Behavior Around Earnings Announcement Events For Emerging Markets - Free Essay Example

Sample details Pages: 17 Words: 5216 Downloads: 9 Date added: 2017/06/26 Category Statistics Essay Did you like this example? 1. INTRODUCTION 1.1 Background of Research Question Stock prices show a tendency to behave in a manner not consistent with what current finance theory proposes or expects. This gap may be the result of flawed assumptions presently used as a basis in existing theory. Don’t waste time! Our writers will create an original "Behavior Around Earnings Announcement Events For Emerging Markets" essay for you Create order Conventional modern finance theory rests on the assumption of investor rationality. Efficient market hypothesis (EMH), representing an integral part of conventional finance theory, further assumes security prices reflect (to varying degrees) all available information as processed by rational investors. Modern portfolio theory (MPT) suggests[1], a stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s price represents the present value of future expected cash flows and therefore, is dependant on investorà ¢Ã¢â€š ¬Ã¢â€ž ¢s expectations of estimated forecasts of earnings growth rates into the future. Actual short-term stock price behavior indicates anomalies and significant divergences of prices away from fundamental intrinsic values, long-term averages, or expectations as implied by MPT. Behavior finance takes the approach of understanding these price anomalies through a study of cognitive and emotional biases. This thesis investigates the possibility of investorà ¢Ã¢â€š ¬Ã¢â€ž ¢s making mistakes (through irratio nal behavior) in their forward expectations of future corporate cash flows, resulting in short-term overreaction to earnings information releases due to influence of representative bias (a cognitive bias). This proposal attempts to examine the existence, relationship and, impact of overreaction as a determinant of securities price behavior in emerging markets of Far East. The aim of this study is to discover representative bias, a tendency of investors to overweigh most recent information in making future forecasts, as one possible cause leading to overreaction in securities prices. This thesis tests investor responses to corporate earnings announcements, specifically surprises, to determine overreaction behavior and to identify representative bias as the cause of such overreaction. The results may contribute, by offering a missing piece of the puzzle, of understanding stock price behavior (towards the search for a unified theory), into existing research work for behavior finance. In addition, a better understanding of what drives stock prices would be a highly useful forecasting and policy tool for participants concerned with asset pricing. 1.2 Motivation for Research The field of behavior finance focuses on the question; what drives investor behavior?. It is divided into two main groups. Cognitive and emotional biases, which are further sub-divided into two sub-groups, individual and collective biases. Behavior finance has been seeking to discover the causes of investor irrationality within the investment decision-making framework. Significant empirical and theoretical studies have been conducted, which suggest cognitive and emotional biases affect investor rationality. Indeed, the field of behavior finance directly challenges the conventional finance framework, which uses within its paradigm the assumption that investors are rational decision makers, and securities prices reflect all available information (EMH[4]. According to Fung (2006), it seems clear that EMH and CAPM[5](pillars of the current financial theory), despite mounting evidence against their validity, remain widely in use. One reason for this is the fact that these models cannot be empirically falsified due to their dependence on layers of assumptions, which support each other. The other reason is a lack of an alternative asset-pricing model taking cognitive biases into consideration, which does not exist so far. Behavior finance offers just such an alternative, and after observing price anomalies as a trader in the financial markets, I have become interested in pursuing empirical work in this direction to understand and discover a better way to price financial assets. Furthermore, only limited research exists for capital markets covered by this thesis namely Malaysia, Thailand, and Singapore, despite the fact these markets have outperformed western markets recently and continue to offer potential for future growth. 1.3 Statement of Problem This thesis focuses on the following problem: à ¢Ã¢â€š ¬Ã…“What is the relationship between representative bias and overreaction, as it relates to individual as well as a series of earnings surprise announcements, on investor behavior in the stock markets of Far East?[6]à ¢Ã¢â€š ¬? 1.4 Research Questions Objectives This proposal consists of three components. First, the study aims to discover existence of investor overreaction (derived and tested from stock price behavior) in the stock markets of Malaysia, Thailand, and Singapore based on overreaction hypothesis (ORH) as proposed by Thaler (1985). Thereafter, the second objective of this thesis is to test for overreaction in response to corporate earnings surprises (positive and negative). Third and last objective of the study is to determine if representative bias (cognitive bias) is a source of this investor irrationality, in response to earnings surprises, as demonstrated through price behavior in the respective stock markets. In other words, to contribute an answer to the key question behavior finance is seeking; what drives investor behavior in the stock markets?, this study tests emerging stock markets of far east for investor overreaction. Subsequently, this thesis focuses on representative bias as one cognitive attribute of investor behavior, which may cause overreaction to occur. Following are some of the research questions this study will attempt to answer. Research Questions: This study attempts to answer the following research questions: Research Question 1: Does investor overreaction exist in emerging stock markets? Research Question 2: Do investors overreact to positive earnings surprises? Research Question 3: Do investors overreact to negative earnings surprises? Research Question 4: Is representative bias present during investor overreaction to earnings surprises? Research Question 5: Does representative bias cause investor overreaction when earnings surprises are positive? Research Question 6: Does representative bias cause investor overreaction when earnings surprises are negative? Research Question 7: What is the relationship between representative bias and overreaction as it relates to a series of earnings surprise announcements, both positive and negative? 