THE IMPACT OF FIFA WORLD CUP ON SPONSORING COMPANIES AND THE HOST COUNTRY STOCK MARKET INDEX - DIVA PORTAL

The Impact of FIFA
World Cup on Sponsoring
Companies and the Host
 Country Stock Market
 Index

 MASTER THESIS WITHIN: Business Administration
 NUMBER OF CREDITS: 15
 PROGRAMME OF STUDY: International Financial Analysis
 AUTHOR: Anas Alsaadi & Sayan Banerjee
 JÖNKÖPING May 2020

Master Thesis in Business Administration
Title: The Impact of FIFA World Cup on Sponsoring Companies and the Host Country Stock
Market Index
Authors: Anas Alsaadi & Sayan Banerjee
Tutor: Michael Olsson
Date: 2020-05-18

Abstract

 We investigate if the FIFA affects the sponsoring companies’ stock returns more than that of
 the host countries’ securities indices, we have presented the findings of earlier research entities
 and provided some insight into the influence of FIFA and other sports on global stock index.
 We have also made a detailed consideration of stock market reaction for the sponsoring
 companies’ securities and host countries’ security indices and found some articles about
 country wise investor sentiment based on match outcomes because they are the one to invest
 in the sponsoring companies or the host country security markets. Throughout our work we
 have tried to verify our hypothesis and support it with year-wise and host country-wise data
 through regression models and an event study. In the end, we have tried to come up with
 coherent findings based on the proven hypothesis and discuss their interpretations along with
 some possible predictions for the upcoming FIFA world cup in 2022.

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Contents
1 Introduction ........................................................................... 1
2 Theory..................................................................................... 2
2.1 Findings of Goldman Sachs ................................................................... 2
2.2 An Insight to Investor Behaviour and Their Consequent Investment
 Decisions That Affect the Stock Market ................................................. 5
2.3 Reason behind the impact of FIFA On Global Stock Indices and
 Comparison of Such Impact with That of Other Sports .......................... 6
2.4 Detailed consideration of the stock market reaction at various levels
 and their variations. ................................................................................ 8
2.5 Based on the previous literature review we have framed the following
 two hypotheses: ................................................................................... 15
3 Data ....................................................................................... 15
3.1 Countries research and their major indices and currencies ................. 15
3.2 Sponsors .............................................................................................. 16
3.3 Benchmark ........................................................................................... 16
3.4 Data description ................................................................................... 17
3.4.1 South Africa 2010 FIFA ........................................................................... 17
3.4.2 Brazil 2014 FIFA ..................................................................................... 18
3.4.3 Russia 2018 FIFA .................................................................................... 19
4 Method: ................................................................................ 19
4.1 Conducting the Event Study................................................................. 20
4.2 Estimation and Event Window ............................................................. 23
5 Results ................................................................................. 24
5.1 South Africa 2010 FIFA ........................................................................ 24
5.2 Brazil 2014 FIFA .................................................................................. 27
5.3 Russia 2018 FIFA ................................................................................ 28
6 Discussion ........................................................................... 29
6.1 Next event 2022 ................................................................................... 30
6.2 Ethics and sustainability ....................................................................... 31
6.3 Suggestions for future studies.............................................................. 32
References ...................................................................................... 34
Appendix ......................................................................................... 36

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Figures
Figure 1: Estimation and Event Window ............................................................ 24

Tables
Table 1: A tabulation of post-1 year and pre-1 year returns for the winners, The runner ups and
 host countries for the year 1974 to 2010. ................................................... 4
Table 2: Countries research and their major indices and currencies. ........................ 15
Table 3: Sponsors indices and currencies. ........................................................... 16
Table 4: Details of returns South Africa 2010 during FIFA. ................................... 17
Table 5: Correlation Matrix. .............................................................................. 18
Table 6: Details of returns Brazil 2014 during FIFA. ............................................ 18
Table 7: Correlation Matrix. .............................................................................. 18
Table 8: Details of returns Russia 2018 during FIFA............................................. 19
Table 9: Correlation Matrix. .............................................................................. 19
Table 10: South Africa 2010 FIFA NR&AR calculation. ........................................ 25
Table 11: South Africa 2010 FIFA T statistic. ...................................................... 26
Table 12: Brazil 2014 FIFA T statistic. ................................................................ 27
Table 13: Russia 2018 FIFA T statistic. ............................................................... 29

Appendix
Figures
Figure A1: Excess Returns Jan-May South Africa 2010. ........................................ 36
Figure A2: Excess Returns during FIFA South Africa 2010. .................................. 36
Figure A3: Excess Returns Jan-May Brazil 2014. .................................................. 37
Figure A4: Excess Returns during FIFA Brazil 2014. ............................................ 38
Figure A5: Excess Returns Jan-May Russia 2018. ................................................. 39
Figure A6: Excess Returns during FIFA Russia 2018. ........................................... 39

Tables
Table A1: T test South Africa 2010. ................................................................... 37
Table A2: T test Brazil 2014. ............................................................................. 38
Table A3: T test Russia 2018. ............................................................................ 40

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1 Introduction

 The FIFA World Cup, probably the biggest international football event to be ever hosted and
 watched all over the world. Countries from far end corners of the world come together and
 lighten up the sportsmanship vibe as they participate as hosts, teams and audience. First hosted
 in the year 1932 and from then onwards this major sporting event has continued to fascinate
 millions of avid football fans. As a small example of how great the event is about 3.572 billion
 people (more than half of the world population) watched the event while it was being
 telecasted. Such an information casts light on how influential this event is. However, the
 influence of it has not been confined to the stadium and players only. Letting alone the
 sportsman spirit of the event, it has even gone to the extent of affecting the primary capital,
 secondary stock markets and investor predilections.
 No wonder such an event would cost a fortune to host and invest in. The requisite capital for
 such a massive investment comes from the public offerings made by private and government
 sponsoring companies. To what extent would they be able to accumulate enough capital
 depends on the willingness preferences and speculations made by the investors. An example
 of this phenomena is evident if one takes a glance at the volumes of security transaction data
 during those times compared to other years. The onset of this major event also casts light on
 investors’ tendency to speculate on prospective investment projects. This behaviour can be
 exemplified when they are the stakeholders of the sponsoring companies and indigenous ones
 that deal in commodities like sports gear, FIFA merchandise and fast food. The so-called
 prophecies made by and convictions of these stakeholders about their companies’ performance
 goad them into gambling on their beliefs in the hope of attaining above-average returns and
 hefty capital gains during the world-cup hype.
We will focus on the following questions

