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110 Seiten, Note: 2,0
List of Figures
List of Tables
1 Introdu tion
2 Literature Review
2.2.2 Basi Materials
2.2.4 Consumer Cy li als .
2.2.5 Consumer Non-Cy li als
2.2.6 Finan ial Se tor
2.2.7 Health are
2.2.8 Te hnology
2.2.9 Tele ommuni ation Servi es
3 Data and Methodology
3.1 Sto k Market Rea tions and Related Losses
3.1.1 Stru tural Break
3.1.2 Di eren e-in-Di eren es
3.2.1 Event Study
3.2.2 Hypothesis Testing - Statisti al Analysis
4 Empiri al Results
4.1 Sto k Market Rea tions and Related Losses . .
4.1.1 Stru tural Break of Sto k and Forex Markets
4.1.2 Di eren e-in-Di eren es
4.2 Multinationality Hypothesis on Index Level
4.2.1 Event Study
4.2.2 Event Study - Ex hange Rate Adjusted
4.2.3 Hypothesis Testing
4.3 Multinationality Hypothesis on Industry Level
4.3.1 Event Study
4.3.2 Mean Reversion
4.3.3 Hypothesis Testing
5 Con lusion
1 Timeline for an event study (Ma Kinlay 1997)
2 Pooled FTSE 100 & 250 Returns of the (Multi)national Portfolios
3 FTSE 100 & 250 Portfolios
4 EuroStoxx 600 and Pooled FTSE 100 & 250 Portfolios
5 Ex hange Rates
6 Ex hange Rate Adjusted Pooled FTSE 100 & 250 Portfolios
7 Ex hange Rate Adjusted FTSE 100 & 250 Portfolios
8 EuroStoxx 600 and Adjusted FTSE 100 & 250 Portfolios
A.1 Stru tural Break in Euro - Pound Ex hange Rate
A.2 Ex hange Rate Euro - Japanese Yen
A.3 Ex hange Rate Euro - US Dollar
A.4 Ex hange Rate Japanese Yen - British Pound
A.5 Ex hange Rate US Dollar - British Pound
A.6 Stru tural Break of the (Adjusted) FTSE 100
A.7 Stru tural Break of of the (Adjusted) FTSE 250
A.8 Stru tural Break of the EuroStoxx 600
A.9 Stru tural Break of the Dow Jones
A.10 Stru tural Break of the S&P 500
A.11 Stru tural Break of the Nikkei
A.12 Energy: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.13 Basi Materials: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.14 Industrials: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.15 Consumer Cy l.: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.16 Consumer Non-Cy l.: EuroStoxx 600 & FTSE 100 & 250 (Inter-)Nationals
A.17 Finan ials: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.18 Health are: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.19 Te hnology: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.20 Tele om: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.21 Utilities: EuroStoxx 600 and FTSE 100 & 250 (Inter-)Nationals
A.22 Energy: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.23 Basi Materials: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.24 Industrials: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.25 Consumer Cy l.: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.26 Consumer Non-Cy l.: EuroStoxx 600 & (Adjusted) FTSE 100 & 250i
A.27 Finan ials: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.28 Health are: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.29 Te hnology: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.30 Tele om: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
A.31 Utilities: EuroStoxx 600 and (Adjusted) FTSE 100 & 250
1 Chow Stru tural Break Test for Indi es
2 Stru tural Break in The Ex hange Rates
3 Re ursive Stru tural Break Test with Supremum Wald Test
4 Di eren e-in-Di eren es of the FTSE 100
5 Di eren e-in-Di eren es of the FTSE 250
6 Di eren e-in-Di eren es of the Eurostoxx 600
7 Des riptive Statisti s of The Multinationality Categorization
8 Des riptive Statisti s of EuroStoxx 600 Multinational Firms
9 Correlation Table of The Input Variables of the Respe tive Three Indi es
10 Regression of CARs of FTSE 100 & 250 Before the Vote
11 Regression of ARs and CARs of EuroStoxx 600
12 Regression of ARs and CARs of FTSE 100 & 250
13 Mean Reversion of Industries: AAR[0℄, CAAR[0,2℄ and the CAAR[0,5℄
14 Regression of Abnormal Returns of European Industries
15 Regression of Abnormal Returns of Pooled British Industries
16 Regression of Individual FTSE 100 & 250 Industries
1 F-Statisti s Chow Test
2 Chow Test Regression
3 Break in Means
5 Di eren e-in-Di eren es Regression
6 Market Model
7 Abnormal Return
8 Average Abnormal Return
9 Cumulative Average Abnormal Return
10 Test Statisti
11 Abnormal Return Regression
12 Ex hange Rate Adjusted Return
illustration not visible in this excerpt
The unexpe ted result of the Brexit referendum to withdraw from the EU resulted in high levels of politi al un ertainty, whi h a e ted nan ial markets adversely. To assess whether the Brexit aused disruptions a stru tural break test was ondu ted for sto k and forex markets. The results suggest that only British sto k markets experien ed signi ant disruptions, whi h was although only minor relative to other adverse events in the last de ade. On forex markets ve ex hange rate pairs were investigated. All onversion rate pairs, ex ept the EUR-USD pair, showed signi -
ant responses. However, again in omparison to other events, the severity of the stru tural break was relatively petite. In the aftermath of the Brexit, British sto k markets developed positive and outperformed many global sto k markets, implying a positive rea tion to Brexit. In order to re tify for a tual developments, it was or- re ted for ex hange rate e e ts in order to gauge the de fa to gains/losses of British and European sto k markets. Therefore, the di eren e-in-di eren es approa h was applied, whi h indi ated that losses for the FTSE 250 ranged between 12-16% and FTSE 100 losses lied between 6-9%. The EuroStoxx 600 evin ed a similar range of losses of 5-8%. Based on the in rease of ountry spe i risk it is obvious that inter- national diversi ed rms should have been less exposed. Hen e, foreign involvement is hypothesised to diminish a rm's sto k pri e rea tion related to the Brexit. By virtue of an event study the e e t of geographi business diversi ation was assessed on British and European (abnormal) sto k returns on the index and the industry level. The results portend to a positive relationship of foreign involvement and sto k returns, whi h implies that multinational presen e of rms mitigated adverse sto k rea tions related to politi al sho ks. On European index level the ndings indi ate a reversed relationship of sto k returns and multinationality of rms
Former Prime Minister David Cameron (Tories) unre e tingly threatened with a refer- endum to withdraw from the European Union (EU) already in 2013 in order to leverage the EU to renegotiate its relationship towards spe ial onditions for the United King- dom (UK). As we know now this set o an unstoppable avalan he (BBC 02.20.2016). The polls prior to the ballot indi ated a tenden y towards a Remain vote, however, the vast share of unde ided voters still denoted that the ra e for some of the Leave advo- ates su h as Boris Johnson and Nigel Farage was still not doomed.1 Hill et al. (2016) summarized the impli ations that are a ompanied with either a remain or a leave vote. A remain vote would have stood for a ontinuan e of prevailing onstitutional law making, whereas a leave vote would stand for an unpre edented path of the rst EU resignation along with an emergen e of high politi al un ertainty. The referendum's result in the early hours of the 24th of June 2016 to withdraw from the EU was nevertheless unanti i- pated to most market parti ipants as the British market was already pri ing in a remain vote. At around 3:40am the BBC announ ed that the Leave adherents' votes outnum- bered the votes to remain within the EU. At the same time already major movements on the urren y markets were in full swing, for instan e, the Pound already tumbled more than 10% against the Dollar to 1.33$ whi h was at that time the deepest level in over 30 years (The, E onomist 06.24.2016). When the British nan ial markets opened at 8:00am its leading sto k market index, the FTSE 100, plummeted from 6338 to slightly below 5800 index points in the rst ten trading minutes, whi h is equivalently to a drop of approximately 8% (see Oehler et al. 2017; numbers from yahoo nan e2). However, within the remaining day the index ould re over a tri e to 6138.7 points (a ording to yahoo nan e data). Though, the FTSE 250 index nosedived even twi e to the extent of the FTSE 100 (Look and Gjorgievska 2016). Other major European sto k indi es, prevalently from southern European ountries, plunged moreover more than UK sto ks by far, however, the authors did not in orporate urren y movements, whi h were dras- ti as outlined beforehand (Look and Gjorgievska 2016). Furthermore, the result of the Brexit also disseminated as an earthquake overseas wiping more than $2 trillion o global sto k markets in one day (The Guardian 06.25.2016). Hen e, it is of parti ular inter- est whether the referendum triggered signi ant disruptions on global sto k markets and foreign ex hange (forex) markets. This question is addressed at the outset of this thesis wherefore stru tural break models are employed.
In the aftermath of the Brexit referendum, it was observed that British sto k markets essentially outperformed other major global sto k markets. This in turn would imply, ounter to intuition, that British sto k markets were positively a e ted by a negative event. Hen e, sto k market related performan e is elaborated in this thesis with regard to su h parti ularities, whi h are also shown to not fully re e t the reality, as also major urren y u tuations were monitored. This thesis therefore tries to shed some light on the dark by quantifying a tual in urred gains or losses of British and European sto ks markets relative to other sto k markets, wherefore the Di eren e-in-Di eren es (DID) approa h is predestined.
