The earnings season is the time after the end of a company’s quarter and it is usually marked by a publicization of the institution’s most recent earnings. The declaration of a company’s earnings usually comes with a profound effect on stock prices. There are two prime ways in which stock prices respond to earnings announcements in the first three days. The first response is the stock prices and volumes immediately shifting in the direction of the earnings meaning that, if the company’s earnings indicate an upward trend, then chances are that the stock prices will go up. On the other hand if the earnings just stay at the expected levels or even experiences a loss, then the prices of the stocks might go down. The second response is stock-market activity shifting in a manner opposite to company earnings announcements. In this regard, if the released earnings indicate a positive performance, the stock prices and volumes will go down and if the announcement indicates a decline in the company’s earnings then the stocks respond by going up. This phenomenon is referred to as post-earnings announcement drift. The first three days following the earnings announcement is normally seen as the most unstable in the stock market. Most stock traders tend to capitalize on this period to advice their clients to buy and sell during this period as an easy way of making quick profits. When corporations release earnings information without giving prior notice to the investors, the stock market responds following the direction of the earnings release. This essay seeks to analyze the response of the company stocks to earnings announcements. To this end, both the normal and the unexpected market responses will be studied and proper scientifically researched explanations will accompany the discussions.
The research for this essay was based on secondary data collection. Data was еxtractеd from various journals, articles and books. Thе critеria of sеlеction for thе litеraturе was rеlеvancе to thе rеsеarch topic and thе yеar of publication. Both public and privatе librariеs as wеll as onlinе librariеs were visitеd to accеss thе data. Somе of thе onlinе databasеs that were accеssеd include Ebsco, Quеstia, Emеrald and Science Direct among others. This research was partly evidence based and partly founded on professional research by professionals in the field. Various articles were studied in order to provide background information which will essentially give credibility to the final essay. Information from the books will serve to provide explanation as regards to the internal machinations of the stock market. This is very vital information that will make the research appeal to both professionals and the general public. For the latter, it may require that some of the information obtained from the books and other publications be broken down into simple language and at the same time illustrations drawn from the commonly applied functionalities of the stock market. Empirical data was collected from various studies and numbers and figures used to show the usage of various hypotheses in a practical situation.
Studies have shown that when companies announce their earnings (quarterly), a substantial upward shift occurs in the trade volumes accompanied by appreciable price volatility. Aside from this, the prices of stocks rises in days before and after the earnings are announced (Rappaport and Mauboussin 2003, p.9). The rise in stock prices could easily be attributed to the increase in volume linked to the announcements of the earnings. The premium is directly proportional to the increase in trading activity in the time before, during and after earnings announcements and therefore those stocks that have high volumes around this period tend to have high premiums and attract more investors (Rappaport and Mauboussin 2003, p.9). This therefore means that for most stocks, the prices go up around the announcement period because of increase in demand by customers. Some schools of thought however do not support this correlation of a rise in stock prices to increased individual investor demand.
Owen Lamont and Andrea Frazzini are two economics scholars who believe that there is no way of categorically associating stock price with interpretation of the releases. Instead, the two believe that investors will be more interested in certain stocks provided the announcements are attractive and attention grabbing (Lamont and Frazzini 2007, p.2). The two researchers particularly found the attention-grabbing hypothesis most credible especially because they found out that the stocks which receive more media attention tend to have high volume and receive high sales regardless of their quality. This is particularly for those companies whose highest trading in the past appeared to be on earnings announcement days (Lamont and Frazzini 2007, p.29). The predictable upsurge of stock prices in the period around the announcement date draws the interest of such buyers especially because their main strategy is to make quick profits.
The Efficient Markets Hypothesis in explaining the short-term stock market response to earnings announcements
Stock market investors are a differentiated class of individuals who differ based on different characteristics including wealth and experience. Characteristics of informed trading have been used by various scholars to explain market trends in the first three days after the announcement of quarterly earnings. One of the hypotheses for explaining the characteristic behavior of stocks in the first three days following earnings announcements is the efficient markets hypothesis which holds it that all the information pertaining to a company’s financial performance has to have a notable impact on the enterprise’s stock prices (Malkiel 2003, pp.3-6). The efficient markets theory is one of the most recent and most properly tested of the logical explanations that explain the stock market behavior before, during and after the announcement of company earnings. This theory proposes that the most common initial response to earnings announcements by investors is a complete underreaction (Malkiel 2003, p.6;8). However in some instances there is extreme activity in the movement of stock price following the announcement of earnings which is essentially viewed as an overreaction. The uncharacteristic response of stock price and market activity to earnings announcements is primarily referred to as the post-earning announcement drift and it is characterized by stock prices surging upwards when a company’s earnings indicate negative performance or for stock prices going down even when the earnings announcement is indicative of positive company performance. There a number of scholarly explanations for the post-announcement drift but all of them point to the disparity between stock prices and earnings in one quarter and the effect of the current stock prices on future company earnings. Consequently, in subsequent quarters, the value of the stocks tends to respond to earnings changes in ways that are contrary to expectations even though these changes could have been easily forecast prior to the event (Easton 2010, p. 3). Depending on a quarter’s earnings, the short term (3 days) response to the announcements for four succeeding quarters are predictable to some extent depending on the earnings of the current quarter (Easton 2010, p. 12).
