اهمیت اطلاعات، تمایلات سرمایه گذار و سهام بازده: مورد شرط بندی فوتبال انگلیس
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|13438||2009||20 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Corporate Finance, Volume 15, Issue 3, June 2009, Pages 368–387
Soccer clubs listed on the London Stock Exchange provide a unique way of testing stock price reactions to different types of news. For each firm, two pieces of information are released on a weekly basis: experts' expectations about game outcomes through the betting odds, and the game outcomes themselves. The stock market reacts strongly to news about game results, generating significant abnormal returns and trading volumes. We find evidence that the abnormal returns for the winning teams do not reflect rational expectations but are high due to overreactions induced by investor sentiment. This is not the case for losing teams. There is no market reaction to the release of new betting information although these betting odds are excellent predictors of the game outcomes. The discrepancy between the strong market reaction to game results and the lack of reaction to betting odds may not only be the result from overreaction to game results but also from the lack of informational content or information salience of the betting information. Therefore, we also examine whether betting information can be used to predict short-run stock returns subsequent to the games. We reach mixed results: we conclude that investors ignore some non-salient public information such as betting odds, and betting information predicts a stock price overreaction to game results which is influenced by investors' mood (especially when the teams are strongly expected to win).
It is now widely acknowledged that individuals have limited information processing abilities. As Herbert Simon (1978: 13) mentions “many of the central issues of our time are questions of how we use limited information and limited computational ability to deal with enormous problems whose shape we barely grasp”. As a consequence of this limited processing ability, investors may concentrate their time and attention to highly visible, easy to process information. In other words, limited processing ability may generate limited attention. One of the consequences is that reactions to public news depend on its relative salience: the higher the information salience (i.e. media coverage), the faster the public information is processed by investors and is reflected in the share prices. In the recent past, several articles have reported empirical evidence about asset price reactions to public news consistent with the salience theory. Studying closed-end country funds, Klibanoff et al. (1998) show that country-specific information which does not receive large media coverage is incorporated only gradually into the share prices. In a case study, Huberman and Regev (2001) describe EntreMed's substantial and permanent stock price rise after a ‘special report’ on new cancer-curing drugs on the front page of the Sunday edition of the New York Times (NYT). This is remarkable as the NYT article did not contain any new information: the potential breakthrough had already been reported five months earlier in the scientific press (an article in Nature) and in the popular press (including the NYT itself but then not on a prominent place—in a tiny article on page A-28). Chan (2003) studies market returns following prominent public news, i.e., firm-related information that made the headlines or a lead article, and finds that investors react slowly to bad news. A recent study by Gilbert et al. (2007) shows that investor inattention influences the aggregate stock market. Investors' constraints in information processing are not only characterized by ignoring relevant news but also by misinterpreting the relevance of news. In particular, studies on behavioral finance argue that investors are subject to sentiment (e.g. De Long et al., 1990).1 Some recent papers study the impact of exogenous changes in investor emotions on share prices (e.g. Kamstra et al., 2003). When arbitrage against sentiment-prone investors is risky and costly, mispricing may persist in financial markets (Shleifer and Vishny, 1997). An example of investor sentiment is the study by Edmans et al. (2007) who investigate the impact of international soccer results on stock market indices. They find a significant market decline after losses by national soccer teams in international soccer competitions. The authors demonstrate that this loss effect is caused by a change in investor mood.2 Indeed, soccer results influence investor sentiment but have little direct economic impact. Edmans et al. also show that the stock market effect is stronger for countries with a prominent soccer tradition, for games in the World Cup and for elimination games, and for smaller stocks. English and Scottish professional soccer teams listed on the London Stock Exchange (LSE) provide a unique way of studying the stock price reaction to different pieces of news while controlling for the informational content. For each of these stocks, betting markets and stock markets co-exist and two pieces of information are released on a weekly basis from August to June: betting odds and game results. Listed