The sectoral effects of Brexit on the stock and CDS market in Britain in short-term

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The sectoral effects of Brexit on the stock and CDS

market in Britain in short-term

Author: Qinning Shan

Student number: 11107340 Thesis supervisor: Doettling, Robin Finish date: June 2018 University of Amsterdam MSc Economics & Business

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STATEMENT OF ORIGINALITY

I declare that I have finished the paper by myself, and all the sources used in the document are mentioned.

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ABSTRACT

The paper assesses the effects of the Brexit referendum on the stock market and CDS market in Britain for various sectors. Based on the data from WRDS and Datastream, I apply the event study methodology to study whether these markets are affected by the Brexit announcement through testing the significance of cumulative abnormal return (CARs) and cumulative abnormal CDS spread changes (CASs) for each sector in Britain. The results indicate that Brexit would have various sectoral effects, even though most sectors show negative CARs and positive CASs, which means both stock and CDS markets are negatively affected. Consistent to the previous studies, the banking and other financial institutions sectors are affected most severely by the Brexit.

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CHAPTER 1 Introduction

The effects of Britain’s decision to leave the European Union, which can also be called the Brexit, on the United Kingdom’s economy has generated a heated debate before the vote and it is still being discussed, particularly because the type of the exit UK would get will be decided by negotiation with the EU. The referendum on Britain's membership of the European Union will bring advantages and disadvantages to the UK. The effects in the short term and the long term might be different.

Proponents of leaving the EU stated that immigration from the European Union was harmful to Britain-born workers, especially for jobs, wages and access to public services aspects (Jonathan Portes and Giuseppe Forte, 2017). Besides, Minford's (2016) assessed that the United Kingdom European Union membership referendum would have substantial adverse effects on trading. An argument used to support the Brexit was that the United Kingdom could decrease the cost of imported goods since the tariffs on imports into Britain is removed, which would benefit Britain (Swati Dhingra, Gianmarco Ottaviano, Thomas Sampson and John Van Reenen, 2016). In parallel, Britain businesses would become more competitive since the companies would no longer need to conform to the costly and unified regulations. In contrast, Dhingra et al. (2016) claimed that Brexit had been estimated as a negative signal for the development of the Britain economy uniformly. The UK GDP would drop by between 1.1 percent and 3.1 percent due to lower trade with the EU. The less skilled immigration, reduced foreign direct investment, and the dynamic consequences of lower trade could also cause substantial losses. Furthermore, Britain would not participate in deciding the rules of the single market even if it can be fully accessible to the single market following the referendum.

To sum up, the economic consequences of the Brexit are complicated. However, lower contributions to the EU budget is likely to benefit the Britain economy less than the cost from reduced integration with EU countries.

Most of the existing studies examined the economic impacts of Brexit. Some researchers also studied some additional impacts, such as foreign investment (Dhingra et al., 2016) and immigration (Ebell et al.,2016; Dhingra et al., 2016). However, very little studies paid

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attention to how those impacts would vary across different sectors of the British economy. In this paper, I assess the effects on various sectors to observe how the stock prices of distinct sectors react in the short term following 24 June, on which the Brexit referendum was announced. Vikash Ramiaha, Huy N. A. Phama and Imad Moosa (2017) claimed that sectors reacted differently after the Brexit, although most sectoral effects were negative.

In addition, the Brexit would bring substantial political uncertainty. To measure the effects of political uncertainty, we can use credit default swaps (CDS) spreads. The Credit Default Swap (CDS) is a financial swap agreement, which provided "insurance" to protect the financial institutions or companies from a credit event that probably harm the value of them (Berndt et al. 2007). Hence, it was often used as a proper indicator of the credit risk (Forte and Lovreta, 2009). According to a lot of recent researches, the credit default swap contracts played an important role in the financial crisis. Although they did not contribute to the causes of the crisis, the credit default swap contracts were associated with spread distress among the financial institutions (Acharya and Johnson 2007). However, the existing studies did not assess the effects of Brexit on the Credit Default Swap. There was a little evidence on the influences on individual firm’s credit risk. Hence, I study the impacts of Brexit on the CDS market for various sectors in addition to the stock market in Britain.