When going a level deeper from the index to the se tor level, high dispersion among industries' rea tions was observed at the Brexit vote. British bank sto ks fell in the range of about 30% due to the Brexit vote result, though, these equities were also able to re over from their losses to roughly minus 15 - 20% (The, E onomist 06.24.2016). However, other se tors were not penalised at the extent of the banking se tor, whereas one other industry in turn had to a quies e even higher losses, respe tively. This heterogeneity in responses points to bran h-spe i rea tions besides rm spe i e e ts, whi h ould (mostly) be pre-empted in the ase of a vote to exit the EU. The British banking industry ould lose for instan e their EU passports, so their banking li enses, and not be able to operate in EU ountries anymore (Odendahl 2016). Still, within those se tors there was also a on- siderable heterogeneity in responses, whi h portends to spe ial rm hara teristi s, whi h investors rewarded or punished as well. Thus, a next aim of this thesis is to nd a rm spe- i determinant investors re ognised on the rm level and industry level within the days after the ballot. The Brexit referendum onstituted a ountry-spe i risk, also referred to as politi al risk, wherefore international persisting e e ts should not be observable. Therefore, it is intuitive that geographi business diversi ation of rms might have on- stituted a rm hara teristi investors rewarded when the results of the Brexit ballot were de nite. This is supported by the substantial depre iation of the British Pound-Sterling, whi h in turn in reased the value of rms' foreign assets of ompanies. Simultaneously, foreign sales are sin e then more valuable denominated in British Pound. Therefore, the hypothesis for this thesis is that business diversi ation3 of rms mitigated the adverse rea tion of the ompanies' sto k pri es. International sales are thought to be diminishing the exposure to politi al risk of enterprises, simply with the diversi ation of politi al risk by means of the engagements in other ountries. This argument is in a ordan e with theoreti al reasoning on the bene ts of operation diversi ation, dis ussed in the prevailing literature (see e.g. Kwok and Reeb 2000; Oehler et al. 2017). Hereby an event study is ondu ted for the rst indi ation and visual representation of the impa t of geographi business diversi ation. For the hypothesis testing several regressions following Oehler et al. (2017) are employed in order to determine the meaning of business diversi- ation a ross domesti borders for apital investors. Additionally, this is enhan ed by also examining se tor level rea tions, where highly distin tive rami ations ould mostly be anti ipated onditional on the industry prior to the vote (however, not for ea h se tor and sub-se tors). Furthermore, it is also elaborated whether the rea tions parti ularly on the sto k market were exaggerated in the sense of a mean reverting pro ess on industry level.
This thesis was able to nd eviden e for a positive relationship of multinationality of rms and sto k returns at the Brexit referendum, so in the ontext of a politi al sho k. Thereby, the international involvement of rms served as a sho k absorber. For European sto k markets the reversed pattern was evident, although the magnitude of the e e t is rather small.
Regarding the results of stru tural breaks of sto k market indi es it was as ertained that only British sto k markets experien ed a signi ant alteration in their behaviour. The stru tural break test for the re ursive pro edure, the supremum Wald test, strongly support the previous nding for the British FTSE 100 sto k market, however, only for a petite time span. When expanding the time-frame the stru tural break aused by the heavy oil pri e de line outweighed the Brexit event on sto k markets. Hen e, the Brexit aused only a minor stru tural break relative to other events su h as the European sovereign debt risis or leave alone the great nan ial risis whi h were mu h larger in their severity. On the urren y markets the results suggest that the Euro, the US-Dollar and the Yen relative to the British Pound experien e major realignments in the onver- sion rates, whereby inituitively the British Pound depre iated towards their ounterpart. Furthermore, an appre iation of the Japanese Yen relative to the Euro was re ognised, whereby the Euro - US Dollar ex hange rate did not fa e a severe break. By means of the re ursive model the break dates oin ide essentially with the presumed date of the break in the mean tests for the Yen and the Pound, ex ept for the Euro - US Dollar pair. However, when onsidering even longer time horizons for the supremum Wald test the signi an e of other events outweighed the Brexit. The results for the di eren e-in- di eren es approa h intimate that the losses of the British lead index, the FTSE 100, are in the range of 5 to 9 per ent. Moreover, the FTSE 250 results suggest de lines of 11 to 17 per ent. However, very interestingly, the EuroStoxx 600 index su ered losses roughly to the same extent as the FTSE 100, whi h implies that investors were not di erenti- ating between dire t impa ts of British sto ks and impli it e e ts of European equities, respe tively. Robustness results indi ate two per ent higher losses for the FTSE 100 but support the range of losses for the FTSE 250. The EuroStoxx 600 sturdiness results sug- gests losses ranging inbetween six to eight per ent, whi h is still roughly equivalent to the FTSE 100 losses. In the se ond main part the results portend to a material e e t of geographi business diversi ation investors onsulted. In the run-up to the referendum the exa t opposite pattern ould be determined for rms in the FTSE 100, whi h an be attributed to polls whi h indi ated a membership ontinuation within the EU. After the publi ation of the ballot results, investors in turn immediately rea ted onversely on the basis of the arisen politi al in ertitude. However, in both British indi es, the FTSE 100 and the FTSE 250, the results suggest that higher internationalization implied lower de lines in se urity pri es. Although, the magnitude of the e e t bise ts for the FTSE 250 relative to FTSE 100. The EuroStoxx 600 sto k returns exhibits a negative impa t of business diversi ation as well as a negative in uen e of leverage in reasing over time and a positive impa t of size whi h is de reasing over time. On British se tor level, the indus- trials, the non- y li al onsumer, the nan ial and the y li al onsumer se tor evin ed a sturdy positive relationship of equity returns and international engagement. In the Eu- roStoxx 600 se tors the nan ial bran h, the energy se tor and the te hnology industry exhibit a negative relationship of sto k returns and rm-level internationalization, where the robustness is although not awlessly.
The master thesis pro eeds as follows: in se tion 2 the hypothesis is formulated a - ording to urrent state of the (a ademi ) literature for the se ond major part. Se tion 3 elaborates the applied methodologies in detail in this thesis. The results of the overall sto k market omportment regarding the stru tural break tests are depi ted and dis ussed in se tion 4.1.1. This is followed by the a tual in urred losses of British and European sto k ex hange indi es relative to some referen e sto k market in the DID approa h in se tion 4.1.2. The results for the se ond main part (se tion 4.2 et. seqq.) of this s ienti work tries to de ompose the sto k market rea tions and the potential relationship of the degree of rm level internationalization and the respe tive se urity pri es. This is more- over assessed at the sto k and industry level and graphi ally displayed by means of an event study. In se tion 5 the thesis is summarized along with the dis ussion of the results.
In this se tion the hypothesis, whi h (possibly) a e ted the individual rm's sto k pri es and the respe tive se tors, is derived.
Large and mature entities, so alled Blue Chips, as well as medium sized orporations are often hara terised by a (sometimes even substantial) relian e on foreign markets i.e. international geographi al diversi ation of their respe tive business operations (Oehler et al. 2016).4 This is a ompanied with no perfe t orrelation of the ountries' e onomies, whi h in turn merits the term diversi ation as theoreti ally a rm's default probability should be mitigated (Burgman 1996). Despite the fa t that the referendum's result was highly startling, the (future) separation from the EU an be ategorized mostly as an idiosyn rati risk to the UK. Hen e, major and persistent transnational impa ts shall not arise from an international point of view, ex ept for the impli it damage in reputation of the EU. On the basis of in reased ountry spe i risk, it seems obvious that multina- tional presen e of rms might have had an alleviation e e t in omparison to orporations fo ussing solely on British markets (Oehler et al. 2017). Another alternative explanation why rm-level internationalization ould have had a mitigating e e t was the expe ted urren y depre iation, in ase of a Leave vote in the referendum. Thereby, foreign sales and asset values denominated in foreign urren ies are ultimately more valuable in Pound terms (Hill et al. 2016, p.15). Thus, the hypothesis an be formulated as follows:
- A larger degree of geographi business diversi ation implied a lower proneness of adverse sto k pri e rea tions.
The results of Lombard et al. (1999) suggest for instan e that domesti orporations are exposed solely on domesti fa tors (of ourse), whereas internationally diversi ed rms are exposed to the same fa tors less than one half. However, international rms are exposed to additional sour es of risk su h as geographi lo ation and an international industry fa tor a ording to Lombard et al. (1999). Burgman (1996) names other origins of risk su h as agen y osts and politi al risk (e.g. tax poli y), whi h was highly present at the Brexit referendum. With that in mind, the hypothesis in turn also impli itly answers the question whether geographi business diversi ation limits the exposure to politi al risk, for instan e, in ase additional referenda, to withdraw from the EU, are held. However, the alleviation of rm internationalisation on sto k returns in ombination with a ertain politi al sho k in the short-run has until now only been examined by Oehler et al. (2017). The authors found for instan e a highly signi ant impa t of multinationality on abnormal returns in their event study. 4. At the outset some general explanations for the reader: the terms geographi al business diversi a- tion and multinationality in general have to be viewed as di erent notions, although in my thesis both an be interpreted as synonyms. Additionally, next to geographi al diversi ation there is also produ t diversi ation (Chkir and Cosset 2001), whereby I am always referring to the former diversi ation type in the thesis.
