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Stock Price Reaction to Quarterly Earnings Announcements with respect of outlook changes and deviation to consensus forecast

Bachelor Thesis 2008 51 Pages

Business economics - Investment and Finance

Excerpt

Table of Contents

List of Abbreviations

List of Figures

1 Introduction
1.1 Problem Definition and Objectives
1.2 Course of the Investigation

2 Theoretical Foundations
2.1 What Determines a Stock Price?
2.2 Prime Standard
2.3 Ad Hoc Publicity
2.4 Market Efficiency
2.5 Anomalies and Abnormal Performance

3 Theoretical Discussion on Stock Price Behaviour after Earnings Announcements
3.1 Behavioural Finance
3.2 Investment Strategies and Models
3.3 Bad-model Problems

4 Practical Examination on Stock Price Behaviour after Earnings Announcemens
4.1 Data
4.2 Benchmarks
4.2.1 Sector Indexes as Benchmark
4.2.2 Consensus Expectations and Company Outlook as Benchmarks
4.3 Classification of Portfolios
4.4 Results of Examination
4.4.1 Differentiation between Quarters
4.4.2 Differentiation between Performance Prior the Earnings Announcement
4.5 Outliers

5 Conclusion

List of Abbreviations

Abbildung in dieser Leseprobe nicht enthalten

List of Figures

Figure 1: Trading Volume around earnings announcements

Figure 2: Efficient versus Inefficient Market

Figure 3: Capital Asset Pricing Model (CAPM)

Figure 4: Fama and French Three-Factor Model

Figure 5: Portfolio 1

Figure 6: Portfolio 2

Figure 7: Portfolio 3

Figure 8: Portfolio 4

Figure 9: Portfolio 5

Figure 10: Portfolio 6

Figure 11: Portfolio 7

Figure 12: Portfolio 8

Figure 13: Portfolio 9

Figure 14: Positive Stock Price Performance Prior Reporting

Figure 15: Negative Stock Price Performance Prior Reporting

Figure 16: Impact of earnings surprise regarding analyst consensus forecast

Figure 17: Impact of changes in full-year outlook

1 Introduction

1.1 Problem Definition and Objectives

“The impact of particular types of firm-specific events (e.g. […] earnings reports) on the prices of the affected firms’ securities has been the subject of a number of studies. A major concern […] has been to assess the extent to which security price performance around the time of the event has been abnormal – that is, the extent to which security returns were different from those which would have been appropriate, given the model determining equilibrium expected returns.” (Brown and Warner, 1980, p. 205).

Many authors have already studied about stock price reactions after earnings announcements yet, which is because of the importance of earnings announcements, in particular quarterly earnings announcements, for many investors. However, all major studies concerning this topic deal with long-term scenarios, the stock’s price performance is measured for a time period of at least three quarters. Due to the fact that there are many investors, especially institutional investors such as hedge funds that trade stocks much more frequently, the existing studies are not relevant for them.

This paper studies stock price reactions around quarterly earnings announcements for companies listed in Deutscher Aktienindex (DAX) or Midcap DAX (MDAX) with respect to changes of the company’s full-year outlook and of earnings surprise regarding analyst consensus forecast within ten days before and after the announcement date. Hence, this paper aims to analyse short-term reaction to quarterly earnings announcements, which are of relevance for all investors, whose investment strategy is, at least partially, focussing on the short-term performance. The main target group of this analysis are therefore hedge funds and investors that run short-term strategies. Due to the fact that the widespread Event Study Methodology is focused on the long-term, it is irrelevant for this analysis.

Companies who want to be component of DAX or MDAX have to publish quarterly earnings announcements. These earnings announcements were originally designed to report the company’s financials for the prior period, but they more and more expanded, including forecasts about the company’s future performance in the meantime. The quantitative part, also called accounting information, is measurable and relatively easy to interpret, but qualitative information, such as an outlook for future earnings, is more challenging. On the basis of the financial data published in these interim reports, analysts as well as the company itself set respectively change their estimates for the fiscal year concerning the company’s earnings. If it emerges that the company recognizes those estimates to substantially differ from the actual ones before the interim report is published, the company has to announce a profit warning in order to keep information equilibrium.

In order to gain superior stock returns without bearing extra risk requires the market to be inefficient or, in other words, not in equilibrium.

There are two predominant theories regarding the topic of market efficiency and rationality, the efficient market hypothesis (EMH) and the behavioural finance theory.