One of the reasons that has been given by economic scholars for explaining the underreaction of the stock market to earnings announcements is the failure of the stock market to completely and appropriately absorb new information into the stock prices in a rapid manner (Jacob, Lys and Sabino 1999, p. 340). The proponents of this theory believe that most of the stock market operatives tend to take a long time to assimilate new market information consequently leading to instability in the trading volumes and stock prices. Unfortunately, this explanation translates to inefficiency in the stock market.
This hypothesis has received acclaim as far as providing explanation to the uncharacteristic relationship between the stock market and the announcement of company earnings particularly due to its effectiveness. The efficient market hypothesis is primarily a prolongation of the zero profit equilibrium in competitive business and can be presented by the description below (Yu 2009, pp. 847-850):
- The weak form of the efficient market hypothesis which assumes that the information used in the analysis include data carried in past price history of the markets at a given time (Chordia and Swaminathan 2000, p.915). This basically means that it is virtually impossible to identify securities that were priced wrongly and use information obtained by analyzing historical price records to challenge current markets. In other words, nobody can make financial gains in the stocks markets using information that everybody else possesses.
- The medium-strength form of the efficient market hypothesis which assumes the data to be used in the analysis includes all information that is available to everyone at the specific time. Public information in this case includes both past and current data on an enterprise’s performance. In some cases, the public information may not necessarily be data of financial nature (Chordia p. 711). For example, when studying software firm, public information includes data on current research pertaining to software development. Since this version contains all the former history of prices, it can be regarded as a stronger form of the first version.
- The strong form of the efficient market hypothesis which is basically a logical completion to the available classes of hypotheses and it asserts that the current price comprises all types of data; both private and public. This hypothesis clearly states that company heads are not in a position to make huge profits by buying into company, on a private capacity, buying using insider information that in a given amount of time the company is going to invest in a very profitable venture (Aboody, Hughes and Liu 2005, 654).
Empirical information to support the efficient market hypotheses
The weak form of market efficiency
The weak form hypothesis also known as the random walk hypothesis tends to imply that price shifts following each should not be linked to each other. Various scholars conducted studies to analyze the effectiveness of this hypothesis by studying the linkage between the current return on a security and the profits on the same security in a different time in history. A positive serial correlation will imply that high profits in one season will be followed with high profitability in the next season. On the other hand, a negative correlation means that high profits in one season will be followed by low than average performance in the next period. Therefore if this hypothesis had substance, it would mean that a zero correlation would be expected. Scholars in the field established that serial correlations for 30 Dow Jones were far too small to address the costs of transaction (Damodaran 2002, p.124). While most analysts did not find this method of analysis relevant Brock, Lakonishok, and LeBaron (1992) that the simplicity of the technical analysis in this framework can come in handy in predicting the Dow Jones industrial average.
The semi-strong form
This hypothesis clearly states that investors should not at any given time profit using information that is publicly available. It is public knowledge that investment managers have devised clever ways of beating the market. Empirical data however supports the contrary. In one study Michael Jensen discovered that in the nine year period between 1955 and 1964 mutual funds attained a performance of zero per annum. This implied that mutual fund managers did not bear any special stock-identifying skills. Studies have been conducted by various scholars including Eugene Fama and Michael Jensen to analyze the response of the prices of stocks in tandem with stock splits (Klein, Rosenfield and Tucker 2006, p.1). It is well known that stock splits should be received positively be investors mainly because they are accompanied by an increase in dividends. They found out that immediately before the splits, the stocks performed impressively. However, after the split, the stocks did not present with manifestation of abnormal performance. This therefore means that individuals could not make any substantial profits by buying in on the date of the split (Klein, Rosenfield and Tucker 2006, p.3).