This s ienti work adds a ontribution to a ademi literature, as unfortunately, only very little literature regarding the impa t of foreign involvement and sto k returns in the presen e of high politi al in ertitude is available. Nevertheless, a multitude of s ienti pa- pers examined the superior bene ts of international portfolios over national ounterparts (see Santis and Gerard 1997, Errunza et al. 1999, Bekaert and Harvey 2000, Christo ersen et al. 2012, Chiou.2013).
Firm-level internationalization might be a e ted by other rm hara teristi s su h as rm size (Oehler et al. 2017). This argument is very intuitive for European ompanies, as national market expansions are onstrained multiples in size and ustomers relative to US or high growth developing ountries su h as China. Business operation internation- alization for instan e in reases with rm size a ording to Riahi-Belkaoui (1999). The author ites that there is positive onne tion between the degree of geographi al business diversi ation and the market value of equity. His explanations suggest that the market pri es in the extent of internationalization as an unbooked asset in the rm . Mayer and Ottaviano (2008) also put forward a larger entity size of transnationally operating European rms relative to domesti operating rms. Altomonte et al. (2013) aim to nd a link between innovation and multinationality, where he also lari es that enterprise size in reases with internationalization. The results of Hill et al. (2016) suggest that the rm size was a material determinant of politi al un ertainty, whi h negatively a e ted sto k pri es prior to the Brexit referendum. Thus, rm size is a ounted for in the hypothesis testing (for further lari ations see se tion 3.2.2.
Furthermore, other pe uliarities hara terise and distin t national from international entities, su h as the apital stru ture, often referred to as leverage (ratio) or debt ratio et . Early studies of this interdependen e of leverage shows that domesti ompanies are having signi antly higher debt ratios (see Fatemi 1988; Lee and Kwok 1988; Burgman 1996). A More re ent paper by Akhtar and Oliver (2009) elu idate a negative relation of orporate transnational diversi ation and the debt/equity ratio in Japan. A multitude of studies also examined the apital stru ture for national and international enterprises in the US. Doukas and Pantzalis (2003) for instan e are able to nd again a signi ant di eren e in leverage of domesti and multinational ompanies, whereby latter have again a lower debt a i ted apital stru ture. Mittoo and Zhang (2008) ome to the same on lusion for the US, however, in Canada the results indi ate that national orporations employ less debt apital than multinationals. Further studies that examine and provide results that multinationals arry less debt than their domesti ounterparts are Akhtar 2015 and Homaifar et al. 1998. Contrary to the previous mentioned studies Mi hel and Shaked (1986) found that US based rms have a lower debt/asset ratio. Still their results also indi ate that national rms are riskier in terms of standard deviation and Capital Asset Pri ing Model (CAPM) Beta by Sharpe (1964) than multinationals. Akhtar (2005) ould not verify a signi ant di eren e between Australian multinationals and domesti rms. However, the author stated that ompanies in the nan ial se tor exhibit leverage ratios that are in turn determined by the amount of deposits and banking regulation, whi h portends also to se tor spe i apital stru tures.
Furthermore I also in orporate European rms listed in the EuroStoxx 600 (but ex- luding British rms from this sample). Thereby it is assessed in whi h patterns and dimensions the unanti ipated result of the referendum spread over ontinental Europe. However, sto k returns are assumed to not have been in uen ed by multinationality on ontinental European level. Hen e, there is no related hypothesis , as the degree of rm internationalization is not an anti ipated key determinant of European orporation's sto k pri e rea tion related to the Brexit on the basis of virtually the same e onomi outlook for domesti ally and internationally operating rms. In general, one ould observe that sto k pri e rea tions were also primarily negative due to un ertainty the EU is fa ing as well with its unpre edented ase of a disembarking ountry. Further, Europe was also impli itly a e ted by means of the EU with the loss in its on den e and possible onta- gion e e ts for other ountries to follow the UK and exit the EU. Hen e, European sto k markets also rea ted highly adverse.
Within this se tion it is elaborated whi h rami ations a potential withdrawal implied for ea h se tors and why. Hen e, a tual se tor rea tions are omprehended better in my point of view. The industrials' rea tion on the sto k markets an and will of ourse be di erent either in the dire tion and/or the magnitude with respe t to ea h industry, respe tively. This is on the basis of the ex ante impli ations in ase of a leave vote has had on se tors and sub-se tors. Hen e, I will outline arguments for the short-term behaviour along the Brexit referendum on the basis of long-term prospe ts and (potential) impli ations in ase the UK is not able to establish satisfa tory arrangements with the EU. Nevertheless, ertainty for ea h industry an be elu idated when the negotiations with the EU are ompleted in 2019. Maybe those two years are even a too narrow period of time for negotiating. Still, some (sub-) se tors were barely overed in the media and/or simply were only negligibly exposed to the Brexit vote. The following order of the industries orresponds to the sequen e of the Thomson Reuters Business Classi ation (TRBC).
The UK the energy se tor is responsible for 6% of total government tax re eipts (Pollitt 2017). Up to now the British energy se tor ful ls European regulation, whi h heavily a e ts the needs of energy in Great Britain. The energy se tor omprises renewable and atomi energy as well as fossil energy providers (Thomson Reuters 2012). Currently, being member in the European Internal Energy Market ensures stable and dis ounted ele tri ity pri es for English ustomers due to the inter onne tedness with ontinental European ountries. However, the margins of the power apa ity are nearly at its limits whi h implies that the produ tion of ele tri ity is losely su ient to meet peak levels of demand. Thus, the so alled energy se urity pro le is at risk denoting potential unanti ipated ele tri ity supply disruptions. For the avoidan e of su h a s enario new investments in power generating units are required. Nevertheless, British regulators framed rules aligned on guidelines on EU level, whi h are said to rest upon a solid foundation. Still, due to the referendum the British will have to renegotiate existing and also establish new rules, whi h is going to be a hallenging task. In ase the two years of negotiations won't su e in rearranging prevailing trade agreements, this will give rise to un ertainty again that impli ates potential delays or abandonments of proje ts for the energy infrastru ture (Flavell and Villana i 2016).
The Great Britain gas se tor is assumed to resist unfavourable out omes of the Brexit withdrawing. Despite the fa t that domesti produ tion in the North sea is de lining and hen e, more Liquid Natural Gas (LNG) needs to be imported, su h imports are hedged by means of long term ontra ts with the EU. On the basis of these fa ts, the e e t on the a essibility of LNG is anti ipated to be very limited (Flavell and Villana i 2016). An analysis of Flavell and Villana i (2016) suggests that Great Britain's a ess to fossil energies su h as oal, gas, oil and related re ned produ ts in ensured and in no way impaired. A ording to Pollitt (2017), the UK re eives large LNG imports from Norway next to European ones. Hen e, the author argues that even a hard Brexit would have only minor impli ations for the UK energy se tor. Hill et al. (2016) gauged the politi al un ertainty (proxied by the probability of a Brexit in the referendum) in the run-up to the referendum. Their results suggest that the Oil & Gas se tor was among the rms exhibiting the lowest exposure to politi al risk.
In my point of view the third party a ess to British markets is also one major key topi . This might result in bene ial out omes for national energy providers as the a ess of foreign orporations ould get visibly hampered (Flavell and Villana i 2016). Further, the Her ndahl-Hirs hman-Index (HHI) for this respe tive se tor is already per eived to be rather un on entrated a ording to Moss and Bu kley (2014).5 On the basis of these two arguments oligopoly-like onditions ould emerge in the UK. Thereby ompetition ould be diminished even further, resulting in a higher markup of energy pri es, whi h in turn positively a e ts the pro tability of the related ompanies at the expense of onsumers. Still, the energy se urity pro le ould be ameliorated when enterprises are nan ially more sound, but ustomers ould be exploited. The possible limited market a ess for foreign entities might urb also infrastru ture investment (implying a de rease in energy se urity) where both arguments have to be weighed against one another by the government.
As Great Britain an address these issues on their on behalf without having any dire t sever e e ts imposed on this se tor one an dedu e that the British energy se tor was, either not at al, or more likely positively than negatively a e ted within the days of the referendum. Unfortunately, there is only one national energy rm listed in the FTSE 250. So, visual inferen es regarding the hypothesis underlie too mu h idiosyn rasy.
The basi materials se tor is omprised, as its name suggests, of rms whi h extra t, produ e, re ne and/or pro ess raw materials (New York Times, n.d.). This in ludes rms su h as mining, hemi al, metal produ ers, papers and forestry ompanies (Thomson Reuters 2012).
From the end of 2015 to the end of 2016 the 7 mining sto ks doubled its weight in the FTSE 100 to 5.5%. In addition, all revenues of these rms are denominated in US Dollars, whi h boosted their sales in Pounds even further with the depre iating Pound due to the referendum (Wrathall and Broda 2016). The British mining industry did not really exhibit strong sto k market rami ations along the referendum's results. Sin e the Brexit vote (until Mar h 28th 2017) mining sto ks were the best performing equities in the FTSE 100 (Connington 2017). In an event study by Ramiah et al. (2017) even found eviden e of a signi ant redu tion in systemati risk for this industry after the Brexit vote. Lawless and Morgenroth (2016) assume on the basis of their results that trade from and with the EU is negligibly a e ted for most of su h produ ts in ase the UK is la king a membership in the single market after the two years of negotiations.