Overall, I will make a contribution to the study on Brexit referendum effects in the following ways. The first research question is whether Brexit has negative and significant short-term effects on the stock market in all sectors in the UK. The second one is whether Brexit referendum has positive and statistically significant short-run effects on CDS spreads in every sector in Britain. Since long-term effects are based on the forecast, I focus on the short-term effects. For these purposes, I empirically investigate the changes of the stock market and the CDS market before and after the Brexit announcement for each sector in Britain. I apply the event study methodology and calculate the abnormal return, and the abnormal CDS spread changes. By testing the significance of the cumulative abnormal returns and cumulative abnormal CDS spread changes for all sectors in Britain, the effects of Britain on the stock market and CDS market for each sector could be defined. The daily series data including stock returns and CDS spread are downloaded from WRDS and Datastream data sets. The findings show that the bank and other financial institutions sectors are affected most severely by the Brexit. The referendum leads to negative impacts on cumulative abnormal return, and positive effects on cumulative abnormal CDS spread changes for these two sectors. It means the significant decrease of stock return and substantial increase of credit risk in these two

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sectors after the Brexit announcement, which are consistent with the previous researches' results.

The rest of the paper is structured as follows. Chapter 2 discusses the leading theories in the existing literature and provides further comparisons to existing studies. Chapter 3 identifies the methodology, which shows the model used for the research and how to analyze data. Chapter 4 lists the sources of data and shows the general picture of data statistics. Chapter 5 discusses the final results and compares them with the existing literature’s conclusion. It also gives economic meaning to the results. Chapter 6 presents the robustness checks of the model used. Finally, Chapter 7 provides a conclusion.

CHAPTER 2 Literature Review

2.1 Political uncertainty and the stock market:

Many prior researchers showed that the referendum on Britain's European Union membership could be considered as a large change in the government policy. Such political changes are commonly related to the decreasing share prices, especially when the uncertainty of the policy is drastic. Lubos Pastor and Pietro Veronesi (2012) documented the evidence that stock prices would drop around the announcement of a change policy in general. The reduction of the stock price should be considerable when the uncertainty surrounding government policy is significant. The effects would also be significant when the policy change was followed by the downturn of economy. Therefore, the political uncertainty should increase the volatilities of the stocks as well.

2.1.1 Return:

Marie-Claude Beaulieu et al. (2006) claimed the effects of the political uncertainty result from the 1995 Quebec referendum on the Quebec companies’ stock returns in the short term. The results revealed significant evidence that the referendum had a positive influence on stock returns in the short run. Also, they noted that the short-term Quebec firms’ stock returns would be influenced by the political uncertainty significantly when the financial markets could not anticipate the policy changes. Besides, the firms exposed to political risk mostly

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were affected by the referendum’s uncertainty on portfolio returns more than the companies which are exposed to political risk least.

2.1.2 Volatility:

Frankie Chaua, Rataporn Deesomsaka, Jun Wang (2013) have indicated the impacts of civil revolt in the Arab states. They also studied the relationship between related political uncertainty and the stock market’s volatility in the Middle East and North Africa region. Their results indicated that the political uncertainty had impacts on Middle East and North Africa stock markets’ volatility, especially for the Islamic indexes. The results proved the previous studies and were robust to model specifications. For instance, Bailey and Chung (1995) noted that the financial volatility was driven by political uncertainty in other stock markets.

Thus, the empirical evidence suggested that not only the common financial and economic factors contributed to the financial asset price movement, but also the political events affected the volatility of stock markets (Gilpin, 2011).

2.2 Political uncertainty and CDS spread:

Jinyu Liua, Rui Zhong (2017) claimed that the firm’s credit risk was positively related to the political uncertainty which was caused by the national election. They chose the companies with single-name credit default swap (CDS) contracts from thirty nations, which was a large sample for testing.