 • Does the FIFA event help the sponsoring companies' stock returns to improve?
 • Does the FIFA event help the host countries security market return to improve?
 • Which one of the sponsoring companies' stock returns or host countries security market
 return gets improved the most by FIFA world cup which would help us know where to
 invest our money in. In other words, would it be better to invest our money in the equally
 weighted portfolio of sponsoring companies or in the host country security market indices.

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By finding out the answers to these questions with the help of theory, methodology and
 hypothesis testing, we would eventually try to prove if that the FIFA world cup, although a
 major sporting event made for the purpose of entertainment and not a phenomenon that
 matters to the sponsoring companies’ stock prices and the host countries’ securities market
 indices for improvement. Later in the study, we would prove this assertion with the relevant
 hypothesis, equations and findings. The assertion has been proven with the help of tests of
 significance of the standard deviation of average abnormal returns through t-Statistic.

2 Theory

 Here, we will present the earlier researches regarding the hypothesis about whether FIFA world
 cup influences the stock market price variations and investor activities. Based on their
 perspectives we would summarize and articulate their point of view.

2.1 Findings of Goldman Sachs

 Goldman Sachs (2014) is of the opinion that FIFA world cup does affect the stock market,
 even though for a short period of time. They have found a clear pattern which shows the
 winning country outperforms the stock market in the upcoming weeks following the FIFA
 world cup final. They found the magnitude of outperformance to be 3.5 percent. Compared to
 the stock markets of other countries. On the downside, this outperformance lasted only for
 about three months, such hype maybe due to investor sentiment for the time being. The reason
 behind it may be due to the inability of the winner country to hold on to its gain much longer
 as soon as its investors get over the hype of positivity. Maybe, that is why most of the winning
 countries see their stock markets underperform by as much as 4 percent on average, in the
 following year after the world cup final. Goldman Sachs (2014) has analysed the stock market
 data of winner countries right from 1974 and found that all the winner countries other than
 Brazil (Winner of 2002) have attained outperformance in the month right after FIFA world
 cup final. However, the cause for Brazil’s underperformance was a little different since the
 country was already beset with acute recession and currency crisis. Such an undesirable
 situation, kind of overshadowed their victory. To cite some data about the extent of their
 underperformance, their equity market went down by 19 percent compared to the world index
 and by 13 percent over their own performance compared to the previous months. But this
 setback could not hold Brazil back from displaying the post-world cup feel good factor and

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support the fact that FIFA does in fact influence the stock market. The country outperformed
the MSCI world index in just one month after its win 1994, a time when bull market thrived.
Brazil itself accounted for 21 percent outperformance in overall 38 percent outperformance by
all the stock markets in the world. In the absence of economic crisis, the winner tends to make
the most out of the hype of their success, even though for a brief period.
Focusing on the case of runner ups, their fans would be disappointed at losing in the final
match. Similar is the case of their stock market that probably does not react well either. This
again supports the fact that stock markets can be influenced by the FIFA outcomes. Compared
to the winners, the runner ups experience post-final bout of the blues. This fact was verified
by Goldman Sachs data which says that the runner-up stock market’s relative performance rises
by two percent on average in the first month after the finals. It is an improvement but however
compared to that of the winner’s market, the market reaction is not that significant. However,
to contradict such findings, it would be appropriate to say this average runner-up performance
is heavily inclined to Argentina, that enjoyed a 33 percent outperformance in that month.

Speaking from the perspective of security markets of host nations, the pride and confidence
associated with them has led to a positive impact on those markets even though such impacts
last for a couple of weeks. For example, the FIFA world cup 2018 was hosted by Russia. Within
one month of hosting the event, the returns of Russian security market stocks went up by 2.7
percent on average but faded quickly after the world cup was over. This backs another corollary
information that while FIFA influences stock market performance, such performance is not
consistent as the above-average performance gradually dies out.
A glance at table 1 that contains recent stock market performance of the countries believed to
be win the world cup in each of the years right from 1974 to 2010 would reveal the changes in
stock market returns before and after the event, for example, pre-FIFA-3 months and post
FIFA-3 months return. Looking at the Table 1, one would find that Brazil had reaped the
benefits of one of the best stock market performances in the 3 months before and after the
event in 1994 where the returns shot up from 14.1 percent to 37.9 percent. The biggest
improvement made can be seen in the case of Spain in in 1982 in terms of pre-1 month and
post 1-month return where the returns improved from –14.20 percent to 9 percent (Over 23
percent rise) while German stocks have underperformed relative to the world index.

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Year Winner pre-1yr return post-1yr return Runner-Up pre-1yr return post-1yr return Host pre-1yr return post-1yr return
 1974 Germany 2.5 21.8 Netherlands -9.6 21.8 Germany 2.5 21.8
 1978 Argentina - - Netherlands 2.6 2.3 Argentina - -