1.5 Research Significance The motivation behind this research is to contribute a better understanding of determinants of stock pricing in the context of investor decision making. The results of this study will be useful in furthering current empirical research on cognitive biases affecting stock price behavior, specifically investor overreaction and representative heuristic, (as it relates to earnings surprises), as well as provide useful understanding for investment decision making, forecasting, and policy making for financial market participants in the asset management field. In addition, contribution towards a piece of the stock-pricing puzzle, as well as further research questions may also be discovered. 2. LITERATURE REVIEW 2.1 Cognitive Biases Overreaction Hypothesis (ORH) Behavior finance seeks to understand effects of psychology on financial behavior. However, a unified model, which can replace the conventional mainstream models such as the efficient market hypothesis and CAPM (capital asset pricing model), has yet to be discovered, Fung (2006). Keynes (1973, original publication 1936) wrote in his General Theory: à ¢Ã¢â€š ¬Ã…“ Day-to-day fluctuations in the profits of existing investments tend to have an altogether excessive, and even absurd, influence on the marketà ¢Ã¢â€š ¬? (1973, pp. 153-154). This became the starting point for a study on overreaction by De Bondt and Thaler (Fung 2006, p.29). Keynes remark infact implied the possibility of systematic mispricing of securities by investors. Indeed, this argument led to directly challenging the efficient market hypothesis, a mainstream concept used for financial asset pricing invented by Fama (1970). Fama created an empirically testable model to price securities based on this concept called the à ¢Ã¢â€š ¬Ã…“fair gameà ¢Ã¢â€š ¬? which implied the notion that markets cannot have expected returns in excess of equilibrium expected returns (ibid., p.385). This particular notion is questioned in De Bondt and Thalerà ¢Ã¢â€š ¬Ã¢â€ž ¢s, 1985 paper, proposing instead the stock market overreaction hypothesis (ORH). They suggest, stock prices fluctuate from their intrinsic values (PV of expected future cash flows of the firm) due to optimism and pessimism prevailing amongst investors. In addition, De Bondt and Thaler (1985) suggeste d two other hypotheses: 1. à ¢Ã¢â€š ¬Ã…“Extreme movements in stock prices will be followed by subsequent price movements in the opposite directionà ¢Ã¢â€š ¬? 2. à ¢Ã¢â€š ¬Ã…“The more extreme the initial price movement, the greater will be the subsequent adjustment. Both hypotheses imply a violation of weak form market efficiencyà ¢Ã¢â€š ¬? (1985 p.795). In other words, their hypothesis suggested the existence of the possibility of earning excess returns above equilibrium returns. This may be accomplished by investing in stocks, which have performed poorly relative to the average (a new contrarian strategy). In addition to casting a doubt on the EMH, De Bondt and Thalerà ¢Ã¢â€š ¬Ã¢â€ž ¢s paper (1985) also brought into question the validity of the CAPM (Fung, 2006). According to CAPM, an assets return is a function of the asset risk premium and the risk free rate. In other words, higher the systematic risk (Beta) of an asset, higher the assets return (represented by a linear relationship between risk and return). However, the findings of De Bondt and Thaler discovered low Beta (low systematic risk) portfolios (L) generating higher returns and high beta portfolios (W) producing low returns. This result contradicts the basic risk-return relationship as proposed by CAPM. Fama and French in their 1992 paper were the first to confirm this CAPM contradiction through empirical study based on discovering the (positive) relationship between size and beta. They suggested CAPM did not fully measure and adjust for the higher risk of smaller(size) firms. In summary, empirical research has discovered that consistent anomalies exist between risk-return relationship as proposed by the widely used EMH and CAPM (the traditional financial theory paradigm). However, no comprehensive theory exists to explain why some stocks do better than others. Lakonishok et al. (1994) confirm in their paper that value stocks outperform glamour stocks. Thereby they suggest cognitive bias as a possible explanation for this anomaly. à ¢Ã¢â€š ¬Ã…“Putting excessive weight on recent past history, as opposed to a rational prior, is a common judgment error in psychological experiments and not just in the stock marketà ¢Ã¢â€š ¬? (ibid., p.1575). It seems clear that EMH and CAPM (pillars of the current financial theory), despite mounting evidence against their validity, remain widely in use. Behavior finance seems to offer an alternative to the current financial theory, and therefore it is imperative to pursue empirical work in this direction in order to understand and discover a better way to price financial assets. 2.2 Investor Overreaction Earnings Surprises Research in Behavior Finance has taken different approaches to discovering cognitive biases and their impact on asset pricing. Odean (1998) and Daniel, Hirshleifer and Subrahmanyam (1998) focused on overconfidence, while Hong and Stein (1999) investigated mispricing by positive feedback trading. De Bondt and Thaler (1985) have empirically investigated overreaction, and concluded investors overreact to information. Their research focused on NYSE stocks and cumulative returns for three years (event window). They concluded specifically that stocks with previous abnormally low returns performed better than those with previous abnormally high returns. This return reversal indicated investor reaction to be over-weighted in response to information, which was later corrected in prices over the longer term. The overreaction anomaly has been empirically established in finance through multiple studies. Kaestner (2006) points out that Poteshman (2001) tests overreaction in the options market; Cutler, Poterba, and Summers (1991) for gold market; Chui, Titman and Wei, (2000) and Bhojraj and Swaminathan (2001) for international stock markets. In addition Chopra, Lakonishok, and Riter (1992) as well as De Bondt and Thaler (1987) have confirmed overreaction in stock markets. The main gap, which remains in empirical research, is establishing the determinant or driver of overreaction (Kaestner 2006, pp.3). This particular cognitive bias has recently been tested as a driver of overreaction in a few markets only. Kaestner (2006) further points out that Poteshman (2001) has researched for representative bias and overreaction in the options markets through investor responses to changes in variance of the underlying asset. De Bondt and Thaler, (1985 and 1987), Chopra, Lakonishok, and Ritter, (1992) look at representative bias as the potential driver of overreaction basing their studies on current earnings, forecasted changes in earnings and past performance without directly testing for it. Kaestner (2006) directly tests for this link between representative bias and overreaction for NYSE stocks related to earnings surprises. 