The hemi al se tor has a high share of trade with the EU and vi e versa. Still, in ase no arrangements with the EU an be rea hed, the de rease in overall trade of su h 5. In order to gauge the ompetition intensity within an industry several measures exist. One prominent example is the HHI, whi h simply squares the respe tive market share of an enterprise. Thereby the HHI is lowest when rms have an equal market share and high when the market shares are highly asymmetri for any number of rms (Calkins 1983). The general theory is suggesting that 0-1000 implies low on entra- tion whereby numbers above 1800 suggest high levels of on entration, see also http://www.geogr.uni- jena.de/fileadmin/Geoinformatik/Lehre/ba kup_05_2007/Modul141/Skript/Skript-Kap5.pdf produ ts with the EU would be below 20% a ording to Lawless and Morgenroth (2016). Ramiah et al. (2017) omputed in their event study an AR of this industry whi h is slightly positive with 0.23%.
Johnston and Buongiorno (2016) predi ted the impa t of the Brexit on the interna- tional forest produ t se tor distin t by an optimisti and a pessimisti s enario. In the latter setting, the e e t was larger than in the optimisti s enario (of ourse), however, the overall impa t of both was identi ed to be small. Lawless and Morgenroth (2016) also argue that, next to iron and steel, paper produ ts would merely be levied with very small tari s when the negotiations would progress in an undesired way. In the previously mentioned study by Ramiah et al. (2017), the authors en ountered a very positive AR of 3.82% for the forestry and papers industry. Furthermore, Hill et al. (2016) as ertained that this se tor was among the lowest exposed to politi al risk.
On the basis of the arguments brought forward one an expe t that the rea tion of this se tor should be positive or at least non-negative, very similar to the previous Energy se tor. However, there is no domesti lassi ed rm in the EuroStoxx 600, just one in the FTSE 100 and only two in the FTSE 250. Hen e, idiosyn rati parti ularities ould distort the real industry behaviour, whi h hampers the visual assessment of the di eren e in the national and international portfolio's returns and the inferen es from the hypothesis testing on the industry level.
This industry omprises several di erent ompanies whi h either produ e or provide industrial items and solutions and this se tor an further be bran hed out into industrial goods (aerospa e and defen e, ma hinery et .), industrial and ommer ial servi es ( onstru - tion, professional and ommer ial servi es), industrial onglomerates, and transportation (freight and logisti s, passenger transportation servi es, transport infrastru ture) (Thomson Reuters 2012). Hen e, it is very di ult to propose overall valid statements regarding the general industrials' industry rea tion on the sto k markets, as the referendum ( ould have) had partly alternating impli ations on every small bran h.
The rst one of the aforementioned bran hes, namely the onstru tion industry, was already fa ing an e onomi ontra tion prior to the referendum and ould further be hara terised by a gloomy e onomi outlook. Additionally with the vote to leave the EU several other un ertainties ame into play. For instan e, European workfor e might migrate ba k to ontinental Europe resulting in a shortage of skilled and unskilled labour (Green 2016). Additionally, with a lower demand of a ommodation house pri es are likely to fall, whi h has ultimately been the ase in the UK (ex ept Wales) for instan e for the rst three onse utive months in 2017 (Shaw 04.15.2017). A ording to Wood et al. (2011) the onstru tion se tor is among the most ompetitive industries in the UK. Hen e, it is hallenging to stay pro table in su h an environment.
The aerospa e (and defen e) se tor en ompasses no airlines but other rms like Air- bus, an aeroplane produ er. The British aerospa e se tor is a ounting for 2.3% of British total exports where 45% are destined to the European Union. The ere tion of barriers in this se tor would hurt both, the EU and the UK mutually (Booth et al. 2015). Further- more, tari s ould be implemented for this industry up to 7.7% if the UK fails to align their interests with European ones (European Movement International 2016). Ramiah et al. (2017) en ountered on the day after the referendum (24th of June 2016) in their event study that the aerospa e (and defen e) se tor had a positive AR of 2.6%, whi h the authors ategorized in the unexpe ted group as media presen e did not over this se tor by and large.
Another industry that might be severely a e ted a ording to the European Movement (2016) is the professional servi es bran h. A ording to Booth et al. (2015) this se tor employs 11.6% of the total British labour for e and its share of total British exports amounts to 9.9% whi h makes it an indispensable pillar of the e onomy. Furthermore, this industry does not fa e the risk of tari s but the un ertainty in the mutual re ognition of professions in ase no satisfa tory agreement an be negotiated (Booth et al. 2015). British government statisti s (2015) further portend to low business on entration as the top 15 rms just turned over around 22 per ent of the total se tor revenues in 2015. Ramiah et al. (2017) as ertained an AR for this se tor of -3.6% on the 24th of June 2016.
The passenger transportation se tor an be sub- ategorized further into aviation, rail- way and maritime rms (Thomson Reuters 2012) . However, I will outline only the more important airlines se tor. One key issue in this se tor is the EU Open Skies agreement (Gerrard 2017). If the UK does not ome up as a member of the Open Skies agreement, then signi ant impa ts will be observed for the airlines (Booth et al. 2015). This is due to the so alled Air Operator Certi ates (AOCs), whi h urrently su es to hold the UK AOC in order to approa h European airports. However, after the separation from the EU (without agreements) this implies to apply and ful l regulations to obtain the AOC for EU airports. Easy-Jet, a British airline, does not have the AOC of the EU, however, this rm applied for it just weeks after the Brexit vote in order to guarantee ontinental European business in two years after the negotiations without surprises (Gerrard 2017).
Immediate se tor related rea tions on the sto ks markets one day after the referen- dum an hardly be anti ipated, due to intra-se tor parti ularities and the wide range of rms omprised in this se tor with (potentially) opposing rea tions. This is paired with insu ient domesti rms in order to draw on lusive results for the hypothesis testing.
As in the previous se tion 2.2.3, this industry an also be subdivided into several bran hes. These in lude the onsumer durables (e.g. household, leisure equipment, textiles et .), onsumer servi es, media, the automotive (and omponents) and lastly the respe tive retail se tor for su h items. (Fritz et al. 2013; Constable 2013). Thus, it is also here very deli ate to anti ipate unanimous responses with regard to sto k markets and future prospe ts on the basis of the re ently initiated negotiations with the EU, where the out- omes are urrently a i ted to high un ertainty and annot be predi ted. Therefore I outline some rami ations of the Brexit related to (most of ) these sub-se toral business elds. the onsumer durables bran h ontains rms that manufa ture produ ts that tend to endow an avail or satisfa tion over a longer period of time e.g. washing ma hines, furniture, leisure produ ts, lothing and so forth. These sto ks additionally tend to ovary with the business y le (Constable 2013). The leisure (and travel) industry is anti ipated to rea t negatively to the Brexit event on the basis of a redu ed pur hasing power for va ations and related goods/equipment due to the depre iation of the Pound (Ramiah et al. 2017). Next to that argument, Barnard (2016) states that in ase the negotiations end up with no membership in the European E onomi Area (EEA) and just free-trade arrangements, the tourism industry will ertainly be a e ted. This is based on the fa t that if servi es or persons are not allowed to move freely, then a va ation with visas, whi h are a ompanied with osts and hassle, might be reason enough for families to re onsider holiday destinations. Furthermore it is to mention that around two-thirds of all British tourists are European itizens. Further, the results of Ramiah et al. (2017) indi ate that the leisure and travel industry had an Abnormal Return (AR) of -3.16%. Hill et al. (2016) as ertained that this se tor was the most a i ted industries exposed to politi al un ertainty next to nan ial se tor.
The results of Ramiah et al. (2017) further suggest that the household goods and home onstru tion industry group lost most (in terms of ARs) on the day of the pro lamation of the vote's out ome. Even onsiderably more than the nan ial se tor in their setting. This might result from demographi , politi al and business prospe ts of this industry. Furthermore, the lothing industry exhibits high un ertainty too. Assuming that negoti- ations with the EU fail and the UK does not get member in the European single market, then the WTO rules for trade and tari s would apply, whi h would be on a rather high level. (Lawless and Morgenroth 2016). The results of Lawless and Morgenroth (2016) portend to a de rease of trade from and with EU ountries of up to 99%, whi h would be immense. The se ond largest industry hit in terms of trade redu tion would be the food se tor with trade lowering more than 90% (Lawless and Morgenroth 2016). However, these numbers are exaggerated in my point of view.
The automotive se tor in the UK is a large employer with around 800,000 jobs. Some outlooks of this bran h were rather less propitious whi h predi ted a signi ant redu tion in ar sales. However, this may be partly o set by the loosening of the British monetary poli y shortly after the referendum of the Bank of England (BoE), whi h was anti ipated in ase the ballot was in favour of a Brexit (Bailey 2017; Allen and Elliot 2016). In addition, the sharp fall of the the British urren y, the Pound-Sterling, against some other major urren ies may also be stimulating in terms of sales volumes as ars are mu h heaper for foreigners. Contrary, for the European ar produ ers this depre iation is unfavourable, as ar sales in the UK are on the one hand expe ted to de rease as the pur hasing power (in foreign terms) de reased and on the other hand the sales are denominated in Pounds whi h dire tly a e ts their revenues in Euro terms (Bailey 2017).