 Table 1: A tabulation of post-1 year and pre-1 year returns for the winners, The runner ups
 1982 Italy -10 -14.6 Germany 10.2 -2.3 Spain -13.7 -43.3
 1986 Argentina - - Germany 25.7 -19.4 Mexico - -
 1990 Germany 45 -18.5 Argentina 13.1 69.2 Italy 12.1 -25.6
 1994 Brazil 38.7 -3.7 Italy 12.7 -16.4 USA -9.3 13.7
 1998 France 27.7 -11.2 Brazil -37.6 -39.1 France 27.7 -11.2
 2002 Brazil -13 12.4 Germany 2.2 -14.1 Japan 0.3 -13
 2006 Italy 1.1 -3.3 France 6.7 3.9 Germany 9.8 18.4
 2010 Spain -19.7 -14.7 Netherlands 3.4 -9.6 South Africa 7.7 4.1
Average 9 -4 3 -0.4 4.6 -4.4
 Year Winner pre-3m return post-3m return Runner-Up pre-3m return post-3m return Host pre-3m return post-3m return
 1974 Germany 3.9 17.1 Netherlands 0.2 2.3 Germany 3.9 17.1
 1978 Argentina - - Netherlands -5.1 -0.3 Argentina - -
 1982 Italy -16.1 -11.1 Germany -1.8 -9.9 Spain -13.8 -17.6
 1986 Argentina - - Germany -7.3 3.9 Mexico - -
 1990 Germany -3.6 -7.9 Argentina -2.9 6.1 Italy -1.6 -7.2

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 1994 Brazil 14.1 37.9 Italy -7.2 -8.2 USA -1.2 1.1

 and host countries for the year 1974 to 2010.
 1998 France 8.4 -0.8 Brazil -18.5 -26.9 France 8.4 -0.8
 2002 Brazil -19.4 -25.5 Germany 1.7 -22.6 Japan 20.4 6.7
 2006 Italy 2.3 0.5 France 3.4 0 Germany -0.6 0.8
 2010 Spain -8 4.5 Netherlands -1.2 -0.4 South Africa 1.6 8.3
Average -2.3 1.8 -3.9 -5.6 2.1 1.1
 Year Winner pre-1m return post-1m return Runner-Up pre-1m return post-1m return Host pre-1m return post-1m return
 1974 Germany 3.4 5 Netherlands -0.9 9.1 Germany 3.4 5
 1978 Argentina - - Netherlands 2.1 -2.6 Argentina - -
 1982 Italy -7.2 9.5 Germany -0.6 2.8 Spain -14.2 9
 1986 Argentina - - Germany 0 -2.2 Mexico - -
 1990 Germany 7.8 4.2 Argentina 12.4 33.1 Italy -2.3 1.7
 1994 Brazil 9.6 21.1 Italy 1.7 -8.5 USA -2.6 1.2
 1998 France -1.3 0.7 Brazil 0.7 -6.7 France -1.3 0.7
 2002 Brazil -13 -18.9 Germany 4 -4.1 Japan 2.1 2
 2006 Italy -0.7 0.5 France 2.3 -0.2 Germany 1.9 -0.5
 2010 Spain 9.1 5.7 Netherlands 3.4 -0.5 South Africa 2.4 2.3
Average 0.9 3.5 2.5 2 -1.3 2.7

2.2 An Insight to Investor Behaviour and Their Consequent Investment Decisions That
 Affect the Stock Market

 From the perspective of investor behaviour and favourite national sports teams wins and losses,
 past studies show that FIFA world cup results significantly impact the investor mood. Investors
 feel positive when their country wins and depressed when their country loses. Hirt et al. (1992)
 Edmans et al. (2007) showed that a strong correlation exists between the results of FIFA games
 and excess stock returns. They have identified an asymmetric effect that leads to losses to have
 a far-reaching depressing effect on the losing countries’ local stock markets. They wanted to
 test this hypothesis i.e. if the losses depress the stock market returns. After carrying out the
 survey to back their hypothesis they found that it is actually the capital gains and overall range
 of returns that suffer the most due to the losses which ultimately affects the volume of securities
 traded and act as indicators of the investors’ sentiment. They labelled capital gains and returns
 to be investment utility components that are ultimately dependent on investor confidence on
 their national stock markets. So, the reference point here would be the investors’ pre-match
 expectations of how their national team would perform. Here it would be appropriate to say
 that investors not only invest their own money in security markets but also psychologically
 invest themselves in their desired outcomes and end up making biased positive predictions.
 Ultimately, when things don’t go in their favour, they tend to lose all hope and start to divest
 from most of their investments which lead to influential stock price depressions.

 An example of this case would be Nike’s stock market situation during the 17th FIFA world
 cup. Nike was the sport sponsor company of Brazil that won its first match, and Nike’s excess
 stock return on the opening price on the first trading day shot up by 1.3 percent but went down
 by 5 percent the country lost its second match. This shows that sports sentiment of investors
 is very quick to materialize. In the event of getting depressed about the outcome, the investors
 get extra cautious while regulating their investment in fear of losing money in the stock market.

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2.3 Reason behind the impact of FIFA On Global Stock Indices and Comparison of
 Such Impact with That of Other Sports

 Previous research shows that losses in the World Cup have decreased the stock market returns
 and volume of transactions drastically while wins did the opposite. So here it is appropriate to
 analyse the reasons for stock market changes. In order to look at such reasons, we might have
 to extend our view to include other athletic sports as well and find out whether they act as
 possible indicators for stock market changes. The efficient market hypothesis states that stocks
 always incorporate new information and its participants act in a rational manner. So, this implies
 that it is impossible for the stocks to be overvalued or undervalued. But over the years, certain
 findings have shown that certain major events and feelings are well capable influencing financial
 decisions at micro as well as macro levels. This has led to a new application of behavioural
 economics in the area sports and athletic events. A study by Edmans, Garcia and Norli (2007)
 looked into the effect of investor sentiment of security prices due to outcome of sporting
 events. Among the types of sporting events analysed international soccer matches had a strong
 correlation with security prices which would decrease after a loss in the game. They found that
 the primary reason behind the stock price influence was the effect of something called ‘Mood
 Variable’. The statistical research spanned across 39 countries and included next-day stock
 market results of wins, losses and ties after which the expectations were compared with those
 results (Expectations are the outcomes anticipated by the fans and investors about the sporting
 event). They concluded that a result that surprises impacts their investment decisions leading
 to purchasing and selling stocks that would make stock prices fluctuate. At the national level
 Ashton, Gerrard and Hudson (2003) examined the relationship between England’s national
 soccer team matches and the FTSE 100, a share index of the 100 largest companies, by market
 capitalization, listed on the London Stock Exchange.