2.3 The Representative Heuristic Representative heuristic belongs to the family of cognitive biases within the field of behavior finance. Tversky and Kahneman (1974) suggest this bias may affect an investorà ¢Ã¢â€š ¬Ã¢â€ž ¢s decision-making framework by causing the investor to over weight most recent fundamental information regarding a stock while making estimations of future earnings forecasts. Because of representative bias, investors may over/under estimate a stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s intrinsic value[7]resulting in subsequent anomalous security price behavior. According to Tversky and Kahneman (1974), representative bias involves estimating: à ¢Ã¢â€š ¬Ã…“ the probability of an uncertain event, or a sample, by the degree to which it is similar in its essential properties to the parentsà ¢Ã¢â€š ¬Ã¢â€ž ¢ populationà ¢Ã¢â€š ¬? (ibid.). In other words, investors place too much weight on recent small sample datasets (law of small numbers) when projecting future cash flows for a stock. Kaestner (2006) suggests that when a series of such recent earnings data (in the same direction) is presented to the investor, this series is interpreted as a pattern and thereby becomes the basis for future projections of a stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s performance. Such projection thus leads to over/under estimation of future projected probability distributions of expected price performance. Kaestner (2006) argues that if representative bias affects investors then evidence of two related phenomenon would be present. à ¢Ã¢â€š ¬Ã…“First, statistical results would indicate a marketà ¢Ã¢â€š ¬Ã¢â€ž ¢s overreaction to some disclosed information. Second, the overreaction will be increasing in the extent to which the series of similar information is longà ¢Ã¢â€š ¬? (ibid., pp.10). Although De Bondt and Thaler (1987 and 1990) only tested for overreaction in their paper, they do mention the representative bias as a possible reason. Poteshman (2001) tests for representative bias and relates it to overreaction in the options markets. However, Kaestner (2006) for the first time directly tests the representative heuristic and links it to overreaction in the U.S. stock markets. 3. METHODOLOGY 3.1 Methodology Overview The literature has identified a variety of research methodologies, used to test for cognitive biases. This proposal extends the methodology of testing for overreaction used by De Bondt and Thaler (1985) for U.S markets, to Asian markets. Subsequently, the main focus of this study, à ¢Ã¢â€š ¬Ã…“representative biasà ¢Ã¢â€š ¬? as a driver of investor overreaction in response to earnings surprises is tested based on Kaestnerà ¢Ã¢â€š ¬Ã¢â€ž ¢s paper (2006) which also only explored the US stock markets. De Bondt and Thaler (1985) tested the overreaction hypothesis by constructing winner(W) and loser (L) portfolios of NYSE stocks. These were selected based on past three yearà ¢Ã¢â€š ¬Ã¢â€ž ¢s residual stock performance, which was, defined as monthly returns minus monthly market returns. The hypothesis test was run for the period January 1926 through December 1982. Positive results constituted the (W) and negative results the (L) portfolios. The two residual return results of prior and post three-year event periods (total of six years) were tested using the cumulative residual returns (CRS), a sum of the post formation monthly residual returns over three years. CRS was calculated for all sets of portfolios from 1930-1982 and each portfolioà ¢Ã¢â€š ¬Ã¢â€ž ¢s component residual returns were averaged to determine the cumulative average residual returns (CARS). Average of the CARS was calculated as the next step for all (L) and (W) sets of portfolios. CAPM was used in determining the ma rket portfolio return. Overreaction hypothesis suggested that (L) portfolios would perform better than market and vice versa. Results supported the hypothesis. This finding directly challenged the EMH implicit assumption that arbitrage gaps are filled rapidly by rational investors, since markets find an equilibrium price where excess returns are not possible and occur only as a result of luck. In essence, De Bondt and Thaler (1985) discovered the possibility of earning better than market returns. 3.2 Sample Data Characteristics Data for stocks will be acquired for Malaysia, Thailand, and Singapore stock exchanges directly, and/or from other information providers for the period 1990-2008. A total of eighteen years will cover three event windows and two economic cycles. This would also include the 1990 U.S. recession, 1997 Asian crises, and current 2008 global market fallout data. Daily stock prices in the form of open, high, low, and close would be used to determine daily returns and same data set would be required for the market index to get a proxy for market returns. In addition, quarterly EPS (earnings per share), earnings announcements by the company, and earnings consensus estimates of analysts would be gathered. For time line analysis, EPS estimates and actual EPS values will need to be obtained for preceding 4 quarters. To adjust for size, company capitalization data (shares x stock price) will be recorded at the beginning of each year in the sample set through the companyà ¢Ã¢â€š ¬Ã¢â€ž ¢s financia l statements. In addition, Beta estimates for all companies would also be required for the sample period. Most of this data is available in digital form through research sources including online internet subscriptions and the stock exchange itself. Stock selection criteria are detailed in the following sections. 3.3 Dependant and Independent Variables Dependant variable is the excess return derived as the difference between stock raw daily return and market daily return as an indicator of investor reaction. Independent variable is the data of actual earnings surprises in relation to analystà ¢Ã¢â€š ¬Ã¢â€ž ¢s estimates. 