The EMH, introduced by Fama (1970, p. 383), understands the market to always be efficient by the immediate adjustment of prices and information equilibrium. In contrast to the EMH, the behavioural finance theory argues that prices are often driven by irrational investors. Shiller (1981) was the first one who used volatility studies in order to test market rationality. Moreover, there is statistical evidence that a significant degree of stock returns can be predicted by quantitative information of the company as well as multipliers, such as price-earnings ratios (P/E), book-to-market ratios (BE/ME) or market capitalisation (Campbell and Shiller, 1987).

1.2 Course of the Investigation

In accordance with the aim of this paper mentioned above, the following course of the investigation results: After the introductory comments, chapter 2 presents theoretical foundations relevant for this study. Besides basic information, such as the determination of stock prices as well as legal requirements for the analysed stocks, chapter 2 furthermore presents the efficient market hypothesis (EMH), which used to be, until recently, the predominant theory for explaining capital markets. Moreover, the theory of anomalies and abnormal performance is presented. This topic is presented because of the fact that stock price performance that could not be explained by the EMH is the basis for this paper.

Chapter 3 presents a more in-depth theoretical discussion on stock price behaviour after earnings announcements. The prevalent theory, which is also the basic framework of this study, is the behavioural finance theory that is contrary to the EMH. This part presents several theories regarding decision theory of market participants in different scenarios. This part is furthermore used to compare the findings of the analysis of this paper to the past findings in the economics literature. Moreover, this chapter goes into details concerning investment strategies and asset pricing models, addressing several of the most important ones. In order to round out the presentation of asset pricing models, the chapter ends with addressing the existence of bad-model problems.

The practical examination of this paper’s topic is presented in chapter 4. The sources of all data used are presented in this part, which are the datasets of companies as well as the time period used for the analysis. Furthermore, the benchmarks are mentioned, which provide a basis of comparison. After having separated the dataset into specific groups (“Portfolios”), the results of the examination are presented. The results are divided into two subchapters, whereby the first subchapter investigates differences between a bull- and a bear market scenario; the second subchapter differentiates between the pre-announcement performances, whether it was positive or negative. The chapter ends with bringing up the existence of outliers and possible reasons for the occurrence.

A conclusion summarizes all important implications of the study regarding the impact of quarterly earnings announcements to stock prices.

As this analysis is not based on empirical evidence, there is the possibility that the results are not representative.

2 Theoretical Foundations

2.1 What Determines a Stock Price?

The market price of a share is determined by its supply and demand on the Stock Exchange. It is agreed between a buyer and a seller in a stock transaction. The question rather is which factors indirectly influence the market price. A major event in terms of trading volume is the quarterly earnings announcement (see figure 1). At this event, quantitative news as well as qualitative news are published and both types of news can influence the stock price indirectly. This is because of the fact that these news reflect the past performance of the company, but on top, these news give a forecast of the future performance of the company. Quantitative news, such as sales or net income of the past quarter lead to certain multipliers, such as earnings per share (EPS), dividend per share (DPS) or the price-earnings (P/E) ratio. All of them are crucial to the investment behaviour of the most investors. Qualitative news on the other hand is the forecast, given by the company’s management, on the future performance of the company as well as an outlook for the fiscal year of the company. This outlook can range from full-year accounting outlook, for example sales/earnings outlook, to future growth or M&A plans.

Figure 1: Trading Volume around earnings announcements

Abbildung in dieser Leseprobe nicht enthalten

From Morse (1981), p. 381

2.2 Prime Standard

All companies analysed in this paper used to be components of either DAX or MDAX at the point of time when the data was collected[1]. DAX and MDAX together contain the 80 largest German companies in terms of market capitalisation and stock market turnover with a free float of at least 5%. In line with Deutsche Börse Group (2008), for being accepted in DAX or MDAX, the Prime Standard obligations have to be fulfilled on top: Shares must be listed in the regulated market, the company has to publish quarterly reports in German and English, apply international accounting standards (IFRS/IAS or US-GAAP), publish a financial calendar, stage at least one analyst conference per year, publish ad hoc disclosure in English and German and follow-up obligations of General Standard.

2.3 Ad Hoc Publicity

In this paper, price movements around quarterly earnings announcements are analysed. However, if there has been an ad hoc announcement close to the interim report that carries along stock price reaction, I will use this date as t0 instead of the date when the interim report has been published, because such a profit warning releases the bulk of stock price sensitive information of an interim report. §15 WpHG (2005) clearly defines that the respective issuer of a financial instrument, traded in the domestic organised market, instantly has to release insider information. Insider information is defined as information that is able to influence stock prices substantially when published.