 To consider each of situations their analysis included ‘Friendly’ matches when the team was
 not participating, ‘qualifying’ matches when the team was attempting to qualify for a
 tournament, and finals matches when the team was participating in a tournament. They studied
 the outcome of the ‘Finals’ matches and found a stronger correlation with stock market
 fluctuations than either of the ‘Friendly’ or ‘Qualifying’ matches. This shows that not all ‘Wins’
 and ‘Losses’ are equal in effect. A defeat in an important match seemed to have a greater
 psychological effect than a relatively unimportant match. They studied England to find out
 about this. To do away with this biasness, Kaplanski and Levy (2008) widened the research
 ambit by looking at FIFA world cup matches from 1950 to 2010. The developed research

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focused on America’s S&P500 index. This captured loss suffered by multiple countries because
of the high amount capital invested by foreign countries in US. The effect of 32 countries and
64 matches appears to be statistically significant and large. This helped the researchers to
concentrate on investors’ irrationalities while they predicted their desired outcomes. This is
basically called ‘Expectation Theory’ that drives the entire stock market show. As a possible
underlying reason behind the stock market dropping, it is important to examine expectation
theory. Mitra, Schaubroeck, Shaw and Duffy (2008) researched the effect of failing to meet and
exceeding pay raise expectations on an employee’s happiness. This research was restricted to a
university hospital but may be representative of a person’s general psychology. The researchers
found that failing to meet expectations had an effect larger in magnitude than either meeting
expectations or exceeding expectations on worker happiness. The change in turnover
intentions was larger in magnitude for failing to meet expectations than meeting or exceeding
expectations. They also discovered that higher expectations correlated with a larger increase in
turnover intentions. These findings are important in our context because it may help explain
why losses impact the stock market more than wins or draws. Another important factor to
consider is the idea that people are generally overly optimistic. Schreier, Carver and Bridges
(1994) found that people are generally over optimistic and that it is a pervasive human trait.
While they note that not everyone is generally optimistic.

Optimism remains prevalent in a significant percentage of people. Armor and Taylor (2002)
found that people are more likely to maintain optimism despite evidence to the contrary. This
is important because teams that are not favoured to win still may have fans that expect them
to win the match. Thus, losing the match is more likely to fail to meet expectations, while
winning a game is more likely to only meet expectations. Fans are not likely to adjust
expectations because of biases towards their team and tendency to ignore evidence against the
bias. These findings are important in the context of this paper because it may help explain why
losses impact the stock market. When such overly optimistic expectations are proven wrong
by the results, people might start to sell stocks and divest investments, which might well be
perceived by the investors to be negative for the economy, while being proven right has the
opposite impact and lead to investing in additional stocks.

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2.4 Detailed consideration of the stock market reaction at various levels and their
 variations.
 One added feature of this thesis namely, the thesis published by Wijden, J. V. (2019) that
 presented studies concerning football matches and stock returns is that, along with studying
 the effects of match results of national football teams on stock indices during the FIFA World
 Cup. It also considers the effects of match results of listed football clubs on their stock price,
 the effects of match results on the stock price of intimately involved companies. In the end the
 article presents the differences in receptivity to sports sentiments and the consequent
 investment decisions in the Latin American and European stock market. Dohmen, Falk,
 Huffman and Sunde (2006) asked a representative sample of the German population about
 their personal economic situation, the current economic situation in their country and their
 expectation regarding changes in both the situations a year later. They found out that after an
 unexpectedly good performance of the German football team, the respondent developed a
 more positive outlook relating to their economic perceptions and expectations. The results
 were found to be convincing enough for the entire German population and the economy.

 The article seemed to be very interested in whether such optimistic traits has an impact on the
 trading behaviour of investors in domestic stock markets. The article segregated the influence
 of match results into three different levels. The first level is the impact of the FIFA match
 results on the domestic stock index which mainly include national teams, at the second level
 the influence of FIFA match results on stock prices of football clubs that are listed on the stock
 exchange (Juventus of Italy, Arsenal of England etc,) and lastly, at the third level, the influence
 of FIFA match results on the stock price of the sponsoring companies associated with those
 football clubs.

 Ashton Gerrard and Hudson (2003) were the first to study this effect. They studied the effect
 of the performance of England’s national football team from January 6, 1984, to July 3, 2002,
 on the British FTSE 100 index by conducting binomial tests and found a statistically significant
 relationship. This study was further augmented by Bernhard Zwergel and Christian Klein
 (2009). They redid the binomial tests to find whether the return of the trading day following a
 FIFA match of England’s national football team differed from the unconditional mean returns
 of normal trading days. The two studies came up with different findings despite using the same
 data. The two different conclusions may be due to the difference in perspectives of the two
 studies.

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To enumerate on it, first, Ashton did not consider the holiday effect. By holiday effect the
article means a day when no trading takes place. Zwergel and Klein (2009) corrected this
loophole by omitting all returns that fell on holidays.

Second, the studies differ between how they deal with draws in knock out matches. This
difference is due to the existence of penalty matches after a draw in a knockout match. The
result of a loss after penalties would be same as the result caused by a loss within the 90 minutes
of a match as the team gets out of the tournament.

Third, the study by Ashton did not consider time during which a match is played that would
inevitably have an impact on the magnitude of the return. Since most matches are played during
the evening, the extent of abnormal returns becomes visible on the first trading day after the
match. Although it is something very obvious, but the DataStream makes an error while
showing the returns and stock prices if the match is played in another time zone. To clarify it
further, during the World Cup 2002 that was played in South Korea and Japan. England played
against Argentina on 7th of June. It was Friday and the match started at 8:30 pm (Local time)
and at 12:30 pm in England. The match ended at around 22:30 pm (Local time) which was
14:30 pm in England. What Ashton did was that he took the closing price on the first trading
day after the match to calculate the abnormal returns i.e. 10th June, Monday but the investors
have already reacted on Friday 7th of June since the FTSE index was still open on that
afternoon. Zwergel and Klein (2009) took this timing factor into account and recorded the
closing on the match day to calculate abnormal return.
The conclusions were therefore very different in themselves. While Ashton found a statistically
significant relationship between stock market return on FTSE 100 and the performance of
England’s national team. Zwergel and Klein (2009) could not find any such relationship
between them. This shows that there are many ways arising from different perspectives to study
the topic that can lead to different conclusions. What is important is how vast is the area of
study and how practical has the researcher been while conducting the research.