3.4 Overreaction Test Overreaction will be tested using sort-ranking procedure, as used by De Bondt and Thaler (1985) and repeated by Kaestner (2006) based on past stock return performance. Stocks will be ranked according to their past performance over three year event windows as a proxy for prior information and will be included into portfolios based on this performance. Post-formation performance will be assessed to test the ORH. 3.5 Portfolio Construction Portfolios of best performing (W) and worst performing (L) stocks will be constructed using past performance as a criteria. Each stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s historical monthly closing prices will be used to determine past performance over three-year event windows. The monthly return (Rist ) for stock i, based on its monthly closing stock price minus the monthly market return (Rmt ) derived from the closing market index price (for the same period) will generate the excess return (ARiet ) for stock i. ARiet = Rist Rmt This excess return (ARiet) will be defined as a performance measure for stock i, at time t, where the à ¢Ã¢â€š ¬Ã…“eà ¢Ã¢â€š ¬? represents excess and à ¢Ã¢â€š ¬Ã…“sà ¢Ã¢â€š ¬? represents stock specific return. Positive excess return (+ARiet) stocks would indicate best performers (W) while negative excess return (-ARiet) stocks would become part of the worst performers (L). The next step will calculate the cumulative excess (abnormal return denoted by AR) returns (CARi(p,q)) by summing the monthly returns for the 36 month formation event window for all stocks. q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet t=p p = time at beginning of event window (t=0) q = time at end of event window (t=3 yrs) Thereafter, stocks will be ranked from high to low, based on their cumulative excess returns of previous three years (formation period), and subsequently be added to either the best performers (W) portfolio or the worst performers (L) portfolio. To provide for progressive multiple tests, this portfolio formation process will be repeated for all non-overlapping event windows covering the entire test period with new portfolios formed every 3 years to be tested against their performance in the post-formation 3-year periods. Overreaction hypothesis suggests that (L) stocks should perform better than the market in the subsequent three-year post-formation event window as compared with the previous three years, whereas the reverse should be true for (W) stocks. This implies (L) stocks should have positive excess returns (+ARiet) while (W) stocks should generate negative excess returns (-ARiet) in the post event three-year period. A total of six years data will be required for the stocks und er consideration. For the market return (Rmt), an equally weighted monthly arithmetic average of stock returns in the sample will be used as proxy for market return (De Bondt and Thaler 1985). For each (W) and (L) portfolio, cumulative excess return (CARi(p,q)) for three-year post-formation event window will be calculated and repeated for all sets of portfolios. Finally, a mean of all member stock CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s in each portfolio will be computed and referred to as MCARi(p,t). Thus, two MCARi(p,t)à ¢Ã¢â€š ¬Ã¢â€ž ¢s will be obtained for each of these portfolios during the formation period of 36 months, and this will be repeated for all progressive portfolios over different event windows of the entire test period. In summary, CARi(p,q) and MCARi(p,t) will be calculated for the post-formation 3-year event window to test with formation event portfolios. If overreaction exists, then it is expected worst performing portfolios (L) should generate positive excess returns and vice versa for the best performing portfolios (W), i.e. negative excess returns. This return reversal would imply initial prices had overshot rational values (investor overreaction) as a short-term reaction and therefore adjusted back to rational values subsequently. Here, W-MCARi(b,t) = best performer portfolios L-MCARi(w,t) = worst performer portfolios The overreaction hypothesis (De Bondt and Thaler, 1985) expects post-formation results as follows: W-MCARi(b,t) 0 L-MCARi(w,t) 0 Such that, L-MCARi(w,t) à ¢Ã¢â€š ¬Ã¢â‚¬Å" W-MCARi(b,t) 0 3.6 Overreaction Due to Earnings Surprise Events Test Overreaction in response to earnings surprises will be tested based on sort-rank for single event and selection-ranking event method, for series analysis, as used by Kaestner (2006). The study will use portfolio-study approach as proposed by Ball and Brown (1968). Portfolios will be constructed based on stock earnings announcement events, ranked on highest to lowest surprises, for stocks in the sample. Highest earnings positive surprise stocks will be added to portfolio (+Ä ¤p ) and highest negative surprise stocks will constitute portfolio (-Ä ¤n ). Standardized Earnings Surprise criteria Quarterly earnings surprises will be computed based on standardized surprise earnings (Ã…Å ¾SÄ–q) represented by the difference between the actual released earnings (AÄ–q) and the one month prior to announcement consensus estimate for earnings (EÄ–q), scaled by the standard deviation of the individual estimates for each stock (à Ã†â€™est-q). Therefore, quarterly standardized surprise would be as follows: Standardized Surprise measurement: Ã…Å ¾SÄ–q = (AÄ–q EÄ–q) / à Ã†â€™est-q Excess Returns Measurement Excess returns (ARiet) for each stock will be computed on daily basis using closing stock prices as described in section 3.5. These returns will use size-adjusted approach[8](Kaestner 2006) and will be calculated as the difference between stock daily return (Rist ) and the equally weighted daily return of the stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s own portfolio (Rmt ). Thus excess return will be, as explained earlier in section 3.5: ARiet = Rist Rmt Thereafter, post-formation cumulative excess returns (CARi(p,q) ) will be derived based on event windows of 0 (0 represents the announcement date) to 1, 3, 10, 30 and 60 days for each portfolio Ä ¤p and Ä ¤n . The cumulative excess return for an event window will be: q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet t=p where; q= 1,3,10,30 or 60 day post-formation event window Overreaction to earning surprises expects stock prices to overshoot in the direction of the surprise, represented as follows: Positive cumulative excess returns for positive surprise portfolios and vice versa. CARi(p,q) 0 for +Ä ¤p CARi(p,q) 0 for -Ä ¤n Such that, Positive surprises (+Ã…Å ¾SÄ–q 0): CARi(p,q) 0 Negative surprises(-Ã…Å ¾SÄ–q 0): CARi(p,q) 0 Null Surprises ( Ã…Å ¾SÄ–q = 0): CARi(p,q) = 0 3.7 Representative Bias a Driver of Overreaction to Earnings Surprises According to Kaestner (2006), two expected phenomenon should be present, if representative bias plays a role in investorsà ¢Ã¢â€š ¬Ã¢â€ž ¢ overreaction to earnings surprises. First, a confirmation of overreaction to released information events, as