The strong form
Empirical tests of this hypothesis have been carried out to find out the credibility of the argument that company workers can make profits based on insider trading. Rozeff and Zaman (1988) discovered that insider trading had a profitability of approximately 3% after taking away all the technical costs. This, therefore, disapproves the strong form of the efficient markets hypothesis. A second explanation for the abnormal reaction of stocks to earnings announcements is referred to as risk misspecification. This theory explains that the abnormal returns following the earnings release are basically fair compensation for the risk bearing (Rees 2005, 465-496).
Expectation and the determination of short term stock market response post earnings announcements
Estimating unexpected returns
Data pertaining to the announcement of earnings can be approximated by usage of unexpected returns (Li 2009, pp.595- 620). This is basically arrived at by taking the difference between the real income and the expected earnings and the deflating it. After this operations what you get are the standardized unexpected earnings (SUEs). A number of expectation theories have been utilized in post-announcement drift analysis. These include the Watts-Griffin model, the Brown-Rozeff model and the Foster model (Dharan 1983, p. 256). The Foster model is however, the one that has found most contemporary usage in the study of earning expectations primarily because of its credible predictive ability (Dharan, 1983 p.269-271). Because information has its unique independence based on the time of reference, SUEs also tend to work effectively when providing explanations for quarterly earnings only if they are allowed to maintain independence over the time of reference. The Foster model for predicting company earnings is structured in such a way that it analyses the expectations of investors as opposed to other theories which tend to use the mathematical explanations of the time of events and its relation to the earnings (Dharan 1983, p.268 ).
This basically means that the Foster model can only identify one point in time in which abnormal returns can be arrived at by the investors buying based on the earnings of the company at the time. The usage of this model has found modern-day relevance in the work of management analysts who can accurately predict company performance as well as provide clear security returns.
Estimating abnormal returns
Abnormal security returns are mainly identified by taking the difference between the actual returns and the expected security returns (Gregory and Matatko 2006, p.13-14). Because the actual returns usually come with little or no mistakes it is imperative that the expected returns factor in future risk so that the final outcome is presented without error. There are three primary methods for approximating abnormal returns. These are briefly explained below:
- The excess return strategy-this approach looks at the expected security returns as a factor of market returns. The market returns in this instance implies all the players in the stock markets. This method does not provide measures against risks and is therefore weak when it comes to the provision of proper evidence for analyzing the efficiency of the market.
- The abnormal return strategy-this approach analyses the expected returns based on capital asset pricing. The parameters are approximated starting from a clear time period which is usually some time before the earnings announcement (Gregory and Matatko 2006, p.18). The only weakness of this method is that it tends to depend on parameters obtained from the estimation of market performance in a certain period to explain the returns in a different time. If structural changes are encountered between the two periods, then the prediction will come with errors. The main challenge while trying to approximate abnormal returns, therefore, is adjusting the security returns to accommodate risks.
The announcement of companies’ quarterly earnings is for all practical purposes and intents a reflection of the institutions performance. Companies that are doing well will tend to attract more investors and this is usually revealed by high trading activity in the stocks of the high performers. However, the announcement of earnings and the stock market have a unique relationship particularly in the first three days following the announcement of the earnings whereby sometimes the response in investor interest and stock price is not always directly related to the immediate announcement of company earnings. This relationship has been the focus of this essay effort has been made to provide explanations for the various occurrences in the stocks trade. It has been established that depending on factors such as the time of the announcement, company performance and the amount of information released to the public the stock prices and volume may respond in two principle ways in the first three days post earnings announcements. The stocks may respond by following the direction of the earnings or in a unique way they may move in the opposite direction. The efficient markets hypothesis has been identified most reliable for explaining the short term response of stock prices and volume to earning announcements have also been analyzed. The hypothesis has been divided into three categories depending on the amount of information utilized in the assessment of data for the purpose of explaining the relationship between earnings announcements and stock prices and volumes. These categories are the weak, semi-strong and the strong versions of the efficient markets hypothesis and they have all been given an in-depth analysis. Finally, the expectation of earnings has also been identified as one of the elements that can help companies predict the response of the stocks. It has therefore been given a critical highlight, specifically touching on the estimation of unexpected returns as well as the estimation of abnormal returns. This paper has been grounded on information from high quality sources. These include recent peer reviewed journals and books and among the criteria used for selection of the information to be used include the relevance to the discussion. It is however worth noting that the discussion has not listed absolutes and there is still more room for research and discussion on the topic.
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