Being aware of the findings put forward by Zwergel and Klein. Ashton et al. (2011) still assert
the significance of the relationship between national football matches and FTSE 100. The
primary reason for their assertion was that the link between international football results and
stock market returns is subject to various statistical approaches (Parametric approaches in
particular) that have been ignored by Zwergel and Klein.

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Edmans, Garcia and Norli (2007) surveyed the international football matches on the World
Cup from 1973 to 2004. Their survey also included relevant qualification matches in their study
to get a total sample of 1162 football matches played by 39 countries. Edmans, Garcia and
Norli (2007) analysed the effect of international football matches on stock prices by looking at
the return variation on a broad stock market index on the first trading day after the match. This
method is same as that of Ashton et al. (2011) and Edmans et al (2007) knew the after effect
that a part of the reaction in stock prices may have already taken place in stock prices before
the measurement day. Edmans did this to get the return for an entire day when the match
outcome is known. They found a robust negative stock market reaction to losses by national
football teams. The size of the loss effect was found to be economically significant in terms of
monthly returns, but no evidence was found of corresponding reaction after wins in football
matches. The researchers relate this effect to change in investor mood after the matches. This
effect is more evident in countries where football is a popular sport. The effect gets even more
augmented along with the importance of the match being played. Such effect has a large impact
on small stocks that are held by local investors whose mood is more affected by the
performance of the national football team.

Graziano, Vicentini (2016) and Demirhan (2013) studied the effect of one single national
football team on the domestic stock index. Graziano and Vicentini analysed the effect of Italian
national football team results on the FIFA world cup from 2002 to 2014 on the index names
FTSE MIB. Demirhan investigated into how the sporting success of Turkish national football
team between January 1988 to May 2011 affected the Borsa Istanbul stock index returns.
Graziano and Vicentini figured out a positive and statistically significant relationship at one
percent confidence level with football match results of Italian national football team in FIFA
world cup. Demirhan found no abnormal return on the Turkish stock market index after a win
of the Turkish national football team but an appreciable negative effect in the event of a loss.

Talking about the above-mentioned survey from a different perspective Gerlach (2011) found
the pattern of returns documented in the papers by Ashton et al (2011) and Edmans et al (2007)
also existed in countries whose national teams did not take part in tournament during the period
of survey. This, however, casts doubt about whether the abnormal returns are because of the
match results or for some another reason. To clarify the same, in the quarter final between
Brazil and England on June 21, 2002, Brazil won the match by 2-1. On the following trading

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day i.e., June 24th Monday, the Brazilian index rose by 1.27 percent while England’s fell by 1.33
percent and the World Market Index fell by 0.31 percent. With the help of the Global Index as
the benchmark, this would provide support to the hypothesis that world cup matches affect
returns through investor sentiment because Brazil had a higher return than the market index
and England had a lower return. But, on June 24, 2002, the return on Argentine index (When
Argentina played against Brazil) was 2.04 percent while the return on French index (When
France played against England) was 3.45 percent. Both Argentina and France did not advance
to the elimination round in world cup 2002, so their national team performances did not affect
the returns on that day.

As concluded by Ashton, it is extremely tough to be totally certain that the event study is correct
in every detail and it is rather sensible to contemplate on how academic studies can be
accurately replicated. The different methods used and the difficulty of studies account for
different conclusions. While some studies find a statistically significant relationship in the stock
market after the wins and losses of the national football team the other studies found no such
statistically significant relationship at all.

About some of the football clubs, that are listed on stock exchange Tottenham Hotspurs of
England was the first football club that got listed on stock exchange in 1983 after which, the
other football clubs followed. This time, the study was made a little more specialized by
analysing the effect of match results on the value of the football clubs. To cite an example, in
June 2018 Juventus was defeated by Ajax for 2 goals to 1 and Ajax got qualified for the semi-
finals for the first time. This led Ajax’s share price to increase from 17.15 euros to 18.75 euros
(about a 9.33 percent increase) on the day following the match while this outcome led
Juventus’s share price to decrease by 24 percent on Milano Stock Index. From the example it
can be concluded that investors are very like-minded about the effects of match results on the
share value of football clubs. Dobson and Goddard (2001) showed that good match results
may amount to financial rewards because success attracts media attention and avenues for
sponsoring. Other financial results involve premiums associated exclusively with European
competitions for example Europa league. Champions League etc. However, Zuber, Yiu, Lamb,
and Gandar (2005) found that investors do not trade on information which can lead to change
in cash flows, but they rather want to obtain value from their ownership stake in the clubs.

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The next category of stocks that can be affected by football match outcomes are those of
involved companies. Hanke and Kirchler (2013) studies the effects on the stocks of jersey
suppliers like Adidas, Nike and Puma after a match of a national football teams that wear jerseys
of those brands. They used data from World Cup and European championships between 1996
and 2008. They found abnormal returns at major football tournaments. Some of their findings
were that matches where both the teams wore the jersey of the same supplier led to positive
excess returns and effects on the share price were greater in case of knock out matches than
for group matches. The loss effect in total and in knock out matches was found to be more
significant when pre-match defeat probability was accounted for.

Ramezani and Mardani (2012) studied the impact and took the data of Iranian football teams
that have sponsoring companies that were listed on the Tehran Stock Exchange between 2009
and 2012. Their results showed that there is 86 percent probability of a significant correlation
of between the results of matches and the stock price of sponsoring companies but such effects
of match results on their stock prices were not the same when it comes to intensity. Here, it
would be good to find out the answer to the question if sponsoring football companies would
affect company performance. Naidenova, Parshakov and Chmykhov (2016) led concluded that
there is no such nexus i.e. no difference has been found in performance between sponsoring
and non-sponsoring companies but the effect of sponsorship can differ among football leagues.
Moreover, the success probability of a national football team does not influence the
effectiveness of sponsorship contract.