The uncertainty caused by incompetent policy-making are harmful to the firms and their clients, possibly through various channels. For example, political risks would cause diminished company’s investments and output according to Julio and Yook’s research (2012). Also, Alesina and Tabellini (1989) claimed that the political uncertainty would lead to the declined appearance of capital flight and undermine customer confidence. More importantly, the long-term profit growth of firms, which is combined with a high level of systematic risk, may decline from the perspective of CDS market (Abaidoo & Kwenin, 2013; Blanchard, 1981; Shah, 1984). Thus, it is sensible to conjecture that the credit default swaps spreads can be

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negatively affected by the political uncertainty according to the empirical evidence. (Tomasz Piotr Wisniewski and Brendan John Lambe, 2015)

Gerardo Manzo (2012) divided the CDS spread into two parts. They are the credit risk premium, which can be also called the distress risk, and the default risk which can be also called the jump-to-default risk. The credit risk premium provides the compensation to the investors for enduring the risk caused by the unanticipated changes in the default intensity. And the default risk catches the abrupt (negative) jump in the underlying bond value in the situation of default. These results showed that the political uncertainty would cause significant impacts on the sovereign credit risk. In particular, 10% rise in the degree of political uncertainty caused a significant and positive variation in both the distress risk and the jump-to-default risk of around 3%. Gerardo Manzo (2012) concluded that political uncertainty contributed significantly to increasing the investors' risk aversion, thus it could be viewed as one of the primary driving factors of the European credit market. However, in practice, the policymakers would respond accordingly to the convulsion in the CDS market only when the risk of default was severe, rather than the subtle changes of credit risk premia. 2.3 Brexit and the stock market in Britain:

According to Ansgar Belke et al. (2018), the policy uncertainty caused by the Brexit will keep causing volatility in critical financial markets and is expected to harm the economic situation in both Britain and the EU. Their panel estimations indicated the conclusion that a rise in the Brexit likelihood would have significant adverse impacts on stock returns.

What’s more, Andreas Oehler et al. (2017) applied an event study to determine abnormal stock returns after the Brexit referendum in the short run. They indicated that the companies with more home sales would have more negative abnormal stock returns than the ones with higher proportions of sales abroad, which emphasized the importance of international diversification.

2.4 Brexit and CDS market in Britain:

The largest increase in CDS spreads in Britain was found in the Ansgar Belke, Irina Dubova and Thomas Osowski’s analysis in 2018. The finding indicated that Brexit would influence

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the creditworthiness of Britain. There was the significant and positive impact for Britain according to the sovereign credit risk’s consequences.

Moreover, Jamal Bouoiyour, Refk Selmi (2018) firstly offered the empirical evidence on the influence of the uncertainty caused by Britain’s EU membership referendum on Britain and European Union. The prices of CDS across Britain showed a more significant rising compared to their past behaviors. In addition, the uncertainty surrounding the Brexit event undermined the creditworthiness in both Britain and the other European countries. Also, Britain is the most potent "net transmitter of volatility".

2.5 Sectoral effects of Brexit:

The Brexit has varying sectoral effects while all industries face increasing uncertainty. According to Jamal Bouoiyoura and Refk Selmi (2018), the reactions of sectors such as real estate and financial services sectors to the referendum event were more significant than the responses of sectors such as oil, gas and pharmaceuticals sectors. They indicated that there were three main reasons for the adverse effects of Brexit on UK industries -- losing the European passport to start the businesses, lacking access to European Union’s Research and Development funds and absence of the experienced workers.

2.5.1 Banks and financial institutions

If UK financial institutions lose their financial service passport rights after the future negotiations between the EU and the UK, the referendum on Britain’s EU membership may result in significant changes in banks and financial institutions (Miethe, Jakob; Pothier, David, 2016).

‘Financial services passport’ is a special legal regime operates within the EU. It allows UK-based institutions to do business with the rest of the European Union even if they do not have a branch there. For example, the USA’ bank which is located in the UK can do the business with EU without setting up a branch there (John Armour, 2017). If the banks lose these rights, they would only have to build a physical location in the EU to deal with the business, which is mostly still done in London. However, there is also the possibility that Britain would lose massive amounts of business to the European Union because of lacking the financial services

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passport rights. It is reasonable to expect Britain’s exporting financial services to the European Union could drop by half, or around £10 billion, without passporting rights (Miethe and Pothier, 2016). The dependence of the United Kingdom on exporting financial services to the European Union would also undermine Britain's bargaining position in the future consulting with the European Union (Miethe and Pothier, 2016).