tested earlier in this thesis, must exist. Second, this overreaction phenomenon should be increasing in relation to a similar series of earnings surprises over consecutive event windows[10]of future expected cash flows). This tendency to misjudge future prospects of a company causes investors to overreact in response to earnings surprises (both positive and negative), and would be reflected through securities prices. As a companyà ¢Ã¢â€š ¬Ã¢â€ž ¢s actual earnings information is released, investors would have to readjust their expectations (if they had overreacted) of cash flows based on the new real (actual) information and therefore the stock price must correct itself over time, if overreaction had occurred in the first instance. Representative bias causing overreaction due to earnings surprises will be tested by measuring investor reaction to a series of same sign surprises (Kaestner 2006). A non-parametric significance test will be used as proposed by Foster, Olsen, and Shevlin (1984) and later reviewed by Lyon, Barber, and Tsai (1999)[11]. This test relaxes the assumption of normality, constant variance of security returns over time, and cross-sectional independence in residuals (Kaestner 2006). The test focuses on establishing a companion empirical sample distribution, and then comparing its cumulative excess return (CARi(p,q)) with the observed CARi(p,q) to assess for statistical significance. Empirical distribution is generated by randomly selecting one event in the parent population for each event, computing equally weighted CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s for the companion sample, and ranking the companion sample CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s from highest to lowest based on a repetition of the first two s teps 2,500 times in order to obtain the empirical distribution. If representative bias exists and investors rely heavily on most recent earnings surprise information, then in the event of positive surprises, they will project overly optimistic future surprises and overreact immediately after the event on the positive side, subsequently reversing the price direction upon next earnings release (should the actual surprise not meet their expected higher surprise, (Ã…Å ¾SÄ–q =0). To test a series of events of earnings surprises, the sequential sort-ranking procedure will be used (Kaestner 2006). The initial portfolio is constructed for all individual null-surprise event stocks (Ã…Å ¾SÄ–q,t=0) and then ranked based on their most recent surprise events (Ã…Å ¾SÄ–q,t-1) relative to this null-surprise, as compared with the stockà ¢Ã¢â€š ¬Ã¢â€ž ¢s last surprise (t-1). In fact all subsequent sorting will be in relation to a starting most recent null-surprise (Ã…Å ¾SÄ–q =0), so that post null-surprise period can be studied. These rankings are used to construct three equal sized portfolios labeled as positive, neutral, and negative (Ã…Å ¾SÄ–q,t-1) surprise portfolios. These three portfolios are then each sub-divided into three more portfolios based on rankings of stock surprises at (Ã…Å ¾SÄ–q,t-2) which means 2 quarters behind in a series. Similarly, these are sub-divided into three more portf olios at t-3, and t-4, giving rise to a total of 5 quarters backwards surprise series-related portfolios. In this way, series of similar earnings surprises in sequence are separated for testing while keeping the current surprise at zero (null). For each family of series of portfolios (including one null surprise) which gives rise to different number of stocks in the sample, CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s are computed for different event windows (i.e 0;1, 0;3, 0;30 and 0;60). This will allow for a study of the impact of similar preceding surprises on overreaction to the most recent earnings surprise. Portfolios will be tested for investor reactions for four event windows. Representativeness hypothesis (Kaestner 2006), suggests investors will overreact initially to a surprise due to overweighting of this information in future projections. And in the case of a series of such surprises, the overweighing of future expectation will be stronger, giving rise to greater overreaction. However, when the actual earnings number results in no surprise, investors readjust their view in the opposite direction, causing a correction to the initial overreaction. This hypothesis suggests then, that a correction will ensue post the current null-surprise event causing CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s to be of the opposite sign of the surprise and also, this reversal should be stronger for longer series of such similar surprises as opposed to shorter series, implying that investors overreaction is affected by the representative bias. Thus, for positive surprises, CARi(p,q)à ¢Ã¢â€š ¬Ã¢â€ž ¢s should be negative in relation to the empirical distribution generated by the null-surprise sample portfolio and positive for the negative surprise portfolios. For the empirical distribution sample and null-past surprise series, the CARi(p,q) should be = 0. 3.8 Empirical Results Statistical Significance Representativeness hypothesis expects: Non-surprise portfolios: Where  : (Ã…Å ¾SÄ–q = 0) CARi(p,q) = 0 (no significant market reaction) For positive surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q) 0 (negative subsequent post event correction beyond null-surprise) For negative surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q) 0 (positive subsequent post event correction beyond null-surprise) Such that: For positive surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q-3) CARi(p,q-2) CARi(p,q-1) CARi(p,q) For negative surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q-3) CARi(p,q-2) CARi(p,q-1) CARi(p,q) 3.9 Summary of Research Objectives Note: details of methodology appear in relevant sections above. This section indicates only a summary of already discussed objectives for ease of reading. Objective 1: Does investor overreaction exist in emerging stock markets? W-MCARi(b,t) 0 L-MCARi(w,t) 0 Such that, L-MCARi(w,t) à ¢Ã¢â€š ¬Ã¢â‚¬Å" W-MCARi(b,t) 0 Objective 2: Do investors overreact to earnings surprises? Null Surprises: (Ã…Å ¾SÄ–q =0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet = 0 t=p Objective 3: Do investors overreact to positive/negative earnings surprises? Positive surprises: (+Ã…Å ¾SÄ–q 0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet 0 t=p Negative surprises: (-Ã…Å ¾SÄ–q 0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet 0 t=p Objective 4: What is the relationship between representative bias and over- reaction as it relates to earnings surprises? Is representative bias present during overreaction? Non-surprise