Sports Sentiment and National Stock Markets: Do the Win and Loss Effect Really Exist?

Sports Sentiment and National Stock Markets: Do the win and loss effect really exist? 12/06/2019 Abstract: Motivated by previous studies on sports sentiment, this paper investigates whether there exists a relationship between changes in the return on national stock market indices and international football results. Using data from 25 countries at major football tournaments, this study adds value to the ongoing debate on the so-called win and loss effect of football games on stock returns. After controlling for the ability bias between countries, there exists neither a significant relationship between stock returns and wins, nor a relationship between stock returns and losses. Correcting for the time-varying volatility of stock returns using a GARCH(1,1) model does not significantly improve these findings. Robustness checks are performed to check whether the results change when the data is separated based on tournaments, time spans and quality. JEL Classification: G14, G41, Z23 Keywords: football results, investor sentiment, stock market index, market efficiency Combined Master Thesis Economics & Finance ’18-‘19 Ruud Bossink – S2756277 [email protected] Supervisor: Prof. dr. R.H. Koning University of Groningen – Faculty of Economics and Business Course codes: EBM877A20 (Economics), EBM866B20 (Finance) 1. Introduction The efficient market hypothesis states that all available information is fully reflected in asset prices (Fama, 1970). Market prices only respond to new information; therefore it is impossible to beat the market on a long-term basis, according to the efficient market hypothesis. Recent literature has studied deviations from the efficient market hypothesis caused by behavioral biases. For example, Hirshleifer and Shumway (2003) found that sunshine is strongly correlated with stock returns. This relationship is caused by upbeat mood. Frieder and Subrahmanyam (2004) confirm that certain religious holidays, like St. Patrick’s Day, lead to abnormal positive returns, while other religious holidays, like Rosh Hashanah, are negatively correlated with stock returns. This paper will use a different variable for upbeat mood to examine its relationship with a country’s national stock index, namely international football results. A mood variable should satisfy three certain characteristics (Edmans, García and Norli, 2007). Firstly, the variable should drive mood substantially, so the effect is powerful enough to affect the return on assets. Secondly, the variable should impact the mood of a large part of the population to ensure that it covers most investors. Thirdly, the effect should be correlated across most individuals within a certain country. International football results are likely to satisfy all three criteria. Sport results in general have a substantial effect on mood. This is especially the case for football, one of the most popular sports around the globe. Major events like World Cups are likely to take a grip of the majority of a population. According to Wann, McGeorge and Allison (1994), fans react positively to good team performance and negatively to poor team performance. Media coverage shows that football is of ‘national interest’ around the globe. Last year, more than 3.5 billion people watched some official broadcast coverage of the FIFA World Cup 2018 in Russia.1 The World Cup final of 2002 between Germany and Brazil was viewed by more than 1 billion people worldwide. It is hard to think of other events that have an impact on the population’s mood as big as the impact of worldwide football tournaments. While national football results impact the entire country in a similar way, other popular sports, like baseball and American football, are merely played on a club level rather than on country wide level. The characteristics above provide a strong motivation for using football results to examine mood changes of investors and is the key strength of this study. 1 2018 FIFA World Cup Russia™: Global Broadcast and Audience Summary 2 The two main approaches used in previous literature on the topic of interest are the event study approach and the continuous variable approach. There are multiple examples of studies using either an event study approach or a continuous variable approach. Kamstra, Kramer and Levi (2000) used an event study approach to examine the effect of changes in daylight saving on the disruption of sleeping patterns. Three years later they analyzed daylight with a continuous variable approach (Kamstra, Kramer and Levi, 2003). The main advantage of the event study approach, rather than the continuous variable approach, is that the former gives a high signal- to-noise ratio in returns, because sudden changes in investor’s mood can be identified clearly. The main disadvantage of the event study approach is that the number of observed signals often appears to be low. In this study, a continuous variable approach is used. Some papers that used the same approach are Edmans et al. (2007) and Fan and Wang (2018). The reason that the continuous variable approach is preferred over an event study approach is that football wins and losses occur often, and not on a single event basis. When an event study approach is used, there needs to be a discrete event. In the case of sports sentiment, this could be the winning of the final at a major football tournament. In this study, not only these finals are taken into account, but all other matches during major football tournaments as well. This leads to a total of 1361 games. Kamstra et al. (2000) preferred an event study approach, because changes in daylight saving only occurs twice a year, once close to the start of spring and once in autumn. Since hundreds of football games are played each year by national teams, it is hard to distinguish single events and the event study approach is not very applicable. The reference point of this paper is the study of Edmans et al. (2007). However, this study is not a replication study. Contrary to Edmans et al. (2007), in this study draws are added to the dataset, because draws do not necessarily lead to a neutral response in investor’s sentiment. A draw of a relatively weak football nation against a strong football nation can feel like a victory for the weaker football nation. Take for example the draw of Morocco against Spain at the FIFA World Cup 2018 in Russia. Besides, a draw can sometimes lead to qualification to the next round. Hence, a draw can be a desired outcome as well. Compared to Edmans et al. (2007), this paper further examines the differences in ability between football nations to measure the unexpectedness of a certain football result. Rather than using a dummy variable to indicate whether a football outcome is surprising or not, this study assigns a real number to the surprise effect. This way it is possible to distinguish the level of unexpectedness of game outcomes. When a win is expected, a draw is a less harsh surprise than a loss. Furthermore, losses or wins against two different football nations should be treated differently. Assume that England loses 3 a game against Croatia and a game against Iceland. Both losses are indicated as unexpected, because England is higher on the FIFA ranking than both Croatia and Iceland. However, the surprise after the loss against Iceland should be more pronounced, because the difference in FIFA ranking between England and Iceland is larger than the difference in FIFA ranking between England and Croatia. Later in this paper will be explained how the different levels of surprise are measured. Lastly, several robustness checks are added to check whether the results are sensitive to changes in tournaments, time spans and quality. Although most previous studies find a significant relationship between stock returns and football results, there are also studies that contradict these findings. The literature review outlines these different findings of previous papers. The fact that most of the previous studies use data before 2006 emphasizes the importance of this new study, using newly available data from football results until 2018. A follow-up study of Ashton, Gerrard and Hudson (2011) extended its previously used dataset and found that over the last period the effect of football results on stock results decreased. It will be interesting to examine whether this trend has continued during the last ten years. The research question in this paper reads: ‘‘How do national stock indices respond to changes in investor’s mood caused by international football results?’’ The hypotheses are that there exists a positive relationship between returns on stock markets and international football wins, and a negative relationship between returns on stock markets and international football loses. The rest of the paper is organized as follows. Section 2 discusses previous studies on the relationship between stock returns and sports sentiment. Section 3 shows from where the data is gathered, and which research method is used in this study. Section 4 gives the econometric results and section 5 concludes the paper. 2. Literature review In the field of financial economics, the efficient market hypothesis is the golden standard. Like stated in the introduction, asset prices fully reflect all available information according to this theory. When following this line of reasoning, there should not exists a relationship between stock returns and international football results. However, there are previous studies that found a relationship between these two variables. Together with studies that support the efficient 4 market hypothesis, these deviations from the efficient market hypothesis will be discussed in the following literature review. I. The loss effect A diverse range of studies on football results and stock returns have been published prior to this paper. Most of the researchers found a positive relationship between stock returns and wins, and a negative relationship between stock returns and losses. Edmans et al.

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