In addition, Portes and Forte (2017) found that the financial services sector depended on European Union law because of the free movement of employees. If the range of candidates is wide enough, it becomes more convenient to hire the skilled workers and to develop the human capital for the company. The immigration restrictions with Britain after the Brexit would limit such recruitment. The United Kingdom government is likely to adopt a regime that promotes the access for professionals in the financial sector, but this will possibly still lead to additional processing costs for firms (Armour, J., Mayer, C., and Polo, A., 2017). Dirk Schiereck, Florian Kiesel and Sascha Kolaric (2016) analyzed the effects of Brexit announcement on June 23, 2016, on the stock and the CDS market of the Britain banks. It showed that the UK's EU membership referendum affected the UK banks severely. On the one hand, the Brexit announcement led to significant declining of the share price. On the other hand, the UK banks' CDS spreads indicated a significant growth after the announcement of the Brexit referendum.

Hence, I estimate that Brexit referendum would have significant negative effects on financial institutions in Britain as indicated by negative cumulative abnormal return (CARs) and positive cumulative abnormal CDS spread changes (CASCs).

2.5.2 Retail and Consumer goods:

Since EU represents 47% of Britain's manufacturing exports and 54% of Britain's imports are currently shipped from EU, the impacts of the Brexit on the retail and consumer sectors in Britain are anticipated to be large.

Although the final results of the Brexit concerning the retail and consumer goods sectors rely on the treaties which would be decided by the UK and the European Union, we can find some

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immediate impacts following the EU Referendum event. Firstly, the businesses are now freely between Britain and the European Union, without any duties and quotas. Britain currently benefits from less administrative stress, simplified customs procedures and free trading with the EU. However, there would be much more uncertainties on these arrangements if the Brexit happens in the future. In addition, Brexit is likely to have an effect on the free movement of labor from the European Union into Britain. It could cause more difficulties for retailers to recruit employees in major cities, warehouses, and distribution centers, primarily as these jobs filled by migrant labor. Thirdly, the Brexit would cause cheaper exports and more expensive imports to Britain immediately. That is because the value of the pound fell significantly in the first few days following Brexit. Hence, the goods imported by most retail and consumer business become more expensive to purchase, which would lead to negative effects on pricing and consumer spending (Richard Welfare, Susanne Karow and Kelly Hardy, 2016). Therefore, I expect that Brexit would have disruptive effects on retail and consumer goods sectors.

2.5.3 Electric Power, Energy, and gas distribution:

The sources of energy in Britain include the primary and refined liquid fuels, coal, natural gas, and electricity supply. They offer the services for heating, power, and transportation. Also, energy accounts for 6% of total UK tax revenue, which is economically significant (Michael G. Pollitt, 2017).

Since Britain is a net importer of energy, petroleum, gas, coal, and electricity, the energy sector would be affected by the devaluation of the pound. The weaker pound would increase the energy cost to Britain immediately. Although the value loss for the pound sterling is uncertain, the current loss is large enough for impacts to satisfy the supply chain (Michael G. Pollitt, 2017).

However, there are also some benefits showed by leaving the European Union in the energy industry, such as more rational allowance system, the smarter meter roll-out and more further cooperation with the countries outside Europe such as North America. Hence, it seems likely that Britain would motivate a new round of energy market reforms throughout the world after being divorced from the European Union (Michael G. Pollitt, 2017).

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Considering the costs and opportunities, the effects of the Brexit referendum on electric power, the energy company, and gas distribution are remained to be studied.

2.5.4 Services:

The service sector plays a more and more crucial role in the Britain economy. It is not only the source of job creation but also the main engine of export demand. The ONS (Office for National Statistics) data showed that the ratio of services to total Britain exports rose rapidly from 28% to 41% between 1997 and 2013, mainly in key service activities, such as the business and the financial services. Also, Britain's entering the export markets for the service sector is vital for future job creation, especially in the digital and creative industries. These are United Kingdom priorities for extending the single market. However, if Britain leaves, the progress in this direction would lose momentum (Iain Begg and Fabian Mushövel, 2016). Therefore, I expect that Brexit would have negative impacts on retail and consumer goods sectors.