Subsuming, one an de nitely expe t that this industry was heavily a e ted by the ballot's results. This se tor has in addition an a eptable number of domesti rms in order to test the multinationality hypothesis, also on industry level.
Consumer non- y li al enterprises, often referred to as the Consumer Staples se tor, usually onsist of rms whi h are hara terized by produ ing items whi h are immedi- ately onsumed and mostly also regardless of the e onomi onditions (Constable 2013). So, typi al examples in this ategorization of sub-industries are food, toba o, beverage and asso iated retail orporations. The TRBC furthermore lassi es personal and house- hold produ ts & servi es as wells as food and drug retailing as non- y li al onsumer rms (Thomson Reuters 2012). The British food, beverages and toba o market employs around 3.7% of the total British labour for e. The same per entage amount (3.7%) is added to total UK's exports by this se tor.
Ramiah et al. (2017) points out that the British food industry is heavily reliant on the EU as 90% of the farmers' in ome is disbursed by it. Nonetheless, food is a basi need and therefore most food rms are anti ipated to have de lined only modest at the Brexit vote. A ording to Lawless and Morgenroth (2016), the food industry is also among the most a e ted ones in ase the the UK falls short of upholding the membership in the EEA during the negotiations. This implies falling ba k to World Trade Organization (WTO) trade and tari agreements. In ase this o urs, the authors even prognosti ate a trade redu tion of 90% with European rms, as mentioned previously. A ording to Open Europe (2015) the food, beverage and toba o se tor exhibits a trade de it for the UK against the EU.
Thereby an in entive is given for the EU to agree on an arrangement as more goods are imported to the UK (from the EU) than vi e versa. Ramiah et al. (2017) found a negative sto k market rea tion with an AR of -1.36% on the day after the referendum. In ontrast, the authors identi ed a positive AR for beverages with 1.16% and an even higher one for the toba o industry with 5.19%, both in the group of unexpe ted results due to low interest of the media on these se tors.
Con lusively, one an suspe t that the overall industry was a e ted by the Brexit vote, however, not to a large extent due to their business models whi h satisfy everyday needs. The hypothesis for internationalization an be examined on industry level as this se tor exhibits enough rms for omprehensible results and is not biased by rm spe i e e ts.
The nan ial se tor in Great Britain is very large relative to the overall e onomy and ontributes to about 11.5% to total government revenues (Odendahl 2016). Moreover, 9.3% of UK's total exports are generated by the nan ial and insuran e industry Booth et al. 2015, so in total an essential part of the British e onomy. However, this se tor further omprises real estate, olle tive investment and holding ompanies too, next to nan ial institutions and insuran es (Thomson Reuters 2012).
The nan ial se tor was among the most sharply orre ting se tors after the Brexit vote. In an event study by Ramiah et al. (2017), the authors as ertained that banks had an AR of -4.99% on the 24th of June 2016. Life insuran es were hit onsiderably too with an AR of -4.2%. In ontrast, nan ial servi es and non-life insuran es were af- fe ted meeker with an AR of -1.94% and -0.4%, respe tively. However, one ould assume already in pre-referendum times that if the UK voted in favour of an EU exit, British banks, insuran es et . fa e the potential loss in the a ess to the enormously huge Eu- ropean market in ase the a ompanying bank li enses (also referred to as passports ) are not reissued when the negotiations from the divor e from the EU are getting nasty. Thus, banks and insuran es are fa ing huge potential redu tions in revenues and/or in- reases in administration expenses, whi h both a e t a rm's pro tability. The results of Hill et al. (2016) reveal that the exposure to politi al un ertainty was highest for the nan ial se tor and the onsumer y li al se tor as mentioned already in se tion 2.2.4. In most ases in ertitude is penalised by investors, whi h was ultimately the ase after the referendum. A ording to Campos (2012) the intensity of ompetition in the nan e and insuran e industry is utterly pronoun ed. Their datasets refer to the year 2010, however, su h stru tures usually adapt only slowly over time, when e one an onje ture that this past geographi al on entration maps therefore roughly the urrent prevailing intensity.
Furthermore, a bun h of global players in the banking world are likely to remove jobs to ontinental Europe as they annot run their EU businesses from London (Arnold and Noonan 2016). This also often referred to as the Brexodus, so ompanies and labour for e leaving the UK (Sorrell 2016). Hen e, one an subsume that British banks and insurers were highly a i ted at the referendum.
It is furthermore of interest whether the degree of internationalization has signi ant varying e e ts on international and solely British nan ial equities. This is grounded on the one hand that multinational rms fa e the potential loss of their nan ial passports. On the other hand those orporations redu ed their politi al risk with their European sub- sidiaries whi h should have a mitigating e e t. Domesti rms are ompletely exposed to British politi al risk and the British business y le where several in uential e onomists (Swati Dhingra, George Osborne, Mark Carney, David Miles and many more) fore asted a re ession for the UK in ase of a vote for withdrawing from the EU (Mason 05.23.2016, Chan 12.06.2016, Giles and Tetlow 01.03.2017 and Ryan 06.23.2016). Additionally, om- petition will possibly intensify even more when the big international nan ial institutions do not get the permission for their businesses in ontinental European ountries, whi h would be detrimental for smaller nan ials. However, those smaller rms in turn are merely modest a e ted of the EU nan ial passporting s heme. On the other side large aps with high relian e on foreign markets do not rely solely on European markets but operate partly worldwide. Still, it annot be pre-empted ex ante whi h argument was more valuable to investors. In total, however, this se tor is assumed to have been highly adversely impa ted by the referendum.
In order to gauge the e e t of domesti and international nan ial on industry level rms a su ient number of ompanies is available. Moreover, Italian banks are dropped from the European dataset. This is due to the fa t that following the vote, these banks or- re ted onsiderably and Raddant (2016) identi ed already high levels of volatility among Italian nan ials prior to the Brexit vote. Hen e, he argues that the Brexit was a trig- ger for anxieties of potentially failing Italian banks whi h would therefore exaggerate the a tual European impa t.
The British publi health are system onsumes about 8.4% of Great Britain's Gross Do- mesti Produ t (GDP), so a onsiderable amount of money (Chang et al. 2008). Next to health are servi es, this se tor onsists also of pharma euti al & medi al resear h om- panies (Thomson Reuters 2012). In 2010, the health are market density in the UK was per eived as relatively sparsely on entrated with a HHI of 123 of the top ve enterprises a ording to Forder and Allan 2011. However, the assessment of ompetitiveness dedu ing from entire market on entration is rather hallenging as the low level of the HHI might on eal lo al high-density distri ts (Forder and Allan 2011). O ial British government statisti s shows low on entrations as the top 15 are homes' ompanies generated merely 17% of the total se tor turnover (2015).
One major fa t this industry is imminent of is the potential loss the of workfor e, as 10% of the British National Health are System (NHS) are ontinental European do tors, whi h might lead to serious issues. However, next to do tors also 5% of people working in are homes originate from EU member ountries. Without free movement of labour this industry may fa e hallenges to re ruit new and hold sta . Hen e, this might result in an advantage of wage negotiations for (potential) employees, but therefore also impli itly to higher fees and/or de reasing pro tability as margins will narrow (M Ke hnie 2016).
On the other hand, the demand of health are will in rease due to the ageing popula- tion whi h ould further taper the sta ng issues in this se tor (Government UK 2016). However, if these di ulties in lling the future va an ies indu ed by the Brexit (de- pending on the out omes of the negotiations) an be over ome, this se tor might have a ourishing future and get an even more material pillar for the labour market. In addi- tion, Great Britain is attra ting people seeking for private medi al are ( y-in patients), whereby its apital ity developed itself already to the entre point for osmopolitan pa- tients. A ompanied with the depre iation of the Pound-Sterling at the referendum, this ould evolve in an even higher attra tiveness for international people seeking top private health are (M Ke hnie 2016). Still, this se tor was not extensively dis ussed in the media wherefore Ramiah et al. (2017) ategorized this se tor into the group with unexpe ted responses. A ording to M Ke hnie (2016) so ial are markets are resilient, operators an su eed in even the toughest environments and investors have be ome and will need to be more astute than ever .
Pharma euti al entities are also material pillars in British and European e onomies. Bruegel (2017), an European e onomi s think-tank, points out that even when no agree- ments with the EU are established, implying to trade with ea h other over the WTO framework, there are virtually no tari s on pharma euti al produ ts. However, other barriers for trading su h items ould arise from border ontrols and immigration he ks. This would result in an in reased delivery time and in reased administration, whi h would in turn a e t margins for pharma euti als. This is industry is furthermore hara terised by high expenses in Resear h and Development (R&D). Another drawba k is that again funding from the EU for R&D in Britain would vanish. And the United Kingdom has the se ond highest share (after Germany) of the EU R&D budget with approximately 20%. Hen e, again the British government would have to substitute the missing funding. Furthermore, as in the are homes and te hnology industry, the pharma euti al se tor relies onsiderably on European personnel, whi h might reassess the lo ation UK in ase of a la k of nan ial resour es. Nonetheless, pharma euti als exhibit in general a low elasti ity of demand, so substantial pri e in reases redu es demand only very little. This hara teristi on edes relatively stable revenues for su h orporations (Bruegel 2017).
