1951, p. 245), investors prefer to be given dividends than these funds being re-invested in the business. This view is based on the fact that the issuance of dividends reduces managers’ agency costs. Miller and Modigliani (1961), on the other hand, opine that in cases were there no transaction costs and taxes, the issuance of dividends do not affect investor’s view of a firm. Linter (1956, p. 100) alleges that firms usually issue dividends when they are convinced that a firm will continue enjoying positive performance in the future. Therefore, he suggests that the announcements of dividends is an indication that a business will be profitable, and it acts as an indicator to investors of this positive prospects. A study by Dasilasa (2004, p. 118) established that normally, an increase in dividends issued is usually followed by a similar increase in stock prices. They also established that stock prices always decreases when there is a similar fall in dividends or no dividends at all. Besides observing the relationship between dividend increases and decreases, Dasilasa (2004, p. 112) further observed that for companies that have steady dividends, announcements do not result in significant movements in their stock prices.
The issuance of dividends is also associated with a reduction in agency costs of a firm, which can effectively lead to an increase in the prices of securities. Regarding agency costs, the management of any organization usually act as agents of the shareholders’ assets; therefore, the issuance of dividends results in a decrease in assets they are managing and subsequently a decrease in their agency costs. Whereas dividend issuance results in a decrease in agency costs, it is important to note that in most organizations, dividends account for a very small percentage of the value of the assets in the firm. From this perspective, Black (1976, p. 170) notes the issuance of dividends leads to a reduction in an organization’s agency costs.
Further, Akbar and Baig (2010, p. 104) observed that high dividends payout-ratio results in a greater decrease in agency costs and subsequently leads to an increase in stock prices, the reverse occurs when there is a reduction in the dividend payout-ratio. These findings are supported by Lonie et al. (1996, p. 35) who observed that there is a relationship in the response of investors to the increase or decrease in the dividend payout ratio in the United Kingdom. In particular, high dividend payout-ratio increases the demand for stock while low dividend payouts lead to a decrease in their demand, which subsequently affects the prices of these securities. Docking and Koch (2005, p. 23) also found that dividend announcements increase the rate of volatility in the stock market.
A study by Mollah (2001, p. 6) to establish the effects of dividend announcements in the Bangladesh stock exchange, showed that dividends announcements do not result in any significant effects in the prices of securities this market. Moreover, the haphazard movement in securities after announcements showed that dividends did not act as signaling tool in the Bangladesh stock market. In particular, the prices of securities decreased after an increase in dividend payout-ratio, and also after a decrease in dividend payout-ratio or the retention of the payout ratio. Based on his findings, the researcher suggested that there may be some degree of insider trading in the market.
Stock prices were also found to increase days before and after announcements of dividends (Aamir and Zullfiqra, 2011, p. 72). A study by Andres et al. (2011) also showed stock prices in the German stock market significantly increase after dividend announcements. Majanga (2015, p. 101) attributes the increase in stock prices to their increased demand. Interestingly, Chowdhury (2005, p. 49) established that dividends are not efficient indicators of a firm’s future performance. The researchers used the cumulative market-adjusted abnormal returns (CAAR) and the daily market-adjusted abnormal returns (MAAR) of 137 companies in the Dhaka stock exchange. In particular, the MAAR was not statistically significant on the date when dividends are announced. Finally, the CAAR established that the net loss for investors was more than the net benefits after announcements of dividends.