portfolios: (Ã…Å ¾SÄ–q = 0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet = 0 t=p (No significant market reaction) Objective 5: Does representative bias cause overreaction when earnings surprises are positive? For positive surprise portfolio: (Ã…Å ¾SÄ–q 0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet 0 t=p (Negative subsequent post event correction beyond null-surprise) Objective 6: Does representative bias cause overreaction when earnings surprises are negative? For negative surprise portfolio: (Ã…Å ¾SÄ–q 0) q CARi(p,q) = à ¢Ã‹â€ Ã¢â‚¬Ëœ ARiet 0 t=p (Positive subsequent post event correction beyond null-surprise) Objective 7: What is the relationship between representative bias and overreaction as it relates to a series of earnings surprise announcements, both positive and negative? For positive surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q-3) CARi(p,q-2) CARi(p,q-1) CARi(p,q) For negative surprise portfolio: (Ã…Å ¾SÄ–q 0) CARi(p,q-3) CARi(p,q-2) CARi(p,q-1) CARi(p,q) 4. EXPECTED CONCLUSION The contribution this research would make is extending current empirical research on cognitive biases affecting stock price behavior, and testing for investor irrationality, specifically investor overreaction and representative heuristic, as it relates to earnings surprises. This study may also provide further understanding of the drivers of stock prices for investment decision-making, forecasting, and policy making relevant to financial market participants. In addition, contribution towards a piece of the stock pricing puzzle, as well as further research questions may be discovered. It seems clear that EMH and CAPM (pillars of the current financial theory), despite mounting evidence against their validity, remain widely in use. Behavior finance seems to offer an alternative to the current financial theory, and therefore latest empirical research in asset pricing, is towards this direction in order to understand and discover a better way to price financial assets. This thesis expects, based on Thalerà ¢Ã¢â€š ¬Ã¢â€ž ¢s (1985) ORH, investor overreaction in the emerging markets (Malaysia, Thailand, and Singapore) as demonstrated through securities prices to be confirmed through empirical testing. In addition, this study expects to identify representative bias as a source of such overreaction. This study offers to contribute empirical research towards the field of behavior finance in understanding better the notion of investor irrationality and its consequent impact on asset pricing. 5. PROPOSED RESEARCH OUTLINE THESIS OUTLINE Sections: Introduction Brief History of Research Question Theoretical Framework Research Objectives Statement of Problem Research Significance Literature Review 1) Prior Research and Gaps 2) Investor Overreaction 3) Representative Heuristic 4) Research Questions Methodology 1) Methodology Overview 2) Research Hypothesis 3) Model Configuration 4) Dependent and Independent Variables 5) Sample Data and Characteristics 6) Construction of Test Portfolios 7) Measuring Abnormal Returns and Earnings 8) Empirical Results and Statistical Significance 9) Does Representative Bias drive Overreaction? 10) Limitations of Study Conclusions References Appendix/Exhibits

Negative Effects Of Cell Phones - 1465 Words

Summary In today’s day and age, cellphone usage has increased tremendously. Almost everyone has had a cell phone since middle school age, or even younger. People spend an average of five hours on their phones a day from recent studies (Perez, 2017). Cell phones are a means of communicating with people more often and faster. The average cell phone user spends two hours a day using them. This shows that out of all the down time people have from school, jobs, or other activities, they are usually going to be on their cell phones. Almost everyone is addicted to having the small, metal, piece of communication device in their specially trained hands and fingers. Every time a stinging vibration surges up their bones, they immediately start†¦show more content†¦People automatically assume that it is the child who cannot take their faces out of their phones, but a lot of the times it is the parents as well. Lastly, socialization is descending with the increased utilization of cell pho nes. Kids and parents would rather be home communicating through their device rather than exerting the energy to be with friends and family face to face. Due to improvements of technology making communication easier, simple face-to-face communication seems like too much work. Adding on to this, people skills are also being affected because there are less face-to-face conversations going on. Learning how to work with others for work and school is a big part of most people’s lives. When hiring, or trying to go to a good university, most people are more likely to be influenced in a real conversation, rather than on a phone. Also, With the over utilization of cellphones, people start to lose the aspect of reading each other’s facial expressions and the tones of their voices to know if there is a problem, if they’re happy, upset, or interested in something. When people use cell phones more than talking face-to-face, their people skills start to deteriorate. Lastly, w ith the increase use of cell phones, health problems are also increasing. Cell phones have a special light called a High Energy Light or HEV light that is one of the shortest wave lengths. This light is a blue light which meansShow MoreRelatedNegative Effects of Cell Phones1731 Words   |  7 Pagestask easier. A cell phone is a type of technology that is a common thing to see in everyday life. The world and the people in it have gotten used to this technology. Cell phones are making the lives of an estimated two hundred sixty five million Americans (Natterson 103) and three billion worldwide (Natterson 103), easier. As useful as cell phones may be, there are negative effects in over using cell phones. Cell phone technology was first developed in the 1980’s, but cell phones became common inRead MoreNegative Effects Of Cell Phones1318 Words   |  6 Pagesthe conclusion that there is a strong correlation between the usage of cell phones and personal health. Studies show that cell phones emit radiofrequency energy, which is a form of electromagnetic radiation and it is proven that radiation exposure to the human body is hazardous. Technology has its ups and downs, with that being said cell phones are a good example of how sometimes advancements can be good and bad. Yes, cell phones have a lot of fun things to do, from playing your latest and favoriteRead MoreThe Negative Effects Of Cell Phones717 Words   |  3 Pages In todays technological era we rely heavily on