soccer teams are also interesting study objects because the performance of the team is greeted with lots of emotion and media coverage. The objective of this paper is not to identify a profitable trading strategy, but to analyse the impact of investor sentiment and information salience on news absorption by the stock market by studying the difference in the market reactions to these two types of news. Soccer betting in the UK occurs via a fixed-odds procedure: the odds are posted several days prior to the game and are very rarely altered in response to betting before the event. This fixed-odds betting system is different from the pari-mutuel system (as often used in betting on horse races) and from the point spread betting system (used for the most popular sports in the US), in which odds respond to betting volumes and thus represent a consensus in investors' opinions. Within a fixed-odds betting system, the odds represent only the bookmakers' (or their experts') opinions.3 Hence, investors are informed on a weekly basis about the experts' beliefs about the game outcomes (through the odds that the bookmakers publish), and the game results. Both these types of news provide new information about the performance of the teams/firms. However, they differ in four crucial ways. First, betting odds represent experts' opinions about game outcomes while game results represent information about realizations. Second, betting odds offer short-lived information. After two trading days, the game outcome is known and the information value contained by the betting odds has evaporated. As a consequence, if betting odds do contain valuable information, markets must be fast in processing this information. Third, while a victory or a defeat of soccer clubs clearly shifts investor mood, betting odds hardly have any impact on sentiment. Finally, these two types of information also differ in their level of salience. Betting odds are publicly available but are only posted on bookmakers' websites and in ‘betting shops’. In contrast, game results are virtually omnipresent: they are extensively discussed in all daily newspapers, on the television news, and in a variety of sports shows on prime time. Our paper is structured around four questions: (i) Do victories and losses trigger significant stock price and trading volume reactions?, (ii) Do the market reactions reflect rational expectations or overreaction induced by information salience/investor sentiment?, (iii) Does the release of betting information trigger stock price and trading volume reactions?, and (iv) Can betting odds predict stock returns and do investor sentiment or information salience explain the differences in the market reactions to the two correlated sets of news? Our findings yield a mix of results. Our first question is answered affirmatively: the market reacts strongly to game results, generating abnormal trading volumes and abnormal returns in the days following the games. Over a three-day period subsequent to the game, we observe an average abnormal return of 88 basis points subsequent to a win, of − 101 basis points subsequent to a defeat, and of − 33 basis points following a draw. We also find that the market processes good news faster than bad news, a result consistent with the literature (see e.g. Hong et al., 2000 and Chan, 2003). After a victory, a significant positive average abnormal return is observed on the first trading day subsequent to the games, but not on the following days. Bad news (i.e., defeats) is processed more slowly as we observe significant negative abnormal returns on the first three trading days after a game. These results suggest that information about game results is used extensively by investors. Since the game results represent ‘hard’ information about future earnings, our study is related to those on stock price (under-)reaction to earning announcements (see e.g. Ball and Brown, 1968, Bernard and Thomas, 1989, Chan et al., 1996 and Frazzini, 2006). Our paper is also related to the studies by Renneboog and Van Brabant (2000) and Brown and Hartzell (2001) who study the stock price reactions to game outcomes for listed sports clubs.4 Our second question asks whether the above market reactions reflect rational expectations or overreaction induced by investor sentiment or information salience. The results yield nuanced answers. The rational expectations hypothesis argues that there is a clear and direct relation between the financial performance as measured by the stock returns, and the team's performance on the field for the following reasons. First, the proceeds from the national TV deals are redistributed to the teams according to a performance-based scheme, i.e., the end of season ranking (see Falconieri et al. (2004) and Palomino and Sakovics (2004) for details). Second, if a team ends the season ranked among the first four of the top league (the Premier League in England), it has the right to participate in the lucrative European competition (the UEFA Champions' League) in the following season.5 For teams playing in the First Division (the football league below the Premier League), promotion to the Premier League also brings about a significant increase in income from television rights.6 Third, field performance has a direct