2.5.5 Manufacturing:

According to ONS data, manufacturing occupies almost 10% of Britain’s GDP. And there are more than half of all manufactured exports shipped to the European Union currently. Brexit would probably increase the cost of doing business and the hiring and retention of capable employees. However, it will also create some advantages. For example, the depreciation of the pound enables the price of exports more competitive. In conclusion, the impacts of Brexit on the manufacturing sector is uncertain (Deloitte, 2017).

2.5.6 Transportation:

Brexit would result in uncertain regulation, strong borders and the end to free movement of labor. They would lead to harmful effects on business operations of transportation firms (Karen Larbey and Chris Bhatt., 2017). As a member of the EU, Britain benefits from the wide freedom of regional trade. But it is likely to be curbed by the Brexit. In addition, the Britain transportation sector would face a massive challenge of lacking available technology talent since the free movement of labor would be tightened in the coming years. Trucking would be disruptively affected most among the transportation sectors. The drivers of heavy

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goods vehicles from the European Union accounts for approximately 20 per cent of the total trucking drivers in Britain. Reducing the sector's recruitment options would weaken its ability to serve the economy. Reducing in supply would raise trucking costs for manufacturers (Karen Larbey and Chris Bhatt., 2017).

However, increasing cooperation with the rest of the world and self-regulation may also provide some benefits. The government’s white paper presents that the government will improve the productivity and enhance job creation by increasing trade and opening markets to attract the world's greatest companies to cooperate with the United Kingdom and to invest in Britain. If this can be realized, transportation companies will be accessible to new markets and new paths to growth. What’s more, increased autonomy over regulation means UK transportation companies may pay more attention to the regulatory process. This could improve the effectiveness of the operating business (Karen Larbey and Chris Bhatt., 2017). Hence, the impacts of Brexit on transportation sector remains to be studied.

Chapter 3. methodology

To analyze how stock return and CDS spreads react to Brexit, I apply an event study methodology. I concentrate my research on the Britain referendum and study the impacts of the United Kingdom’s decision to leave the European Union on companies’ share returns and CDS spreads in various sectors. I consider June 24, 2016 as the event day, on which the final consequence of the Brexit referendum was announced.

Event window: [-1; +1], [-2; +2] [-5; +5] [-10; +10] Estimation window: [-71, -11]

I define the time interval [-n, n] as the period, which lasts from n days before the Brexit announcement to n days after the announcement where n must be positive. Hence, [-1,1] is the time interval from 1 day before the Brexit announcement to 1 day after the announcement and [-5, 5] is the time interval from 5 days before the referendum announcement to 5 days after the Brexit referendum and so on.

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I do the event study for stock returns’ reaction to Brexit by WRDS. The stock returns are from London Share Price Database (LSPD) database. This Tool uses Market Adjusted Model (MAR) as the risk model. The formula is , in which is the security i’s return at time t, and is the return of market at time t. According to the formula, the abnormal return (AR) is viewed as the difference between the country market return and the daily stock return. In addition, I calculate the cumulative abnormal stock return (CAR) by adding the abnormal return of daily stock over the event windows for each firm.

After getting the abnormal return of 670 firms, I classify the companies into 34 sectors. For each sector, I calculate the mean abnormal return and mean cumulative return over the event window, which are defined as AAR and CAAR. Then, I do the t-test for abnormal return and cumulative abnormal return over various event windows. The null hypothesis to be tested is: E (AR) = 0 and E (CAR) = 0. The alternative hypothesis is: E (AR) < 0 and E (CAR) < 0, which is in accordance with my assumption that the stock return market in Britain would be negatively affected by Brexit in all sectors. The t-statistic is constructed as: TS= and TS= , in which N means the number of companies in the sector and s means the standard deviation of AR and CAR. I compared the p-value to 1% and 5% for each sector to check the significance level of effects.