technology, from our phones all the way to our Smart Tvs. However, peoples need to bring their smartphones with them everywhere they go has started to become a problem regarding the way we connect with others. W e need better cell phone etiquette because without it the way people intermingle could completely change in a negative way. A lack of a stricter cell phone etiquette has led people to stop interacting with each other, live their lives throughRead MoreNegative Effects Of Cell Phones1005 Words   |  5 Pagesthat were involved by the cause of having a cell phone. Mobile device has a great impact in the human race, by advancing in technology and causing harm in lives. Cell phone etiquette is not disrespecting a person by discarding the conversation and getting on the phone. Today’ s modern world people all around the planet have a cellular device, but do people really know how to use a cell phone? Why do teachers get so frustrated when a student is on their phone while there lecturing? People all aroundRead MoreNegative Effects Of Cell Phones707 Words   |  3 PagesAlmost everyone in the world owns a cell phone. In previous years, mobile devices did not exist. Surprisingly, p eople would have to use their house phone that everyone in their family shared or they would have to wait until they could the person and talk to them face to face. But, our technology just keeps getting better. Cell phones allow people to communicate quicker and easier that they have become apart of people’s everyday lives. Sadly, there are many negative affects of always having our mobileRead MoreNegative Effects Of Cell Phones1192 Words   |  5 PagesIn this day and age, more than half of the worlds population owns and uses cell phones. It is a well-known fact that cell phones emit low doses of radiation each time one is used, however, people tend to brush it off and not think about the long-term effects it may have. Its only small doses, what harm can come from it? That is a question us cell phone users may ask ourselves, yet never really look into or research. Maybe its because we choose not to know the actual truth and just focus on theRead MoreNegative Effects Of Cel l Phones1100 Words   |  5 Pagescreated the thing that runs the lives of many ---- a cell phone. For those living under a rock, cell phones are portable telephones that requires cellular network (ATT, Verizon and Tmobile) to make and receive phone calls. For the first time ever, a generation of kids are going through their adolescence with smartphones. As stated by Pew Research Center, â€Å"75% of 12-17 year-olds now own cell phones, up from 45% in 2004† (Lenhart 1). As cell phones advanced over the years, the increase of adolescenceRead MoreNegative Effects of Cell Phone of Society1609 Words   |  7 PagesSteve Sheridan Professor Simakowicz 1st Draft Paper 13 April 2010 â€Å"Do Cell Phones Help or Hinder Society?† Times have changed tremendously in the last twenty five years in regards to how the world communicates with each other. The birth of new technology such as cell phones with internet capability, laptop computers, and even the recently released I-Pad has made communication with anyone outside of talking distance immediately accessible. Even though to many people this seems like a movement in theRead MoreNegative Effects Of Texting And Cell Phones894 Words   |  4 PagesTexting and cell phones have, of all age groups, likely affected kids the most. In one way, it has made young kids more socially awkward. These kids are being raised having more communication on social media portals and by texting much more often than face to face interaction. This problem will only get worse as we progress into the future. Children that are raised being able to front their problems and meet new people by using a phone will greatly lack the ability to deal with problems face to faceRead MoreNegative Ef fects Of Technology On Cell Phones807 Words   |  4 PagesWith the growth of new technology, society is becoming too dependent on cell phones. Although communication and information may be important over a screen, it may take away from interaction in society. Overuse can cause negative side effects when it is not available as well as take away the overall experience of life itself. Cellular technology has contributed to negative and positive factors. It is best to view each side and understand how to best use it for a healthy lifestyle. To begin with,

Children Of Inter Parental Family Violence - 1087 Words

Every single day, a child encounters an act of violence. Not only on televisions but also in their own homes as well. For those who go through those circumstances strongly believe that even families and homes are not the shelters where they would find encouragement and sense of security, but rather they abstract the meaning as an arena where fear, anxiety, confusion, anger, and disruption are significant threads in the needlepoint of a home life,(Journal of Child and Adolescent Psychiatric Nursing, 2015, pp. 97-108). A home is supposed to be a safe place where children start learning the essentials and importance of bonding of relationships. It’s a place, where children learn how to love and relate to others and start building of their†¦show more content†¦As a matter of concerns, the demand arises, how does exposure to inter-parental violence and childhood physical and emotional abuse cause physical aggressions in any undergraduate student. To look more closely, one must consider the results of earlier investigative results by various psychiatrists describing the root cause and their possible primitives’ measures. Why do so many children exposed to intimate partner violence struggle with emotional and behavioral problems and become victims or perpetrators of violence in their own relationships? Although multiple processes undoubtedly are involved, the subjective meaning that children draw from hostile and aggressive interactions in the family is proposed to be a critical factor in shaping its immediate and long-term impact on them (Fosco et al., 2007; Grych 2000; Grych and Fincham 1990). The cognitive-contextual framework (Grych and Fincham 1990; Grych et al. 1992) holds that when children witness aggression between their caregivers, they actively process and try to make sense of what is happening, and that their appraisals have implications for their immediate response in the situation and their long-term functioning. More specifically, it proposes that children appraise the degree of threat the interaction poses to them or their families, why it is occurring, and how they should respond. App raisals involve emotion as well as cognition (e.g.,

Spatial Learning And Memory At Acute And Chronic Sleep...