Earnings

The financial results of any organization reveal important financial and non-financial information that affects stakeholders’ perception of the company. The disclosure of the company’s earnings is usually just a part of the information released in financial reports. Ordinarily, audited financial reports, which must be published for every public company, indicate an auditor’s opinion on the financial health of a company. Mlonzi, Kruger, and Nthoesane (2011, p. 145) note that the release of financial reports, which have the income statements, cash flow statement, balance sheet, and other necessary financial disclosures gives investors an opportunity to focus on the future performance of an organization.
Although there has been extensive research on the impact of earnings announcements on stock prices, the findings have been largely inconclusive (Angelovska, 2017, p. 650). Researchers allege that the information on the earnings of a company is used for different purposes depending on the interests of the stakeholder. According to Corrado (2002, p. 565), the information on the financial states is used for decision making by insiders. Some of the decisions made by insiders include knowing when to buy or sell their security and also how to manage their portfolio. Similarly, the information on a company’s earnings informs all stakeholders about the value of the company (Black, 1980, p. 21). Further, other information in the financial report informs stakeholders on the future prospects of the business.
Managers have also been found to use earnings as a signaling tool (Aharony & Swary, 1980, p. 3) note that just like dividends, managers use earnings as a signaling tool. Ordinarily, a report of a steady increase in earnings, or a higher than average industry earnings indicates that an organization has positive future prospects. This type of information can increase the demand and price of the organization’s stock. Beaver (1968, p. 69) notes that the fact that prices of securities change after an earnings announcement is an indication that these reports contain content that affects the valuation of a company. In support, Angelovska (2016, p. 12) notes that since investors are rational persons that intend to maximize their utility, they only make changes in their trading patterns when new information that alters the share value of a firm under consideration is released.
Beaver et al. (1979, p. 319) suggest that the variations between the actual earnings and the predicted earnings are usually due to the association between unsystematic security returns and forecast errors. Further, Atiase (1985, p. 23) notes that the market capitalization of a firm also affects the degree of pre-disclosure of information on a company’s performance. Chambers and Penman (1984, p. 23) alleges that there are higher abnormal returns on earnings announcements on smaller firms, which have low capitalization, than larger firms that have high capitalization. Considering that investors are rational persons, as suggested by Angelovska (2016, p.12) and only react to the extent that new information affects the value of the market, Chambers and Penman (1984, p. 23) opinion suggests that smaller firms have a tendency of not disclosing market-relevant information when compared to the large ones.
A study by Landsman and Maydew (2012, p. 800) to establish if there was a variation in the content of earnings announcement depending on the season (1st quarter, 2nd quarter, 3rd quarter, and final report) showed that there is no variation in the information disclosed to shareholders. Joy et al. (1977, p. 210) note that prices of securities adjust only in cases where companies have highly favorable quarterly earnings. Although forecasted earnings always vary from actual earnings, even in the case where there is significant access to information, analytical studies using regression analysis by Ahmed et al. (2009, p.225) did not identify any specific reason for this variation. The researchers used the logistic regression models and analysts forecast data from 1983 to 2004 to determine the share of analysts forecast revision pairs of quarterly earnings announcements that exhibited Kandel and Pearson differential interpretations patterns. According to Ahmed et al. (2009, p. 225), the differences between forecasted earnings and actual earnings can be significant reduced by reducing the cost of acquitting new information, enhancing the quality of pre-announcement news, and ensuring variables that exist in the actual business are considered in the forecast.
Capital markets have also been found to have a post-earnings announcement drift (PEAD), which is also called the standardized unexpected earnings (SUE) effect (Landsman and Maydew, 2012, p. 799). In this case, abnormal returns are found to be present in the stock market for some days after the announcement of earnings, or during other important events. The estimation of the level of drift in earnings is usually based on a simple basic concept, estimating the earnings surprise. In this case, analysts identify the difference between the actual earnings and the forecast of the earnings, divided by a deflator. Interestingly, most studies only use time series to predict the earnings (Sehgal & Bijoy, 2015, p. 26). Past explanations for the occurrence of PEAD have attributed it to slow reactions to information content of earnings, slow reaction to information on earnings, shortcomings in methods used, risk measurement (Abarbanell & Bernard, 1992, p. 184; Jacob et al., 2000, p. 330; Livant and Mendenhall, 2006, p. 180).
A study by Chen et al. (2005, p. 307) on the effect of earnings announcement in Mainland China showed that companies that make early announcements experience more changes in their prices and a longer PEAD. The researchers noted that this behavior occurs because early announcements surprise the market, resulting in great trading volumes and price reactions. On the contrary, late announcements have a low impact on prices and volume since they are more predictable. In this regard, the information asymmetry is greater in early announcements than the late ones.
Livnat and Mendenhall (2006) examined the data from Charter Oak Investment Systems Inc. for all their firms that had data from 1987 to 2003, to establish whether there were differences in the magnitude of patterns of abnormal returns formed when assessing the variations in the level of surprise in various portfolios. From their analysis, they concluded that PEAD was larger when determining surprise using analyst’s forecasts from I/B/E/S than when using a time series data. This research established that the variations in the analysts’ forecasts and the time-series models were the cause of the differences. Interestingly, the researchers noted that the two types of surprise were capturing different forms of mispricing since analysts forecast resulted in return patterns in future earnings announcements that differed from those obtained using the time-series model.
Research by Cao and Narayanamoorthy (2011, p. 43), established for low forecaseted earnings, there observed PEAD is always high. They also established that the degree of PEAD of a security in a capital market depends on both the magnitude of the earnings surprise and its persistence. Taken together, their conclusions imply that stocks that have high abnormal returns have low trading frictions.