In table 3, CARn means the cumulative abnormal returns over the event window [-n, n]. 3.2 CDS

Measuring the abnormal returns is a general way to study the effects of events on security prices in many event studies, such as stock and bond event analysis. In the event study for CDS market, the abnormal spread changes are calculated for investigating the influences of an event on a company's default risk. The change of CDS spread quantifies the change in the premium from default swap contracts which are newly issued. The default swap contracts also should have the same maturity (Christian Andres, Andre Betzer and Markus Doumet, 2013). Hull et al. (2014), Norden et al. (2014), and Galil et al. (2011) introduced the changes in CDS spread and used it in their studies. The daily spread change is calculated as the day T’s CDS spread minus the day T-1’s CDS spread. The formula is:

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As in the stock market, an abnormal change of CDS spread can be considered as the difference between the real change of CDS spread and the normal change of CDS spread. Here, I use the mean-adjusted model to measure the normal spread change. It is firstly discussed by Brown and Warner (1985) and is applied for analyzing the stock returns. The model used the arithmetic mean of real returns during the estimation period as the normal return. The abnormal return of firm i at time T is calculated as the real return on T minus the average return during the estimation period. In 1984, Handjinicolaou and Kalay used the same model for bonds.

The mean-adjusted model is viewed as the most straightforward normal return (or normal spread change) model. However, Brown and Warner (1985) indicated the results of event analysis gained from the mean-adjusted model were almost the same to the event studies which relied on more complicated models such as the capital asset pricing model (CAPM) and the market model. What's more, Christian Andres, Andre Betzer and Markus Doumet (2013) extended the findings of Brown and Warner (1985) and indicated that the simple mean-adjusted approach even performs better than the competing normal spread change models such as the matching portfolio approach and the market model when employing daily CDS data. George Handjinicolaou and Avner Kalay (1983) concluded that the mean-adjusted returns model had two main benefits. On the one hand, it removes the problems caused by selecting a market portfolio’s proxy. On the other hand, it keeps off the potential biases of using daily bond prices to estimate the market model. Therefore, the simple mean-adjusted approach is recommended to quantify the abnormal spread change since it leads to more reasonable results.

To apply the event study methodology to CDS market, I define the estimation period firstly, which is 71 days before the event day to 11 days before Brexit announcement. Then I calculate the average spread change of company i within the estimation period [-71, -11] to measure the CDS normal return. The formula is:

Assuming that the normal spread is various among the firms but keeps the same over time, I can calculate the abnormal spread change of company i at time T as the formula below:

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It measures how abnormal spreads change after the Brexit relative to the 60 days before. Intuitively, if the default risk of Britain companies has increased via Brexit, then this measure should be positive. This means the negative effects of Brexit on the CDS market. I also measure the cumulative abnormal CDS spread change (CAS) for each firm by calculating the sum of daily abnormal spread changes (AS) over the event window. In table 5, CASn means the cumulative abnormal CDS spread changes over the event window [-n, n].

According to Datastream, there are 10 sectors. They are Banks, Consumer goods, Electric power, Energy company, Gas distribution, Manufacturing, Other financials, Service company, Telephone, and Transportation sector. However, there is only one active company in the electric power, energy company, and gas distribution sectors respectively. So, I combine the firms in these three sectors to the sector called Energy, Electric and Gas sector. For each sector, I do the t-test for abnormal spread changes and cumulative abnormal spread changes. The null hypothesis to be tested is: E (ASi) = 0 and E (CASi)=0. The alternative hypothesis is: E (ASi) > 0 and E (CASi) > 0, which is consistent with the proposition that Brexit leads to increasing CDS spreads in every sector in Britain. The alternative hypothesis also means that Brexit has adverse effects on the CDS market. Also, the p-value is used to quantify the idea of the statistical significance of the evidence.

In table 4, the number in the first column (n) means n business days after the Brexit referendum event. Thus, -2 means the 2 days before the Brexit referendum announcement; 1 means 1 day after the announcement; and so on.

When there was no observation on the CDS spread available for a day, I used the next observation as a substitute.

Chapter 4. Data and descriptive statistics

Stock return and abnormal return are downloaded from WRDS international event study part. I choose different event window [-1 day, +1 day], [-2 days, +2days] [-5 days, +5 days] [-10 days, +10 days] and get data directly. In total, there are 670 British companies and 34 sectors.