Further, Hill et al. (2016) also lassi ed this se tor to one of the least exposed to politi al un ertainty. Hen e, short-term rea tions are anti ipated to be only minor as no heavy or dire t eventuating rami ations are in urred. However, the visual results of the multinationality hypothesis an only be viewed at with aution as there are only two domesti rms in the FTSE 250, whi h implies a high amount of idiosyn rasy.
The te hnology se tor ontributed with a (gross) value added of ¿118.3 bn to the British e onomy in 2014, whi h was then equivalent to 7.3% of the British e onomi output. In addition there are two million jobs in the British Digital E onomy (Government UK 2016). This se tor an in turn be split up into two major bran hes, namely the te hnology equipment and software & IT servi es (Thomson Reuters 2012).
Prior to the ballot, this industry advo ated the UK staying within the EU on the basis of the international fo us of their businesses. After the referendum experts were anxious regarding investors turning their ba k on British te h-enterprises. However, a tual investor behaviour was not as detrimental as outlooks predi ted, te h-deals even marked a re ord-high in 2016. Still, investment fell 28% on a yearly basis, but supposedly not only be ause of the vote a ording to some investors. The idea and opportunities are the still driving for es of an investment a ording to investors. Furthermore, the EU is developing on a framework for the so alled Digital Single Market whi h permits apital and te h-workers a ross this bran h to move freely. Thus, British ompanies might lose agility, exibility and of ourse the unobstru ted work ow a ross EU ountries (M Googan 2017). Additionally, around 45% of all free va an ies are lled from people oming from abroad, whi h makes this se tor extremely reliant of EU talent (and the rest of the world) who simply ould re onsider plans and avoid the UK (Roberts 2017; M Googan 2017). Further, funding for this se tors from EU (¿1.4 bn in 2013) will stop, whi h needs to be perpetuated then by the British government (Ramiah et al. 2017; Baraniuk 2016). Moreover, tari s imposed on te hni al equipment are rather negligible and in the range of approximately 1 per ent.
In total this se tor's rea tion is also rather hard to predi t on the basis of the low media overage and only few information. Furthermore, this se tor omprises of only 10 ompanies when ombining the FTSE 100 and the FTSE 250. Hen e, the inferen es from the graphi al assessment with regard to the hypothesis will underlie rm spe i movements, whi h thus annot be generalized to market behaviour.
The tele ommuni ations se tor omprises ompanies with regard to tele ommuni ation and related servi es (Thomson Reuters 2012). The turnover of this se tor amounted to ¿37.5 bn in 2015 (Of om 2016).
Currently UK orporations an operate in any European ountry under the treat on the European Union, whi h en ompasses the liberty to pro er servi es and the freedom of establishment. Assuming that the UK will not be a member in the single market after the negotiations in two years, these ompanies will forfeit this right. Vi e versa, the a ess for European ountries an also be limited (Maguire et al. 2016). Vodafone even on- sidered moving its headquarters to ontinental Europe (Williams 2016) O ial statisti s from the British government of this industry also suggest that the (wireless) tele ommu- ni ation market was very ompetitive (HHI=3495), whereby the wired tele ommuni ation a tivities was low in terms of market on entration (HHI=330) in 2015 (2015). Hen e, the ompetition in the UK ould de rease if admittan e of European tele ommuni ation rms is impeded. This might be pro table for British rms be ause oligopoly-like stru tures ould emerge, where higher pri e settings would be observable whi h were probably to the disadvantage to onsumers. Thus, the British government would have to evaluate these arguments.
As apparent, not a lot of information is available regarding this se tor wherefore the behaviour annot be pre- empted. The visual results for the hypothesis assessment from se tion 2.1 on industry level have to be treated again with aution based on the low number of rms in this se tor.
The utilities se tor is related to the energy se tor in their role of the distribution, enlarge- ment and maintenan e of energy lines or pipes (e.g. the power grid or gas pipes) from the energy suppliers to the onsumers. Next to power distributors also water-providing orporations are onstituted in this se tor (Thomson Reuters 2012). As su h produ ts satisfy the needs for everyday life these rms (regulated utilities) are mostly very insensi- tive to e onomi downturns (low y li ality), so do not o-move with the British business y le. However, the energy se tor in turn tends to y li ality due to the dependen y of ommodities with volatile pri es. The same reasoning applies for some independent power produ ers whi h also in line to be y li al. (Petro 2013). A ording to British govern- ment statisti s this se tor is also highly on entrated (2015). However, the ompetition will in my opinion only hardly be a e ted by the Brexit as no dire tly related impli ations an be anti ipated for this se tor.
On the basis of these arguments this se tor is expe ted to either not rea t or to rea t positively to the Brexit referendum based on the argumentation and due to the high interdependen e with the energy se tor where well-nigh the same rea tions were predi ted. Regarding the graphi al interpretation of the hypothesis with the distin tion of domesti and international portfolios is has to be noted that only very few ompanies are onstituted in both, the FTSE 100 and the FTSE 250 index. Hen e, rm spe i rea tions ould prevail general market rea tions.
Con luding it is worth mentioning that up to know the overall British e onomy is demonstrating quite some resilien e and ontrary to all the predi ted pessimisti appraisals, the e onomy is growing, although not at a fast pa e (Heath 2016; Elliott 09.15.2016)
In this se tion the methodologi al framework is worked o in order to obtain omprehen- sible and tra eable results. First, it is examined in the next se tion 3.1.1 whether the Brexit event triggered a stru tural break either in the ex hange rate and/or in the sto k markets. Then the di eren e-in-di eren es approa h is applied in order to quantify a tual losses British and European sto k markets in urred relative to other sto k markets. After that, the event study approa h is extensively elaborated in se tion 3.2.1. Subsequently, the various regressions are lari ed in se tion 3.2.2. Daily sto k pri es, ex hange rates and all rm spe i data for the various lassi ations and omputations were obtained from Thomson Reuters Datastream. All statisti al tests were exe uted in STATA.
In the next two se tions di erent methodologies are employed to evaluate whether the Brexit was a trigger for realignments on sto k and forex markets as well as to estimate a tual losses British and European sto k markets su ered in omparison to other sto k markets.
This se tion refers to the question whether the Brexit ballot was a game- hanger for British and other global sto k markets. In order to assess this question the Chow (1960) test is employed. Next to the sto k markets, also eventual stru tural breaks in the ex hange rates by evaluating the mean parameters are examined. Hen e, these tests su h as the Chow test and supplementary tests will be outlined in this se tion.
The assumption for the Chow test is simply that the break date is known As the Brexit vote and its rea tions an de nitely be attributed to a spe i date, this assumption is ful lled for the Chow test. Furthermore an endogenous stru tural break model whi h identi es the break date will be ondu ted for robustness. The Chow test simply tries to apture whether a times series has a alternating behaviour in two di erent time periods. Furthermore there are di erent ways to assess the signi an e of this test. One possibility is the F-test, where three regressions are ondu ted. The rst regression is basi ally the pooled regression in luding both time periods, whereas the other two are the regressions of the split samples. In turn, the resulting Residual Sum of Squares (RSS) of the three regressions are employed to ompute the F-statisti s (Watson and Teelu ksingh 2002). Here the following formula is utilised (see Watson and Teelu ksingh 2002, p.247):
illustration not visible in this excerpt
, where RSSp is the RSS of the pooled regression and RSS1 and RSS2 are the two residual sum of squares of the separated sample regressions. Furthermore, the n represents the total number of observations and k is the number of parameters (Watson and Teelu ksingh 2002).
The alternative way to al ulate the Chow test for the di erent periods of time is dire tly in one regression via the implementation of a dummy variable. In my thesis this se ond approa h is ultimately employed for onvenien e reasons. The dummy (D in the following regression) is zero for the rst time period and one for the se ond time range. By in orporating the dummy variable into the regressions a possible alternation in the inter ept is re e ted (β2), so a level e e t (Watson and Teelu ksingh 2002). Furthermore, the time variable is in luded (β1), whi h represents the slope over the whole sample. Then the dummy is intera ted with the time variable, whi h yields then the di eren e in the slope oe ients for both time periods (β3).6 Hen e the regression equation for sto k 6. regression was obtained from http://www.prin eton.edu/~otorres/TS101.pdf based on Chow (1960)
illustration not visible in this excerpt
Pt onstitutes the sto k index points (dependent variable) Subsequently the oe ients are undergone a Wald test to test whether the slopes and onstants are signi antly di ering before and after the event.