New York Stock Exchange (NYSE)

The NYSE is located at 11 Wall Street, Lower Manhattan, New York City, New York, and is by far the largest capital market in the world in terms of market capitalization. NYSE is owned by Intercontinental Exchange, which is an American holding company (NYSE, 2018). There have been several studies on effects of announcements on the performance of securities in the NYSE. These include studied by Asquith and Mullins (1983, p. 79) on dividend announcements of 168 NYSE listed companies from 1954 to 1963. Research by Woolridge (1983, p. 1608) on effects announcements of a dividend increase in 317 firms and dividend decrease in 50 firms. These are just part of the many studies done on firms traded in the NYSE. My research extends previous studies on the effects of dividend and earnings announcement of companies in the NYSE. In this project I will focus on 150 companies traded in the NYSE, which will enable me to learn how securities in the NYSE behave during the event window of the dividend and earnings announcements.

Hypothesis

H0: There is a positive correlation between share prices and a firms earnings announcements.
H1: There is no correlation (positive or negative) between share prices and a firms earnings announcements.
H0: There is a positive correlation between share prices and dividend announcements.
H1: There is no correlation (positive or negative) between share prices and dividend announcements.

                        Section 5: Approach and Methodology

            In this study, I will use the event study method to examine whether dividends and earnings announcements for 150 companies affect their stock performance in the New York Stock Exchange. This information will be essential in enabling me determine how securities in the NYSE perform after announcements. In addition, it will enable me know the form of EMH for the NYSE. The capital assets pricing model (CAPM) is the most common way of analyzing an organization’s stock (Bosch & Hirchey, 1989; Hovav & D’Arcy, 2003, p. 99). This paper will consider dividends and earnings announcements that occurred from July 1, 2016, to March 31, 2018. Using CAPM, the model abnormal returns will be estimated and averaged to get the Average Abnormal Return (AAR).
The Cumulative Average Abnormal Returns (CAAR) is the sum of all the AAR’s. Campbell et al. (2007, p. 91) note that the main benefit of using the CAPM model over other models to examine for the EMH is because it is an economic model; therefore, it is more precise when calculating returns since it uses economic restrictions. CAPM is based on the required rate of return for a security given its risk and average market performance. CAPM can be represented as shown below.
Rit=Rft + βi * (Rm-Rf)
ARit= [Rit- {Rft + βi * (Rmt – Rft)}]
Where,
Rft = Risk free return (364 day T-bill return),
βi= Market risk (systematic risk),
Rmt= Market index return,
Rit= Expected return of security ‘i’ on time ‘t
Data Selection
A sample of daily prices stock prices of 150 companies will be used in the study. The estimated period will be 180 days before the announcement and it will end 15 days to the announcement date ( from t= -180 days to t= -15 days). This period is similar to that used by Bosch and Hirchey (1989, pp. 71). The estimate parameters of the actual realized returns in the London Stock Exchange market index is used to predict the normal returns of the stock for periods before and after the event.
This study has focused on six separate events for 21 day period around the event announcements. These events are:

  1. Ten days before the announcement and one day to announcement date (day t= -10 to t= -1).
  2. Announcement date to 10 days after announcement (day t= 0 to t= +10)
  3. Two days after announcement to ten days of trading after announcement (day t= +2 to t- +10)
  4. Ten trading days before and after the announcement (day t= -10 to t= +10)
  5. Five trading days before and after the announcement (t= -5 to t= +5)
  6. Three trading days before and after the announcement (t= -3 to t= +3)