Speaking about the popularity of FIFA and comparing its influence with that of other sports.
Boyle and Walter (2001) studied the effects of match outcomes of New Zealand’s national
rugby team on the New Zealand stock market. They came up with no evidence of any link
between sporting team success and stock market return behaviour at any point of the surveyed
time period. Edmans, Garcia and Norli (2007) who investigated the effect of cricket, Rugby,
ice hockey and basketball matchs, while they found a strong negative stock market reaction to
losses by national football teams. The effect of defeat in cricket, rugby and basketball were
found to be insignificant. No evidence could be found as a corresponding reaction to wins in
any of these sports. What can be fathomed from the above findings is that football is the main
sport almost every country in the sample taken, while other sports were in secondary position.

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Lastly, to talk about the differences in receptivity to sports sentiments and the consequent
investment decisions in the Latin American and European stock market, it was found that Latin
Americans were more emotional that their European counterparts and therefore are susceptible
to more mood changes. There are two causes for which the stock market reacts to the sporting
performance of the national football teams. There might be a ‘Feel-good’ factor with national
football success fomenting greater faith in the future. Given the increasing commercial
significance of international tournament finals, an effective stock market would revise
speculation about possible economic benefits to be derived from national team performance
in case of individual match results and the chances of the team progressing further in the
tournament. It supports the fact that stock market reaction to qualifying and finals matches is
greater than friendly matches. For friendly matches, a rather diluted feel good factor is likely to
work and limited information is available on the prospects of the team in competitive
tournament matches. A rather striking fact, the degree of team identification or fanaticism also
influences the effect of football matches on stock market returns. A study by Salman (2005)
shows that Turkish football teams such as Besiktas, Galatasaray and Fenerbache has the most
fanatic of the supporters as reported by the Turkish police force. In 2009, Berument, Ceylan
and Ogut-Eker (2009) only found a positive and a statistically significant relationship in the
study that analysed the stock value reaction for Besiktas, while it was not so influential when it
came to those of Galatasaray and Fenerbache. This supported the statement that a higher
degree of fanaticism enhances reactions in the stock market. Compared to any other sports, a
greater amount of fanaticism is existent in the case of football that leads to more extreme
investor mood swings.

Maranhao (2007) elaborates the distinction between the two styles of playing preferred by the
two population. He said that the Europeans prefer the ‘Apollonian Style’ which signifies a
rational outlook while the Latin Americans prefer the ‘Dionysian Style’ that represents a more
emotional approach. Europeans would have a rational way of playing the game due to their
‘Organization’, while Brazilians would have a unique way of playing of their own representing
their Afro-Brazilian culture. Thus, the qualities associated with ‘Order’ and ‘Rationality’ in
Brazilian football show the structure of the general society. The Brazilians attach a nationalist
feeling that should first be created and then transmitted to the world to perceive, maybe that is
why evaluations are ostensible during big football events, be it the acts of heroism or failure in
the expected performance. John Clifton (2015) (2012) studied the emotional level of people in
more than 150 countries and areas after asking residents about their experience during the

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matches and he found that the emotional level of Latin American to be much higher than that
of their European counterparts. The percentage of people who said ‘Yes’ after accepting their
positive and negative emotions for FIFA matches was found to be ‘47.24 percent’ for the
Europeans and ‘55.26 percent’ for Latin American countries in 2012, Football seems to have a
powerful ability to provoke national unity through appealing people by going beyond
traditional national boundaries. A thing to consider is that what started as a simple played a
seriously important role in developing mankind, especially the Latin American countries. This
issue can be traced back in 1938, when the unique sportive performance of the Brazilian
national football team led to a kind of national identification. Here, it would be appropriate to
say that perhaps Latin American people live and dreams football. It is their reason for hope
and as well as suicide. Just to cite the level of involvement of the Latin American population in
football, as per the study in the thesis by Wijden, J. V. (2019), about 100 thousand Brazilians
suffered a heart attack when their countries lost to Uruguay in World Cup 1950 by a margin of
2-1. This match held the attendance record of 200 thousand, that was traumatic indeed for
Brazilians. In the case of Europe too, the number of hospital admissions for a range of
diagnoses shot up during England’s 1998 world cup matches, especially in matches with
Argentina. The primary cases of diagnoses were of myocardial infarction compared any other
types of health issues such as stroke, deliberate self-harm and road traffic injuries. The match
against Argentina showed 55 extra admissions for myocardial infarctions, that led to the
hypothesis that myocardial infarction can be triggered by emotions. Probably the most
shocking news was the death of a Columbian footballer named Andres Escobar, who scored
an own goal in World Cup, 1990 in a group match against United States that led to the country’s
elimination. He was shot as a punishment and died just 10 days after the match.

The above-mentioned studies show the difference in the way of experiencing football between
Europe and Latin America. Based on the above findings, it can certainly be said that Latin
Americans react more to football match results of their national team that may get visible on
the stock indices.

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2.5 Based on the previous literature review we have framed the following two
 hypotheses:

 H1: The FIFA world cup affects the returns of the host country stock indices significantly.

 H2: The FIFA world cup affects the returns of the sponsoring companies significantly.

 H3: The FIFA world cup event affects the returns of host country stock indices greater than
 the returns of the portfolio of sponsoring companies.

3 Data

 We have downloaded all the data on a daily basis (indices, stock’s prices, currency conversion
 and risk-free rate from investing.com. We have downloaded the stock price data of the
 sponsoring companies, the global index and the host countries’ stock indices from 2010 to
 2018. We chose S&P500 as global index. By ‘Sponsoring companies’, we mean those
 companies that invest in the host countries’ sports infrastructures during FIFA world cup. As
 far as currency conversion is concerned, we have converted the stock prices into the currencies
 of the host countries. As a risk-free rate, the 10 Year US Treasury Bill-rate is taken.