impact on ticket sales, merchandising and sponsorship revenues. Soccer games also reveal information about the players' quality to investors. For all these reasons, game-outcome related information should have an impact on the stock price.7 Consistent with the rational expectations hypothesis, we find that the average abnormal returns of about 1% (− 1%) over the first three days following a win (a loss) is comparable to the average sales revenue derived from a given game for a soccer club. The market reactions to game outcomes are also not transitory in the short run. Firms without a large institutional owner are not subject to stronger market reactions. However, a set of other tests gives more support to the investor sentiment explanation. For instance, smaller clubs are associated with stronger market reactions to game results. Furthermore, investors react strongly to a win, especially when the win was strongly expected (and hence should not create a surprise effect). Investor sentiment thus causes an asymmetric share price reaction: wins trigger abnormal returns due to a positive sentiment but, consistent with the rational expectations hypothesis, the market reaction to a loss is weaker the higher its ex ante probability. Our third question is answered negatively: we cannot find any evidence of a market reaction (neither in volume nor in returns) following the release of betting odds. It may be that the odds do not contain any new information unknown to investors even though we demonstrate that bookmakers' experts are excellent predictors of the games' results. Alternatively, the odds can contain new information which is not processed by investors or is too costly to trade on. The absence of a market reaction may hence be explained by a lack of information salience, or by high bid/ask spreads. Our study differs from previous analyses of the reaction to public news events in two important ways. First, we analyse the difference in the reaction to two pieces of news, i.e. betting odds versus game results that differ in their sentiment and salience levels. Second, one type of news (the betting odds) in our study is released with high frequency and is short-lived. After two trading days, our betting odds do not contain further information as the game outcomes are known. Since betting odds represent opinions about earnings-related information, our study is also related to the literature on (under-)reaction to revisions of earnings forecasts (see e.g. Givoly and Lakonishok, 1979, Chan et al., 1996, Womack, 1996 and Daniel et al., 1998). Combining analysts' forecasts and salience (media coverage) levels, Bonner et al. (2005) show that the investors' reactions to revisions of analysts' forecasts depend on the media coverage of these revisions. 8 However, there are also crucial differences between information released by bookmakers and that released by equity-analysts. Bookmakers, whose expected profits are determined by betting odds, are less subject to the biases documented about these analysts, i.e., systematic optimism ( Easterbrook and Nutt, 1999), conflicts of interests for analysts working for brokerage firms ( Michaely and Womack, 1999), and incentives to herd (see, e.g., Trueman, 1994, Welch, 2000, Hong et al., 2000 and Clement and Tse, 2004). Our fourth question is whether betting odds can be used to predict the stock returns subsequent to the game outcome, and whether information salience or investor sentiment explains the differential market reactions to betting odds and game results. To test the predictive power of fixed odds on stock returns, we compute the average cumulative abnormal returns (ACARs) conditional on the strength of the experts' predictions as reflected in the betting odds (strongly expected to win, weakly expected to win, weakly expected to lose, strongly expected to lose). In particular, we observe that the 3-day (statistically significant) average abnormal return is 64 basis points subsequent to the game outcome when the team was strongly expected to win ex ante. This suggests that betting odds contain new information to investors (which is in contrast to the rational expectations hypothesis). A naïve 60-day trading strategy whereby an investor buys a share in a firm that is strongly expected to win and sells after 3 months (regardless of the intermediate news) yields on average between 175 and 245 basis points over and above the expected returns. Remarkable is that significant abnormal returns only emerge when teams are strongly expected to win and not when teams are weakly expected to win or strongly expected to lose. The asymmetric predictability of betting odds to stock returns following wins and losses and the fact that there is still a market reaction when the outcome is most anticipated, does not support the information salience hypothesis. These results imply that investor sentiment influences news absorption by the stock market, and betting information predicts an overreaction in stock prices. The structure of this paper is as follows. Section 2 provides a description of the fixed-odd betting system. Section 3 discusses the dataset and Section 4 focuses on methodology. Section 5 presents the results while Section 6 discusses their robustness. Finally, Section 7 concludes.