Noteworthy, the announcement date of the event is represented by 0. There are two main categories covered by the classification: the complete event window and overlapping periods. The complete event window are on non-overlapping and sequential segments, which are the pre-event period (-10, -1), announcement period (0, +1), and post-announcement period (+2, +10)) Overlapping periods are days -10 to +10, -5 to +5, and -3 to +3. Importantly, the overlapping periods were essential in enabling me to examine the effects of cumulative abnormal returns for the pre-event, announcement period, post-event, and symmetrical overlapping periods (Dangol, 2008, p. 93). The parameters of the equation are shown in the figure below.
Parameter Estimation and Events Periods
The normal returns of the six periods in the event (-10, -1), (-10, +10), (-5, +5), (-3, +3), (0, +1), and (+2, +10) are predicted using the coefficient estimates from the regression equation below.
Rit = αi + βi Rmt + eit
Where,
Rit = the return of stock i on day t = [Price it – Price it -1]/ Price it-1
Rmt = Market return on day t, the average of returns of all firms in the market index
eit= The error term of stock i on day t
αi and βi = firm independent coefficients that will be estimated.
Diagrammatic Representation of the Events

 
 
 
T= –180 days           T= -16 days         T=-15 days                                  T= 15 days                      T3
 
      Estimation Window                        Event Window                                 Post Event Window
Estimation window (T0-T1): It is used to establish the normal behavior of the stock. In most cases, the market model is used to establish the normal behavior.
Event window (T1-T2): Through the use of the coefficients, αi, and βi, the event window informs a researcher the following information:

  1. Whether there was a leakage in the announcement or it was anticipated.
  2. The post-announcement The length of time it takes for an event’s information to be absorbed by the market.

Post-event window (T2-T3): It is used to investigate the long-term effect of an organization’s performance after an event.
The prediction errors in the event period refer to the estimates of the abnormal returns (AR), and the market model is used to evaluate these errors. For a firm (i) on event day (t), the prediction errors (PE) can be assessed as shown below:
PE it =Rit – (αi + βi Rmt)
The null hypothesis to be tested is that the sample average of market model cumulative prediction errors (or cumulative abnormal return) is equal for all event periods. In this regard, for a sample of N securities, the sample mean predictor error for any day t can be represented as follows:
The sum of the sample mean predictor errors give the cumulative predictor error as shown below.
In this model, T1 and T2 respectively show the start and end days if sample-specific event periods for the 21 days. For example of over the range t= -3 to t= 3 event period. The t-statistic for the predicted error is derived by dividing the predicted error with its standard deviation.
Noteworthy, the cumulative predicted error is assumed to have both cross-sectional and serial independence in the null hypothesis. Further, there is an underlying assumption that the interval test statistic for each sample and holding period of T days is unit normal. The t-statistic for the CPE can be derived as shown below.
A non-parametric binominal statistics were used to calculate the significance of the daily abnormal returns. This statistic is as shown below:
Where,
A= number of positive prediction errors.
E= the expected number of positive errors (N*P).
N= number of observations
P= Percentage of positive predicted errors
Generalized Significance Test
This test will examine if the securities that have a positive cumulative abnormal return in the event window exceed the returns that would be present in the absence of the event (earnings and dividend announcements). The sign test evaluates the null hypothesis so that there is no significant difference between the number of positive and negative average abnormal returns (AAR). This test is done using a binomial equation by examining the total number of positive periods in an event to the total number of days of the event window (N). The test is as follows:
Jsign = [(N+/N) – 0.5]*N0.5 where N (0, 1)
0.5= Expected proportion of positive abnormal returns
In this research, a p-value of five percent was used to test for significance level. Noteworthy, the above binomial statistics is more conservative than the t-statistic, and accordingly does not require the normality assumption.

Section 6: Preliminary Suppositions and Implications

Using CAPM model, the abnormal returns will be calculated. The nature of the abnormal returns, either positive or negative will indicate how the securities react to each announcement. In the case of dividend announcement, more positive abnormal returns than the negative ones in the event window will indicate that declaration of issuance of dividends results in an increase in the market price of securities. This information will imply there is a positive correlation between dividend announcements and stock prices. Similarly, for earnings announcements, the presence of more positive abnormal returns than the negative ones in the event window will show that there is a positive correlation between earnings and security prices. The length of the PEAD will show the form of the market efficiency of the NYSE.

Section 7: Conclusion

In the market efficiency theory, a semi-strong market is one that reflects all publicly available information. Market anomalies, which mostly occur due the variation in investors’ interpretation of information or reaction to this information provide individuals with opportunities of making profits during periods of announcements. This project will provide information on how the NYSE reacts following the announcements of dividends and earnings. More importantly, the information from this research will give investors essential insight on how they can exploit the NYSE market during periods of these events (dividends and earnings announcements). Finally, the assessment of how fast the NYSE incorporates information of these events will enable me to establish its form of market efficiency weak, semi-strong, and strong).

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