3.1 Countries research and their major indices and currencies

 The table 2 shows when the respective FIFA events were held (Years), which country hosted
 it (Country), what are the host countries’ stock market indices (Major index) and what are the
 host countries’ official currencies (Currency). In 2010, South Africa hosted the FIFA world
 cup. They have JTOPI as their major index and their currency Rand (ZAR). In 2014, we have
 Brazil as hosting country for the FIFA world cup. They have Bovespa (BVSP) as their major
 index and their currency Real (BRL) and the previous cycle, Russia hosted the FIFA world cup.
 They have two major indices MOEX Russia (IMOEX) and their currency Rubel (RUB).

 Year Country Major index Currency
 2010 South Africa South Africa Top 40 ZAR
 (JTOPI)
 2014 Brazil Bovespa (BVSP) BRL
 2018 Russia MOEX Russia (IMOEX) RUB
Table 2: Countries research and their major indices and currencies.

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3.2 Sponsors
 Table 3 shows which companies sponsored in FIFA (Company), in which names are
 sponsoring companies’ stocks traded in the stock exchange (Stock symbol) and the currencies
 the stocks are traded in (Currency). The ‘x’ marks under the respective years indicate which
 company sponsored in which of the years.
 Company Stock Symbol Currency 2018 2014 2010
 Anheuser-Busch (Budweiser) BUD USD x x x
 Castrol Cast nse INR x x
 Continental CONG xetra EUR x x
 Hisense 600060 CNY x
 Johnson & Johnson JNJ USD x
 Mengniu Dairy 2319 HKD x
 McDonald's MCD USD x x x
 MTN MTN ZAR x
 Oi OIBR4 BRL x
 Satyam TEML INR x
 Seara JBSS3 BRL x
 Yingli Solar YGEHY USD x
Table 3: Sponsors indices and currencies.

3.3 Benchmark
 For the event study, it is imperative to select a proper benchmark, so we have used the index
 to which the shares belong as a benchmark. Since the shares belong to some indices, the effects
 of FIFA on those indices are to be analyzed if those shares are to be studied. There are various
 ways to select a benchmark. The initial option might be to use a widely used global stock index
 such as S&P Global Inc. can be selected. The benefit of selecting a global benchmark is that it
 can be used for all countries. Another option is to select a country specific index as a
 benchmark. In this case the advantage would be that the abnormal returns will not be reduced
 as the host country might not be represented in that benchmark. Yet another option would be
 to include all other countries in the sample years and take the average of their indices as a
 benchmark. In this case, an own global index consisting of the countries that will be studied is
 created. Among the various options, we have decided to use the global index of S&P as a
 benchmark because of the benefit of comparing all the host country stock market indices with
 this one. As a result, we would be able to study the host country stock market returns based
 on the global index of S&P’s return. Thus, after a specific match outcome, the relevant host
 country stock market abnormal returns can be compared to that of the global index. For
 example, if the South African national football team loses a match, we would be able to

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monitor, study and compare the change in the returns shown by the South African stock market
 index JTOPI with that of S&P. Besides, we can also compare the respective index return of
 the sponsoring companies’ shares that are represented in S&P.

3.4 Data description
 As for the data description, we have set up two tables for each of the host countries and their
 sponsors during FIFA event. The columns in the first table include the average returns, the
 standard deviation of the returns, the maximum and minimum recorded returns and the
 number of observations for the host countries, the global Index of Standard & Poors and the
 sponsors which are mentioned in the row.

 The second table shows the correlation matrix and the correlation co-efficient between the
 returns declared by the host countries securities indices, the index of Standard & Poors’ and
 sponsoring companies during FIFA.

3.4.1 South Africa 2010 FIFA

 We notice that the magnitude of the average returns is small (positive and negative) for all of
 the indices and the portfolio of sponsoring companies' stocks (based on the return
 observation of 20 trading days), while the standard deviations being 0.0126 for the host
 country, 0.011 for S&P and 0.00942 for the sponsors. The maximum return recorded for the
 host country index was 0.024, 0.018 for S&P and 0.016 for the sponsors and the minimum
 return recorded for the host country was -0.025, -0.03 for S& P and -0.016 for sponsors.

 Description Host S&P Sponsors
 Average -0.00056 0.000985 -0.00235
 Standard deviation 0.012635 0.011454 0.00942
 Max 0.024505 0.0189 0.016182
 Min -0.02494 -0.0304 -0.01604
 Count 20 20 20
Table 4: Details of returns South Africa 2010 during FIFA.

 The correlation co-efficient is found to be positive for the average returns of sponsors and the
 host country security market returns (0.6) while it is found to be negative between average
 returns of sponsors and the global index of S&P Returns (-0.52). As for the correlation co-

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efficient of host country stock market return and the Global index of S&P Returns, it is
 negative with the index of the host returns (-0.53)
 Host S&P Sponsors
 Host 1
 S&P -0.531268114 1
 Sponsors 0.641359448 -0.528454459 1
Table 5: Correlation Matrix.

3.4.2 Brazil 2014 FIFA

 We notice that the magnitude of the average returns is small (positive and negative) for all of
 the indices and the portfolio of sponsoring companies’ stocks (based on the return observation
 of 20 trading days), while the standard deviations being 0.009423 for the host country, 0.0039
 for S&P and 0.0109 for the sponsors. The maximum return recorded for the host country
 index was 0.016, 0.006 for S&P and 0.018 for the sponsors and the minimum return recorded
 for the host country was -0.01755, -0.0081 for S&P and -0.01943 for sponsors.

 Description Host S&P Sponsors
 Average -0.00081 -3.5E-05 0.002842
 Standard deviation 0.009423 0.003963 0.010953
 Max 0.016004 0.0068 0.018954
 Min -0.01755 -0.0081 -0.01943
 Count 20 20 20
Table 6: Details of returns Brazil 2014 during FIFA.