In a next step and the ex hange rates are examined for a stru tural break. For assessing the di eren e in the means two dummies are required, where one is zero before and one after the event and the se ond dummy is spe i ed vi e versa (D1 and D2). The respe tive means of the urren y pairs prior and after the ballot are obtained with the following regression simply by inserting both dummies into the regression:
illustration not visible in this excerpt
Pt refers to the sto k index points (dependent variable). In a next step the signi an e of the di eren e in the means needs to be assessed. For this purpose the t-test statisti s was al ulated. The respe tive test statisti is al ulated by the next following formula and assumes unequal varian e due to the expe ted in rease in volatility aused by the
illustration not visible in this excerpt
250 were negatively a e ted in the sense of omparatively lower pri e gains and/or level e e ts relative to the referen e sto k markets after the British ballot. In order to assess the signi an e of the e e ts a ontrol or referen e group whi h should not be a e ted by hanges in poli y. For this purpose, the three sto k markets, namely the S&P 500 (US), the Dow Jones Industrials Average (DJIA) (US) and the Nikkei (Japan) were sele ted on the basis of their ointegration to British and European sto ks markets. This impli ates that these sto k market evin e long-run relationships among ea h other. Next to the baseline group there is the so alled treatment group whi h is dire tly aggrieved to the hanges in government poli y. In order to evaluate resulting di eren es for the ontrol and the treatment group indu ed by the poli y one needs to separate the data into two periods very likely to the stru tural break approa hes. Thus, in total four samples are obtained. So, the ontrol as well as the treatment group before and after the parti ular event. This is ultimately attained by introdu ing again dummy variables, where one dummy (D1 in the following regression) separates the treatment (dummy=1) from the ontrol group (dummy=0). The se ond dummy (D2), just as in the Chow test, di erentiates the the sample at the break date. In the rst period both, the ontrol and the treatment group are onsidered to be highly resembling to ea h other (Watson and Teelu ksingh 2002). The β1 represents the hange in the mean of the treatment and the ontrol set in advan e of the parti ular event (Watson and Teelu ksingh 2002). Moreover, the δ0 resembles the expe ted hange for the ontrol group from prior to after the Brexit vote. (S he hter 2014). The regression equation a ording to Watson and Teelu ksingh (2002) an be written as:
Pi,t = β0 + β1D1 + δ0D2 + δ1D2 ∗ D1 + ǫi where i ∈ [C, T ] (5)
Pi,t onstitutes the sto k index points (dependent variable), C refers to the Control and T re e ts the treatment group. When intera ting both dummies with ea h other the estimate of interest, so the di eren e-in-di eren es estimate (δ1 in the previous regression) is obtained:
illustration not visible in this excerpt
The bar refers to the average sto k index points (P), the rst subs ript indi ates the time period (before, after) and the se ond subs ript refers to a liation either in the ontrol or treatment group.
This δ1 estimate sometimes also alled the average treatment e e t as it measures the impa t of the treatment group (Watson and Teelu ksingh 2002). More pre isely, the estimate re e ts the di eren e of the mean hanges for both groups from before to after the event (S he hter 2014). So, this estimate is negative in ase the treatment group forfeited relative to the ontrol group and vi e versa.
The DID is on e applied for a short-term period (50-50) so fty days prior and fty days after the Brexit referendum.
For the visual impa t of geographi business diversi ation and the hypothesis testing an event study was ondu ted. Here in the next se tion 3.2.1 the pro edure of an event study is stated for reating the domesti and the international portfolio for the respe tive indi es onsidered. In the last se tion 3.2.2 the regression is elaborated whi h ur ially relies on abnormal returns of the event study.
The event study initiated a revolution in the assessment of a wide range of nan ial and e onomi al o urren es on sto k pri es su h as hanges in a ounting rules, sto k splits or earnings announ ements (Binder 1998, p.111). Fama et al. (1969) as ertained for instan e, the e e ts of sto k split announ ements on its respe tive share pri es. Building on the papers by Fama et al. (1969) and Ball and Brown (1968), the basi event study methodology has only paltry been amended, still, plenty of additional extensions have been developed (Ma Kinlay 1997, p.14). Ma Kinlay 1997 formulated a typi al pro ess sequen e of an event study, whereby he also emphasized that there is no unique pro edure. At the outset one has to de ne the event of interest and demar ate the period around the event, whi h an be paraphrased altogether as the event window. Typi ally the event window surrounds some days prior and after the event in order to assure that the e e t is aptured. This is be ause the market may in orporate leaked information or some published information in advan e. On the other side, those spe i impli ations might take a while to pro ess after the a tual event o ured (Ma Kinlay 1997, p.14-15). However, there has to be a trade-o between the avoidan e of apturing other e e ts by expanding the event window too wide and not apturing the impa ts by urtailing the event window too narrowly. The estimation period in my setting is 277 trading days whi h is roughly one year (3rd of June 2015 10th of June 2016). The event window starts at 17th of June 2016 and ends four weeks later at the 15th of July 2016. Now the question arises how to assess whether an e e t has appeared and how to evaluate its signi an e. Binder (1998) argues that one requires a baseline for normal returns, whi h is in my work the market model. The author further notes that the market model aptures the ben hmark rate of returns very well and therefore I hose to employ this model. However, there are plenty more models su h as the Constant Mean Return Model, (Multi-)Fa tor Models, CAPM and Arbitrage Pri ing Theory (APT) with their respe tive reators/developers outlined in detail in Ma Kinlay (1997). In the market model des ribed by Binder (1998) the baseline is gathered as the relationship between the return of se urity i in time period t (Ri,t) and its respe tive sto k market index for the same interval t (Rm,t). This is basi ally the so alled estimation period . All the following equations are gathered from Ma Kinlay 1997. Formally, this an be written as follows:
illustration not visible in this excerpt
This formula is very alike to the CAPM, though, the CAPM gauges ex ess returns, so returns above the risk free rate (rf). Simply by subtra ting the rf from the sto k and market return would lead to the equivalen e of the CAPM Beta with this slope oe ient of the regression. In addition, the inter ept needs to be the same as the risk free rate (Ma Kinlay 1997).
illustration not visible in this excerpt
Figure 1: Timeline for an event study (Ma Kinlay 1997)
The regression is ondu ted with data in the estimation period until the event window. So, from τ = T0 + 1 until τ = T1. The event window starts here at τ = T1 + 1 and ends at τ = T2. If rea tions are assessed to take a long time one an also separately de ne a post-event window (where appli able), as seen in the previous gure 1. However, a post-event window is not essential in my thesis. Subsequently, one basi ally opposes the realized ex post returns with the predi ted values from the previous regression. Thereby, one an then quantify the magnitude of the so alled Abnormal Returns (ARs) simply by subtra ting the predi ted values (from equation 6; Ri,t) from the a tual returns (Ri,t) of the se urity (Ma Kinlay 1997). Formally, this is the subsequent equation:
illustration not visible in this excerpt
Here the ARs are the residuals of the market model in an out of sample predi tion.
Under the null hypothesis (H0; no impa t of event on returns) the ARs should be alto- gether normally distributed [illustration not visible in this excerpt] dependent on the market returns (see Ma Kinlay 1997, p.21). In the next step the ARs are initially either averaged a ross se urities and then aggregated over time or vi e versa. Both approa hes yield of ourse the same results. However, I prefer the pro edure where it is rst averaged and then ag- gregated over time on the basis of graphi al advantages in order to illustrate the results. Hen e, at the outset the Average Abnormal Returns (AARs) are al ulated a ording to the formula:
illustration not visible in this excerpt
One has the opportunity to display the average of the abnormal share returns with this pro edure. In turn, the AARs are added up over various ombinations of multiple periods from τ1 to τ2 where T1 < τ1 − τ2 − T2 (Ma Kinlay 1997, p.21). This yields us the Cumulative Average Abnormal Returns (CAARs).
illustration not visible in this excerpt
Now that we know the magnitude of ARs, AARs and CAARs we have to assess whether those exhibit statisti al signi an e or not. Therefore, one null hypothesis (H0) is that the returns are standard normal distributed with zero mean and varian e of 1. In mathemati al terms the test statisti for the signi an e of the abnormal returns to be unequal to zero an be formulated as follows:
illustration not visible in this excerpt
The same test statisti s an be applied with AARs and CAARs and it simply tests whether all the ARs, AARs and CAARs are signi ant di erent from zero. However, further tests are required in my thesis. For instan e, a t-test for assessing the signi an e between the various returns (ARs, AARs and CAARs) of both, the domesti and the international portfolio is required. At the example of multinationality this implies that initially the dataset is separated with a dummy in order to di erentiate between domesti and multinational ompanies. A rm is ategorized as international when foreign sales ex eed 10% of total sales of the ve year average. Afterwards, the event study is ondu ted and on luded with the aforementioned statisti al tests twi e for ea h portfolio.
This se tion refers to the assessment of the hypothesis that the degree of rm-level internationalization positively a e ted the abnormal returns on British sto k markets. To rephrase it on other words: The higher (lower) international sales, the less (more) severe the respe tive sto ks rea ted to the Brexit ballot.