نتیجه گیری انگلیسی
We started off asking the question whether or not the stock market incorporates the news of victories, defeats and draws of listed British soccer clubs. The average cumulative abnormal returns over a three day period are strongly statistically significant for wins and losses and amount to 88 basis points for a victory, − 101 basis points for a defeat, and − 33 basis points for a draw. We also find that markets are very fast in processing good news about game outcomes (most of the impact of a victory is incorporated in the share prices during the first trading day) and somewhat slower in incorporating bad news (defeats). On the first trading day following a game, we observe significant share volume increases. A second question emerges as to whether these market reactions reflect rational expectations (as the previous literature shows a relation between game outcomes and future operating performance) or the abnormal returns can be explained by investor sentiment or information salience. While the weekly value changes represented by the abnormal returns could be justified by the potential change in discounted cash flows, we find evidence of investor overreaction following the game outcomes. We apply several tests to study investor mood and information salience: Are the abnormal returns transitory? Are smaller firms and firms with no institutional owners more prone to overreaction? Are the market reactions to wins or losses weaker, the higher the ex ante probability of those outcomes? Our most convincing test gives evidence that investors overreact to a win, especially when the win was strongly expected and hence should not have created a surprise effect. Investor sentiment also causes an asymmetric share price reaction: wins trigger abnormal returns due to a positive sentiment, but, consistent with the rational expectations hypothesis, the market reaction to a loss is weaker the higher its ex ante probability. Investors' loyalty to their clubs may lead to fewer share sales in the wake of bad news. Our third question is about how the market receives the experts' opinions about the probability of the game outcomes. These opinions are embedded in the betting information (fixed odds) which is released some days prior to the games. We do not find any significant reaction (neither in share prices nor in trading volumes) to the release of betting odds by bookmakers. This is particularly interesting as we show that the betting odds are excellent predictors of the game outcomes. It is now widely acknowledged that individuals have limited information processing abilities. One of the consequences is that the way information is processed may depend on its relative salience, i.e., the media coverage it receives. Professional soccer clubs listed on the London Stock Exchange provide a unique way of studying stock price reactions to different types of news since two pieces of news are released on a weekly basis from August to June: betting odds which incorporate information about the expected future performance, and game results which capture information about the realized performance. Furthermore, these two types of information differ in their level of salience: game results receive very high media coverage (in all daily newspapers, in the television news, and in sports shows on prime time), while betting odds are only posted on bookmakers' websites, in specialized sports magazines and in betting shops. In contrast to the significant volume and share price reaction subsequent to the game results, there is none subsequent to the release of the betting odds. This may be due to the fact that the latter information is not salient. Still, some caution is needed with this interpretation as it may be that the odds do not contain any new information that has not yet been incorporated into stock prices. Also, the bid-ask spreads of the listed soccer clubs (which are mostly small caps) are high such that developing a profitable trading strategy may be difficult. Due to the absence of a market reaction to the disclosure of betting odds, we ask our fourth question: can betting odds be used to predict short-run market returns? Formally, to test the predictive power of fixed odds on stock returns, we compute the ACARs conditional on the strength of the experts' predictions as reflected in the betting odds (strongly expected to win, weakly expected to win, weakly expected to lose, strongly expected to lose). In particular, we observe that the 3-day (statistically significant) average abnormal return is 64 basis points subsequent to the game outcome when the team was strongly expected to win. This suggests that betting odds contain new information to investors (which does not support the rational expectations hypothesis). A naïve 60-day trading strategy whereby an investor buys a share in a firm that is strongly expected to win and sells after 3 months (regardless of the intermediate news) yields on average between 175 and 245 basis points over and above the expected returns. However, the potential trading profits largely disappear when transaction costs are taken into account. Remarkable is that significant abnormal returns only emerge when teams are strongly expected to win and not when teams are weakly expected to win or strongly expected to lose. The asymmetric predictability of betting odds to stock returns following wins and losses and the fact that there is still a market reaction when the outcome is most anticipated, does not support the information salience hypothesis but leads to our conclusion that investor sentiment influences the news absorption by the stock market.