 The correlation co-efficient is found to be negative for the average returns of sponsors and the
 host country security market returns (-0.017) while it is found to be negative between average
 returns of sponsors and the global index of S&P Returns (-0.06). As for the correlation co-
 efficient of the host country security market returns with Global index of S&P returns, it is
 negative with the index of the host returns (-0.10).

 Host S&P Sponsors
 Host 1
 S&P -0.100385299 1
 Sponsors -0.017670451 -0.065315533 1
Table 7: Correlation Matrix.

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3.4.3 Russia 2018 FIFA

 We notice that the magnitude of the average returns is small (positive and negative) for all of
 the indices and the portfolio of sponsoring companies’ stocks (based on the return observation
 of 20 trading days), while the standard deviations being 0.009294 for the host country, 0.006068
 for S&P and 0.011298 for the sponsors. The maximum return recorded for the host country
 index was 0.012, 0.008 for S&P and 0.021 for the sponsors and the minimum return recorded
 for the host country was -0.019, -0.013 for S&P and -0.02017 for sponsors.
 Description Host S&P Sponsors
 Average -0.00156 -0.00038 0.002793
 Standard deviation 0.009294 0.006068 0.011298
 Max 0.012422 0.0084 0.021361
 Min -0.0199 -0.0137 -0.02017
 Count 22 22 22
Table 8: Details of returns Russia 2018 during FIFA.

 The correlation co-efficient is found to be positive for the average returns of sponsors and the
 host country security market returns (0.48) while it is found to be negative between average
 returns of sponsors and the global index of S&P Returns (0.12). As for the correlation co-
 efficient of host country stock market return with the Global index of S&P Returns, it is
 negative with the index of the host returns (-0.17)
 Host S&P Sponsors
 Host 1
 S&P -0.1778654 1
 Sponsors 0.487308078 0.128460594 1
Table 9: Correlation Matrix.

4 Method:

 Here, we would analyze the security return behavior of the sponsoring companies and security
 returns of host countries during the FIFA world cup right from 2010 to 2018. Our motive is
 to look for abnormal returns in the stocks of sponsoring companies and that of the host
 countries around the FIFA world cup event. An important consideration to be taken into
 account in this aspect is the event study, which normally means the study of the time period
 when the analysis of securities’ return behavior concerning a particular information
 announcement or events, would be conducted. In this thesis, the method that will be used to
 analyze the existence and patterns of abnormal returns of host country security indices and the
 equally weighted portfolio of sponsoring companies during the FIFA world cup. For such a

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methodology, there are two assumptions that are to be made, first, the investors are rational
 and the host countries’ stock markets are efficient i.e. the influence of the event is immediately
 incorporated in the stock prices of both the sponsoring companies and the host countries’
 stock market. Some of the steps to do this has been enumerated by De Jong & De Goeij (2011)
 who developed a three-step model are:

 • Identify the event of interest and the timing of the event
 • Construct a benchmark model, to measure normal stock behavior.
 • Calculate and analyze abnormal returns around the event date

4.1 Conducting the Event Study

 Tabulation of closing prices (CPt) of sponsoring companies’ stocks and host countries’ and
 closing price indices and calculation of normal returns (Rt). Here, we have presented the closing
 prices of sponsoring companies’ stocks and that of the host countries’ stock markets to conduct
 an estimation and event window study. What we would like to do is to calculate the returns in
 the following manner:

 i – i−1
 R = i−1
 .
 The reason for not including the opening price is because, the opening prices are susceptible
 to certain factors such as match outcomes, positive earnings announcements that occur
 between the time span between the closing bell on one day and opening bell the next day of
 the stock market.

 After this, we would find the daily average returns during the estimation and the event window
 for the equally weighted portfolio of the sponsoring companies’ indices.

 1
 RPi = ∑ 
 =1 .
 
 Our next step would be to calculate the expectational regression model for both the portfolio
 of sponsoring companies and host countries securities markets. For this purpose, we have
 decided to use the Market Adjusted Model and not Capital Asset Pricing Model because the
 latter imposes an additional restriction that the intercept equals the risk-free rate. Because of
 this restriction, the variance of the error term is mostly larger in the CAPM than in the Market
 Model. This may result in a less powerful test. Furthermore, 79.1 percent of event studies used
 the Market Model against only 0.7 percent of the studies using the CAPM Holler (2014). In

 20

this step, we would define the actual return with the help of the following market regression
model

 = α + β + .

Beta has been used in the capital asset pricing model as a measure of systematic risk of a
particular security or a portfolio with respect to the entire security market. It measures how the
return of a particular security or portfolio responds to market return variations. It is calculated
by dividing the product of the co-variance of the security or portfolio return and market return
by the variance of market return for the specified period. The ‘Beta’ notation helps investors
to understand the degree of systematic risk associated with the security or portfolio return
movement as it changes according to the direction of the market, while a lower value implies
the opposite and makes the security or portfolio good to hold or invest in. The higher the value
of ‘Beta’, the riskier it will be for the investor to hold the security or the portfolio because of
unpredictable market return percentage and price movements. The benchmark used to gauge
the risk involved in this situation is the market return index.

Since we have applied the market model, beta would be required to find out the abnormal
returns. We have used the following formula to find out the abnormal returns from which we
would calculate the average, standard deviation, t-statistic and so on. The excess returns (Rm)
have been used to calculate the beta. S&P stocks has been taken as a global market. For the
FIFA events, a new beta is computed for each of the host country and the sponsoring
companies by taking the co-variance of the host country index excess return and the excess
benchmark return of the global index and then dividing it by the variance of the market excess
return var (Rm) of the estimation window.

 ( ; i )
 β̂ = .
 ( i )

Alpha is a term used in investment strategies to define its ability to ‘Beat the market’. In other
words, it shows the return that the investor will be able to get over and above the market return
by investing in securities if he or she acts as per his or her investment strategy. So, alpha is
often called the ‘abnormal rate of return’. It is a measure of an investor’s performance in being
able to get a return over and above that of the market’s through his or her investment strategy.
The excess return of an investment relative to the return of a benchmark index is the
investment’s alpha. Alpha may be positive or negative and is the result of active investing. It

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