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For CDS part, daily data series over the estimation window from 18th March 2016 to 8th July 2016 are downloaded from Datastream, which includes the estimation period [-71, -11] and the event window [-11,11]. The series covers credit default swaps spread for each firm, which is expressed in basis points. In total, there are 67 British active companies and 10 sectors according to Thomson Reuters.

In table 1, I calculated the average total return, average abnormal return, average cumulative abnormal return and standard deviation of cumulative abnormal return of all firms for each day over the period [-9,10]. And the graph 1 below gives a more intuitive indication that the mean cumulative abnormal return is decreasing through the period. And it drops quickly, especially after the event day. At the end of the day on which Brexit referendum was announced, the British stock market index FTSE100 closed with a loss of larger than 3% (Andreas Oehler, Matthias Horn, Stefan Wendt, 2017). What's more, it is also apparent that the standard deviation of CAR is increasing over the whole period, which means the volatility of CAR increases.

In table 2, similar to the stock market reaction, we can see that the average cumulative abnormal CDS spread changes have generally increasing trend after the event day. It rises dramatically on the Brexit announcement day and the day after announcement day, around 11 and 10 basis points respectively. And the standard deviation of CASC increases obviously after the event day. It rises from 7.27 bps to 14.18 bps on the Brexit announcement day, which means the Brexit leads to the increasing volatility of CDS market.

These two tables display general pictures of Brexit referendum’s impacts on the stock market and CDS market in Britain. The indications are consistent with the previous studies and my hypothesis. In the next part, I will show more specific effects of Brexit on these two parts for each sector.

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Table 1. Stock return and volatility Day Relative to Event Date Mean Total Return Mean Abnormal Return Mean Cumulative Abnormal Return Standard deviation of CAR -9 -0.0105 0.0024 0.0024 0.0014 -8 -0.0172 0.0020 0.0044 0.0020 -7 -0.0018 -0.0092 -0.0049 0.0022 -6 -0.0093 -0.0029 -0.0078 0.0029 -5 0.0058 -0.0080 -0.0158 0.0028 -4 0.0119 -0.0191 -0.0349 0.0029 -3 -0.0004 -0.0033 -0.0382 0.0030 -2 0.0018 -0.0032 -0.0414 0.0035 -1 0.0066 -0.0056 -0.0470 0.0041 0 -0.0484 -0.0057 -0.0527 0.0046 1 -0.0405 -0.0015 -0.0541 0.0054 2 0.0100 -0.0190 -0.0731 0.0058 3 0.0146 -0.0190 -0.0921 0.0059 4 0.0111 -0.0098 -0.1019 0.0058 5 0.0052 -0.0049 -0.1068 0.0060 6 -0.0027 0.0079 -0.0989 0.0061 7 -0.0136 -0.0082 -0.1071 0.0063 8 -0.0119 0.0000 -0.1071 0.0068 9 0.0054 -0.0068 -0.1139 0.0067 10 0.0066 -0.0049 -0.1188 0.0068

Graph 1. Cumulative abnormal return: mean and 95% confidence level Total 681 events with non-missing returns

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Table 2. CDS spread changes and volatility Day Relative to Event

Date Mean cumulative abnormal CDS spread changes Standard deviation of CASC -10 2.5216 4.0794 -9 6.1712 8.4427 -8 10.7903 12.0991 -7 10.6944 10.0285 -6 12.6448 12.7133 -5 10.7573 10.2032 -4 4.8247 6.0906 -3 3.8051 6.4158 -2 2.2766 6.0761 -1 3.0842 7.2748 0 14.0292 14.1763 1 23.9182 18.4870 2 21.4689 15.5000 3 16.8643 12.3212 4 14.8614 12.0630 5 19.4661 16.2006 6 13.0144 11.0011 7 15.6818 13.2110 8 18.8846 16.2313 9 20.0267 16.9893 10 17.9644 15.7470

Chapter 5. Results

Our observations demonstrate the assumptions that the Brexit referendum had substantial influences on stock returns and CDS spread changes.