In order to assess and quantify the e e t of rm level internationalization on abnormal and umulative abnormal returns a general OLS regression is utilised. For the degree of internationalization the latest available yearly foreign sales in per ent of total sales for ea h respe tive rm are employed. This is ontrary to the regressions of Oehler et al. (2017) whi h use the domesti sales in per ent of total sales (hen e a negative relationship to abnormal returns). My proxy for multinationality is therefore assumed to be positively related to the abnormal and umulative returns. As remarked by Allen and Pantzalis (1996, p.636) every multinational group has its unique parti ularities with regard to their individual subsidiary networks and stru tures and/or the number of ountries the rm is operating. Nevertheless, it is not possible to orre t for rm xed e e ts on the basis of limits in the evaluation possibilities by Stata (the program in whi h the whole analysis for the master thesis was ondu ted). However, this problem an be ir umvented by introdu ing an industry dummy ve tor (with ten dummies; DI) and thus, orre ting for industry spe i xed e e ts. Therefore the TRBC is applied where the Consumer Cy li als bran h serves as a referen e for the other industries and is therefore the model inter ept in the regressions, where ea h other industry inter ept is the relative di eren e to the baseline. Thereby, impli itly another issue is bypassed, as foreign sales also depend on the respe tive se tor a rm is asso iated. With regard to the literature review, some spe ial hara teristi s of national and international were mentioned. One of them implied that international sales might depend on the ompany size (see for instan e Riahi-Belkaoui 1999; Mayer and Ottaviano 2008; Altomonte et al. 2013). Therfore it is orre ted for the rm size by means of the natural logarithmi market apitalization of ea h ompany (ln(MCi)). The natural logarithm is applied in order to adjust the otherwise highly skewed distribution of rm sizes. The next spe i is the varying debt ratio of domesti and transnational ompanies, whi h is usually higher for former one, as outlined in more detail in se tion 2.1. Thus, nan ial leverage is also in orporated into the regressions. Hen e, I approximated this measure by dividing long-term debt plus the market value of equity over the long term debt of the rm. It was followed Akhtar and Oliver (2009) who employed the same proxy for leverage as well as Burgman (1996) and Chkir and Cosset (2001) and very similar to Pani (2008) who utilised the (long-term) debt-equity ratio.
The regression equation looks as follows:
illustration not visible in this excerpt
The regressions are in turn exe uted in the ross-se tion on index level on the 24th of June 2016 (AR[0℄). For the AR[0℄ the general OLS-regression (xi: reg in Stata for in luding the dummy) is employed. Furthermore, the CAR[0,2℄ and CAR[0,5℄ are also investigated in the ross-se tion, however, ontrary to Oehler et al. (2017) whi h in lude the day prior to the 24th of June 2016, where the graphs indi ate a negative relationship of
rm-level internationalization due to the polls whi h suggested a tenden y for the UK to not withdraw from the EU. This would however debilitate the e e t of geographi business diversi ation on the CARs. For this purpose, a robustness he k will be ondu ted whether foreign sales negatively a e ted the umulative abnormal returns before ballot, so for CARs between the 17th and the 23rd of June 2016 (CAR[-5,-1℄). These three and six day CARs are added for robustness and assessing the persisten e of the e e t, also on the index level.
On the se tor level basi ally the same pro edure is applied in order to assess the po- tentially mitigating e e t of international sales at the Brexit ballot, however, the dummy is of ourse omitted in this regression. Furthermore, also the assumption of the E ient Market Hypothesis (EMH) by Fama (1970) must be relaxed in order to examine the data of tardy (industry) market rea tions. Thereby, the possibility of se tor spe i understate- ment/exaggeration of sto k returns an be s rutinised (Ramiah et al. 2017). Therefore, the two portfolio spe i rea tions over time for the FTSE 100 and FTSE 250 are assessed starting from AAR to the three day CAAR[0,2℄ and the six-day CAAR[0,5].
The empiri al se tion is stru tured as follows. At the outset it is assessed whether the Brexit referendum had material impli ations on global sto k markets as well as foreign ex hange markets. Thereby the stru tural break methodology is applied. Subsequently, the di eren e-in-di eren e approa h is ondu ted to quantify the losses the British and European sto k indi es had to a ept. The se ond major part of this thesis deals with the evaluation of the multinationality hypothesis on index and industry level, whereby initially an event study is ondu ted where two portfolios are onstru ted for rms international rms and enterprises that operate solely in the UK. This is followed by a statisti al analysis with respe t to the hypothesis on e on the index and on e on the se tor level.
In this se tion it is evaluated whether the Brexit referendum aused a realignment on sto k markets as well as on forex markets. Therefore, the Chow test is applied for sto k markets and the mean test for urren y markets. By means of the di eren e-in-di eren es approa h the de fa to losses for British and European sto k indi es are quanti ed relative to ointegrated overseas sto k markets.
Hen e, the task for the DID approa h was at the outset to nd ointegrated sto k mar- kets where the rea tion to the Brexit was somehow limited and exiguous relative to British and European sto k markets. Cointegration impli ates a long-term inter onne tedness of sto k markets. In my opinion this enhan es the signi an e of the results. Otherwise, when gauging the di eren es of not ointegrated sto k markets, any possible out ome
ould be observable and hen e, the results would hardly be interpretable. Consequently, based on the following existing literature the S&P 500, the DJIA and the Japanese Nikkei emerged to well-suited referen e markets. A study by Khan (2011) identi es interde- penden ies between the British FTSE 100 and the S&P500. The results by Floros (2005) supports this relationship. Furthermore, the author is able to as ertain a link between the British FTSE 100 and the Japanese Nikkei. Arshanapalli and Doukas (1993) for instan e nd a long-term relationship among UK, German, Fren h and Japanese lead indi es. Ca- porale et al. (2016) as ertain a linkage between the S&P500 and the EuroStoxx 50. In addition, Shahzad et al. (2014) are able to additionally link the UK sto k market (FTSE 100) with the latter two mentioned. Further, Boubaker and Jouini (2014) re ognise a dire t long-term inter onne tion between the S&P500 and the EuroStoxx 600. These ndings are also supported and enhan ed by Shahzad et al. (2016) whi h also link the S&P 500, the EuroStoxx 600 and the FTSE 100 sto k index. Moreover, Masih and Masih (2001) nd signi ant interdependen ies among Japanese, European (UK and Germany) and US-Ameri an sto k markets. On the basis of no more dire t information on a rela- tionship between the EuroStoxx 600 and the Japanese Nikkei index it is assumed for the thesis that both are linked, based on the ross- onne tion of the other sto k markets to ea h other. One of the most important sto k indi es worldwide, the DJIA, has merely literature regarding sto k market integration around the world as mostly the S&P 500 is taken into onsideration by most a ademi s. One of these rare studies is from Ozdemir and Cakan (2007) who identify that the DJIA Granger aused the UK, Japan and Fran e, where in turn only the UK Granger auses the US sto k index. Another study by Ozdemir (2009) establishes a linkage between the US, the UK, Germany and Fran e. Still, the Dow Jones in my opinion an be assumed to be ointegrated (at least unidire tional) with most of the sto k markets worldwide as it is THE world's nan ial hub. For a detailed list of the literature regarding ointegration tests for plenty of ountry ombinations and the em- ployed models in the last two de ades see Shahzad et al. (2014). However, unfortunately no literature was found between FTSE 250 orporations and US/Japanese markets. For this purpose, it is assumed that the FTSE 250 ointegrates with these 3 indi es on the basis of the prevailing strong link to the FTSE 100. Thus, a ording to the previously mentioned studies the Nikkei, the SP500 as well as the DJIA were onsidered as referen es in the following di eren e-in-di eren es method. In addition those markets will also be examined for stru tural breaks in their time series of pri es in the subsequent se tion.
This se tion elaborates the question whether the Brexit was a game- hanger for global sto k and ex hange rate markets. It will be assessed for daily data for roughly three years whether there was stru tural break by means of the Chow test in the sto k markets, as sto k markets usually follow a trend. The stru tural break approa h in means is exe uted for the ex hange rates for the same time-period as for sto k markets (about three year time period as before) and a shorter time period, as ex hange rates typi ally exhibit stationarity throughout time. For robustness purposes, also longer time periods are onsidered. In addition, a re ursive stru tural break test model is employed for sto k and forex markets in order to determine the break date endogenously.
Table 1: Chow Stru tural Break Test for Indi es
illustration not visible in this excerpt
Notes: The numbers represent the p values with the null hypothesis that the slopes and the onstants separately as well as both ombined stay the same. The se ond half of the table refers to ex hange rate adjusted sto k pri es, denominated in Euros. 500-220 represents the days before and after the event. Plus or minus in front of the p values indi ates the hange of the slope from prior to after the event, hen e, either positively (+) or negatively(-).
Table 1 refers to the results of the Chow-test whereby the p-values of the Wald test are stated. All of them are signi ant at the 0.1% level, with the ex eption of the shift in The two µs represent the means, the two σs refer to the respe tive standard deviations and the n1 and n2 represent the observations of the respe tive two samples. For the sturdiness in this se tion a supremum Wald test by Andrews (1993), based on the proposition of by Quandt (1960), was applied, whi h identi es the date of the stru tural break in the dataset. This test simply sear hes for the maximum value of iterated Wald tests within a set of break dates (Vogelsang 1997). The test was exe uted with a pre-spe i ed program (estat sbsingle) in Stata.
The Di eren e-in-Di eren es DID method is in parti ular appropriate when an exogenous event (su h as the Brexit) results in a hange of the politi al environment or the ourse of a government. Hen e, this approa h was employed to see whether the FTSE 100 & 7. t-test statisti s formula was obtained from http://www.stata. om/manuals13/rttest.pdf based on Wel h (1938).
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