A crucial ad hoc announcement, in terms of stock price reaction, is the profit warning: According to Pirelli’s Financial Glossary (2008), “the new forecast must be disclosed to the market as soon as it is clear that the previous forecast, due to the availability of new information, is now misleading and that the previous target can't be reached.” Therefore, a profit warning has to be announced for far better or worse results than expected, as the case may be.

2.4 Market Efficiency

The prevalent theory regarding capital markets has been the EMH. The underlying assumption of the EMH is that prices are only influenced by information. The EMH, in its crudest form, effectively says that returns from speculative assets are unforecastable. For the first time this thesis appeared as the random walk theory by Bachelier (1900, 1964), cited by Courtault, Kabanov, Bru, Crépel, Lebon and Le Marchand (2000, p. 343 - 344). It has been confirmed empirically by Cootner (1964) and several times since.

Fama (1970, p. 383) differentiates between three forms of market efficiency depending on the degree of information reflected in stock prices: The weak form of market efficiency only uses historical prices; the semi-strong form considers information that is obviously publicly available on top, such as earnings announcements, capital increases or stock splits. The strong form of market efficiency prices in private information on top, information, which “investors or groups have monopolistic access to”. Fama, Fisher, Jensen and Roll (1969, p. 20) came to the result that markets are at least semi-strong efficient, as they conclude their work, amongst others, with the sentence “Thus the results of the study lend considerable support to the conclusion that the stock market is ‘efficient’ in the sense that stock prices adjust very rapidly to new information.”

According to Malkiel (1992), a capital market is perfectly efficient if it fully and correctly reflects all relevant information in determining security prices. The market is efficient with respect to a certain information set, if security prices would be unaffected by revealing that information to all participants. This hypothesis is also addressed by Louhichi (2008), but he adds that “empirical studies show that this extreme version of market efficiency hypothesis is not valid”. In fact, “recent tests focus on the degree of market efficiency” (p. 102), which is the speed of adjustment of stock prices to new information. In his point of view, a perfectly efficient market immediately adjusts prices to market news, an inefficient market adjusts prices slowly (see figure 2). Jones and Litzenberger (1970, p.147) furthermore prove empirically that the stock market is not as perfect as random walk theorists claim. They also add that the market does not always adjust intermediately and correctly.

Figure 2: Efficient versus Inefficient Market

Abbildung in dieser Leseprobe nicht enthalten

From Goriaev, 2008, slide 5.

2.5 Anomalies and Abnormal Performance

As already mentioned above, the existence of anomalies raises doubts about the existence of a perfectly efficient market and is therefore in conflict with the EMH.

The conception ‘abnormal returns’ means “the return to a portfolio in excess of the return to a market portfolio.” (About.com, 2008). Brown and Warner (1980, p. 205) highlight that abnormal returns can only be defined in the way of finding the normal return firstly. In order to do this, the authors argue that a model has to be specified. They tested three general models, which are general representations of the models used in event studies. The models are the Mean Adjusted Returns Model, the Market Adjusted Returns Model and the Market and Risk Adjusted Returns Model, whereby the Mean Adjusted Return equals the difference between the observed and predicted return of the security, the Market Adjusted Return equals the difference between the return of the security and the return on the market portfolio. The Market and Risk Adjusted Return is a little more complicated, a representative example would be the two factor asset pricing model of Black (1972, p. 446).

For each of the three models, the basic assumption is the same:

Abbildung in dieser Leseprobe nicht enthalten ,

where Rit is the realised return on security i in period t, Kit is the expected return, given by the model and εit is the abnormal return.

The assumption of studies focussing on short return windows is that any lags in adjusting prices to certain events are short lived. In line with Fama (1998, p. 284), there is a developing literature that challenges this assumption. The assumption here is that stock prices adjust slowly to information. Fama argues that one has to examine returns over long horizons to get a full view of market efficiency. In order to present such a full view of market efficiency, I will show theories of anomalies that are over long-term horizons as well.

DeBondt and Thaler (1985, p. 804) wrote one of the first papers focussing on long-term return anomalies. They discovered that stocks that are ranked on three- to five-year past returns, past winners tend to be future losers and vice versa.

The size effect is a negligible anomaly with respect of the data set I took for my analysis as the size effect says that stocks with a smaller market capitalization outperform stocks with a larger one (Banz, 1981, p. 16). Due to the fact that I took Germany’s largest stocks in terms of market capitalisation, there cannot exist a representative size effect.