Spatial learning and memory are very important to humans in their everyday life. It helps them remember where they parked their car, how to get from home to work, or how to get to the hospital in an emergency. It was a difficult topic to study until Richard Morris created the Morris water maze in 1981. Since then, it has become simpler to observe not only rats, but also human’s spatial learning and memory. There have been a lot of studies on spatial learning and memory and how to enhance it or what improves it. A study done by Azogu et al. (2015) looked at acute and chronic sleep deprivation and how it affected spatial memory. They tested the rats in the Morris water maze and found that rats had improved spatial memory when acutely sleep deprived. In another study done by Merriman, OndÃ…â„¢ej, Roudaia, O’Sullivan, and Newell (2016), it was tested if the familiarity of an environment affected spatial memory. They tested this on older and younger adults. They found that older adults did worse than younger adults on all aspects of the study. They also found that being in a familiar environment provided a benefit on their performance of recognizing novel objects. This was found in both the younger and older adults. These types of studies are important because they help expand the current understanding of spatial learning and memory. The more studies and tests done on this subject, t he better we know what does and does not work in regards to spatial learning. One area that has hadShow MoreRelatedEffects of Lack of Sleep to Students of Philippine State College5455 Words   |  22 Pagesâ€Å"Effects of Lack Sleep to the Students of Philippine State College of Aeronautics† Name (Optional):_____________________ Age: __________ Gender: __M __F Civil Status: ____________ Check for the desired answer. | Yes | No | 1. Do you usually sleep late? | | | 2. Do you find it hard to sleep early? | | | 3. 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Different phenomena that are closely related make up this spectrum of behavior, described as complex behaviors or physiological events that manifest when an individual becomes stuck in the transition period of the sleep cycle. Studies on partial arousal states have been more in depth within the last half century. In regards to sleep terror disorder, many effected individuals only require assurance of their safet y and accurate facts of the nature of sleep terror episodes.Read MoreStress And Its Effects On The Mind, Body, And Environment8594 Words   |  35 Pagesmental training are the most common recommendations for the overall health of your body to prepare for stressful situations (The American Institute for Cognitive Therapy, 2009). Cognitive stress becomes more concerning when it can be categorized as chronic. High stress levels have been associated with many serious physical and psychological difficulties. 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PEST ANALYSIS RESTAURANT free essay sample

Grading Criteria: AAA Explain what is meant by a PEST analysis. Describe the political factors which could affect your product Describe the economic factors which could affect your product Describe the social factors which could affect your product Describe the technological factors which could affect your product Use textbooks and the internet to help with the theory. Summary market research reports and news sites are especially good for PEST factors.You must give very precise points and try wherever possible to support your points with examples and statistics. Make each point, in each section, separate. You can bullet point each factor, but you need some explanation of the point. It should not be simply be a list. A PEST Analysis looks at what is happening n the external environment of the restaurant industry. These factors are usually beyond the control Of a business.A PEST looks at the following factors which could affect your restaurant: Political Economic Social Technological A Quick Quiz In which category would you put each Of the following: Inflation Changing eating habits Introduction of new touch screen ordering systems Unemployment Food Hygiene Laws Increase in the number of older people in the population Advertising on mobile phones Ban on smoking in public places A PEST analysis helps businesses:understand whether a market is likely to row or decline keep up with and take advantage of change Avoid taking decisions which are doomed to fail Explain briefly what is a PEST Analysis. We will write a custom essay sample on PEST ANALYSIS RESTAURANT or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page

Project Management Economy

Question: Write an essay on Project Management? Answer: Here we are told of the critical path, now we must first understand the meaning of the word critical path, it means that when we take up a project we follow a certain path to finish its course and the paths can be different for different project but if the path that is taken proves out to be the longest path then it is called the critical path. Now here we will be given some precedence constraints to work on and the critical path must be chosen according to the precedence constraints set out by the Multiple sclerosis society of Canada, because the constraints determine the working principle that must followed in order to select the critical path that can be taken in order to serve the original purpose of the project of the Grand Bend Bicycle Tour. The critical path will be the longest path taken in order to accomplish the project so the project manager should keep in mind that if the projects deadline crosses over, he/she have to bear the consequences in order to finish the project efficiently so the project manger should always try to diminish the chances of taking up the critical path as the last resort, and revive all the stress of the number of participants involved or the capital needed or the administration involved (Heerkens, 2002). -In order to obtain the most efficient working process the project manager should try to reduce the chances of taking up the critical path to finish his task and so for that the project manger should undertake a sequence of tasks that would help him to reduce his chances of taking up the critical path in order to finish his project some of the methods or sequence of steps are given below. a) The Economy- The main usage of the critical plan comes into the picture when we talk about saving the capital associated with the project, so the first motive is to eliminate all kin sod unnecessary steps that could ensure a hit on the capital and undertaking of the critical path takes place. b) Identify the steps- Identify the unnecessary steps that require more time and obtain more chances of calling in the critical path to finish the project (Deeprose, 2002). So the project manager has the responsibility to reduce the number of unnecessary steps that are undertaken in order to reduce the chances of using the critical path. c) Customer Satisfaction- The project manager should also ensure that the dependency of the customers on the critical path must be reduced and for that they should make sure of taking the optimum time to finish the project so that there comes no need of taking up the critical path. Revised Critical Path- The revised critical path is the path under taken to complete the project in the allotted time by taking in all the methods that can be used in the process of the original critical path and completing the project in the allotted time by achieving all the constraints. Yes, an achievement of less than 23 days is made by taking up the revised critical path. The optimistic times must be undertaken, in order to finish the project of the bicycle tour in order to satisfy the needs of the customers who are in need in the Multiple Sclerosis Society of Canada (Wright, 2002). For that the project manager should think of all the means available in order to fulfill every aspect of the project without going into using the critical path as the last resort to its plan of accomplishing the project and for that the project manager has to deliver all the aspects of the project by completing the task to their ends and then delivering it to the customers and avoid using the critical path to achieve its goals. The present stress that the project managers are facing should be lifted as soon as possible in order to divert the project managers from the path which can be wring and prove itself as a catastrophe. For that the areas of stress must be identified in order to propose a suitable contingency plan and also certify a number of experts to work on the plan efficiently so that the expected objectives are gained (Kerzner, 2001). The contingency plan is nothing but a risk management procedure in order to save the project. References Deeprose, D. (2002).Project management. Oxford, U.K.: Capstone Pub. Heerkens, G. (2002).Project management. New York: McGraw-Hill. Kerzner, H. (2001).Project management. New York: John Wiley. Wright, J. (2002). Effective Project Management.International Journal of Project Management, 20(8), p.633.