Fama and French (1992, p. 451) find that book equity to market equity (BE/ME) capture much of the cross- section of average stock returns. The book equity is the net asset value (NAV) of a company, calculated by total assets minus intangible assets and liabilities, the market equity is calculated by multiplying the share price with the total outstanding shares. The authors argue that BE/ME is related to persistent properties of earnings. Fama and French (1995, p. 154) furthermore figured out that stocks with a high BE/ME ratio, which implies a low stock price relative to book value, are less profitable than low BE/ME stocks. Companies with a low BE/ME are therefore growth companies, a high BE/ME ratio is typical for companies that are distressed. Combining the size and BE/ME effect, small stocks tend to have lower earnings than big stocks. Moreover, Fama and French (1995) support the findings of Penman (1991, p. 240) that low BE/ME companies remain more profitable than high BE/ME companies for at least five years after forming the portfolio on BE/ME. However, the authors also concur with Lakonishok, Shleifer, and Vishny (1994, p. 1575) that growth rates of low and high BE/ME stocks become more similar over the years after portfolio formation. Lakonishok, Shleifer, and Vishny (1994) conclude that the higher returns of high BE/ME stocks over the years after portfolio formation are the result of correcting irrational prices by the market.

The P/E effect was firstly addressed by Nicholson (1960) and later confirmed by Basu (1983, p. 150). Both came to the conclusion that stocks with a low P/E ratio seem to have earned, on average, higher returns than stocks with a high P/E ratio.[2] Basu also argues that the P/E effect is stronger than the size effect. He arguments in the following way: “This E/P effect, furthermore, is clearly significant even after experimental control was exercised over differences in firm size, i.e., after the effect of size, as measured by the market value of common stock, was randomised across the high and low E/P groups. On the other hand, while the stocks of small NYSE companies appear to have earned considerably higher returns than the stocks of large NYSE companies, the size effect virtually disappears when returns are controlled for differences in risk and E/P ratios.” (p.150).

Bhandari (1988, p. 527) documents the debt-equity ratio. His findings are that leverage is positively related to expected stock returns. Leverage is measured as the book value of debt over the market value of equity. High debt-equity stocks have returns that are too high to be explained by their market betas.

Jegadeesh and Titman (1993, p. 67; 2001, p. 699) describe momentum investing as a strategy of taking long positions in stocks that have had returns exceeding market average over the past three to twelve months and short positions in stocks that have had returns below market average over the same period. They tested this system in the US market and came to the result that this system earns profits of about one percent per month for the following year. Rouwenhorst (1998, p. 268) reports that these momentum profits also obtain for the European market. Referring to Sadka (2005, p. 2), the momentum anomaly is one of the biggest challenges to asset pricing. These high abnormal returns gained with momentum investing are the effect of some type of bounded rationality of investors, such as underreaction to information or overconfidence.

Besides price momentum drift, the literature has also documented a price drift after earnings announcements. In line with Sun (2005, p. 1), “post-earnings announcement drift is one of the most robust anomalies in the asset pricing literature.” As the name implies, post-earnings announcement drift (PEAD) is the continuation of abnormal returns after earnings announcements. Ball and Brown (1968, p. 170) have been the first to argue that investors tend to underreact to earnings announcements. Empirical evidence followed, showing that good-news companies respectively companies with high standardized unexpected earnings (SUE) outperform bad-news respectively low SUE companies. PEAD had been tried to be interpreted in the context of EMH in early studies, but the observed price drift exceeded the range that could be accounted by EMH. Barberis, Shleifer and Vishny (1998, p. 312) argue that PEAD is caused by investor’s underreaction to earnings news and therefore lean this anomaly towards behavioural finance.

The continuance of momentum and PEAD anomalies raises serious doubts about the EMH. However, Fama (1998, p. 285) arguments that overreaction of stock prices was as common as underreaction and therefore chance results.

The disposition effect anomaly is the tendency of investors to sell shares too early, whose price has increased, while holding shares too long that have dropped in value (Shefrin and Statman, 1985, p. 779). Investors are unwilling to recognize losses, but they are willing to recognize gains. This loss aversion was firstly addressed by Kahnemann and Tversky (1979, p. 286). Sun (2005, p. 2) hypothesises that stocks are always temporarily depressed on dates of earnings announcements due to excessive supply. He argues that investors only sell, when a premium is offered, which implies that any trading will temporarily be on an inflated price. On the other hand, investors rapidly sell stocks with good earnings announcements in order to lock in profits. Both arguments strengthen the tendency of underreaction on the day of earnings announcement.

3 Theoretical Discussion on Stock Price Behaviour after Earnings Announcements

3.1 Behavioural Finance

Since anomalies challenge the validity of the EMH, a new capital markets theory arose, the behavioural finance theory. In contrast to the EMH, the behavioural finance theory assumes a market that is not fully rational. Stock prices are influenced by the actions of market participants.

Some central issues in behavioural finance are why investors and managers make systematic errors and how those errors create market inefficiencies. Among such inefficiencies, underreactions or overreactions to information are often cited.

Barberis, Shleifer and Vishny (1998) and Daniel, Hirshleifer and Subrahmanyam (1998) present behavioural models that accommodate such overreaction and underreaction.

The model of Barberis, Shleifer and Vishny (1998, p. 315) is motivated by evidence from cognitive psychology of two judgement biases, the conservatism and the representativeness heuristic. The conservatism bias, firstly identified by Edwards (1968), states that individuals change their beliefs in the face of new evidence only slowly. Edwards compares a subject’s reaction to new evidence to an idealised rational Bayesian. He comes to the conclusion that individuals change their opinion proportional to the Bayes Theorem, but insufficient in amount. Conservatism therefore is very suggestive of the underreaction evidence. The second bias in the model is the representativeness heuristic, documented by Tversky and Kahnemann (1982, p. 33). An important revelation of this bias is that people think they see patterns in random sequences. Representativeness heuristic is therefore suggestive of the overreaction evidence. Investors using representativeness heuristic may overreact in a way that they see companies that have continuously grown for a certain time repeating itself in their success. As a consequence, they will overvalue this certain company and be disappointed in the future when the expected earnings fail to materialize.

In a more recent study, Griffin and Tversky (1992) try to reconcile conservatism and representativeness heuristic. Strength and weight are the two characteristics in their framework. Strength refers to aspects such as salience and extremity, whereby weight refers to statistical informativeness (p. 412). Comparing to a rational Bayesian again, according to Griffin and Tversky, news with more strength would generate a bigger reaction from investors (p. 432). Merging the Edwards (1968) theorem with the one of Griffin and Tversky (1992), conservatism would occur in the face of evidence with high weight and low strengths, representativeness heuristic the other way round. To sum up the model of Barberis, Shleifer and Vishny (1998), individuals might underweight information of an isolated quarterly earnings report, but overweight consistent patterns occurring over several years, such as noticeable high or low earnings growth (p. 333). DeBondt (1993, p. 368) confirms these findings by finding strong evidence that people extrapolate past trends. Barberis, Shleifer and Vishny (1998) argue that their findings challenge the EMH, because investors can take advantage of under- and overreactions and therefore earn very high returns without taking extra risk (p. 308).

The model of Daniel, Hirshleifer and Subramanyam (1998, p. 1845) is related to the one of Barberis et al., but uses different behavioural foundations. This model assumes the existence of informed and uninformed market participants, whereby the informed determine the stock prices and the uninformed are not subject to judgement biases. Moreover, the informed are subject of two different biases, the investor overconfidence on the one hand, which leads investors to exaggerate the precision of private information, and biased self-attribution on the other hand, which leads them to underweight public signals, especially when the public signals contradict to their private signals. The authors show that overconfidence tends to produce short-term continuation of stock returns, but long-term reversals. Another new assumption of the authors is selective event, which occur in order to take advantage of the mispricing of a company’s stock, such as share buybacks or capital increases. Capital increases are usually made when the company’s stock price is at a very high level, shares will be bought back at a very low level. The authors argue that such public signals immediately produce price reaction that regulates some of the mispricing.

Another approach of behavioural finance comes from Gaunt (2004, p. 28). According to him, the most common behavioural finance theory is that the market overreacts to both good and bad company performance. As a result of his findings, he concludes a poor judgement by the market, which derives a tendency of people to overweight the value of recent information.

[...]


[1] August 2007

[2] Basu used an E/P ratio instead of a P/E ratio, which used to be more common. Nowadays only the P/E is used.

Details

Pages
51
Year
2008
ISBN (eBook)
9783656972419
ISBN (Book)
9783656972426
File size
1.1 MB
Language
English
Catalog Number
v300329
Institution / College
EBS European Business School gGmbH – Finance
Grade
1.1
Tags
stock price reaction quarterly earnings announcements

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Title: Stock Price Reaction to Quarterly Earnings Announcements with respect of outlook changes and deviation to consensus forecast