5.1 Stock

Table 3 summarized the estimated ARs and CARs for 34 sectors. It is noticeable that all the cumulative abnormal returns in the period [-10,10] are negative and most of them are significant. That means almost all sectors were negatively affected after 10 days, except aerospace and defense, chemicals, electricity, gas, general industrials, mining, and technology hardware sectors.

Table 3 reports ARs, CARs and the corresponding p-values of t-test following the Brexit referendum. Focusing on the abnormal return, cumulative abnormal return for [-1,1] and [-2,

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2], we can find that the market reacted as initially expected in 8 industries: banks, financial services, construction and materials, general retailers, household goods and home construction, travel and leisure, real estate investment and services, and real estate investment trusts. For example, (1) the banking sector was negatively affected by 11.4% on the first day of trading and was negatively affected by 21.4% in period [-1, 1]; (2) the financial services sector was negatively affected by 2.2% after 2 days at 5% significance level; (3) construction and materials were negatively affected by 8.6% after 1 day; (4) the general retailers sector decreased 8.7% after 1 day, which was significant at 1% level; (5) the cumulative abnormal return for [-1,1] of household goods and home construction was -19.4%, which was significant at 1% level; (6) real estate investment and services and real estate investment trusts were negatively affected by 6% and 8.4% at the 5% significance level. And (7) travel and leisure was negatively affected by 5.5% at 1% significance level.

The results of sectors such as banks sector and other financial institutions sector indicate the expected negative effects of Brexit. The previous arguments (Vikash Ramiah, Huy N.A. Pham and Imad Moosa, 2016) determined that Brexit was terrible news for the banking and other financial institutions sector, which was indicated by negative ARs and higher risk for these sectors. And the impacts on banking sector would be much more severe than on other financial institutions. Here, it is consistent with the findings in table 3.

There are also some sectors which were negatively affected, but the effects were not significant. They are (CAR1): aerospace and defense (−3.60%), food and drug retailers (−2.2%), general industrials (−7.0%), industrial engineering (−1.80%), industrial transportation (−1.0%), leisure goods (−1.60%), media (−0.80%) and personal goods (−0.8%).

According to the research results of Vikash Ramiah et al. (2016), there are still positive ARs in some sectors such as oil and gas producers although the majority of affected sectors displayed negative ARs. However, in table 3, there are no significant positive effects of Brexit on any sectors. There are only positive and not significant cumulative abnormal returns for some sectors, such as alternative energy, mining, oil and gas producers and Pharmaceuticals and Biotechnology in the period [-2, 2]. The distinction may be caused by the different model and data sources.

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Table 3. Stock return event study results and robustness test

n AR CAR1 CAR2 CAR5 CAR10

Aerospace and

Defense 3 mean p-value -0.024 0.165 -0.036 0.099 -0.016 0.359 -0.071 0.172 -0.036 0.329

Alternative Energy 10 mean _p-value 0.029 _0.947 0.038 _0.990 0.009 _0.797 -0.102* _0.030 -0.177* _0.011

Banks 4 mean _p-value -0.114* _0.042 -0.214* _0.045 -0.197* _0.022 -0.199** -0.292** _0.000 _0.002

Beverages 6 mean _p-value 0.013 _0.716 0.019 _0.736 -0.017 _0.154 -0.080* _0.016 -0.081** _0.002

Chemicals 10 mean _p-value 0.008 _0.624 0.018 _0.711 -0.024 _0.293 -0.086 _0.095 -0.103 _0.091

Construction and

Materials 16 mean p-value -0.048** 0.002 -0.086** -0.075* 0.002 0.028 -0.151** -0.189** 0.000 0.002

Electricity 3 mean _p-value 0.013 _0.742 0.022 _0.745 -0.004 _0.405 -0.094 _0.174 -0.071 _0.257 Electronic and Electrical Equipment 13 mean 0.008 -0.014 -0.051** -0.164** -0.130** p-value 0.759 0.182 0.002 0.000 0.000 Financial Services

(Sector) 56 mean p-value 0.005 0.714 0.001 0.532 -0.022* 0.044 -0.079** -0.084** 0.000 0.000 Fixed Line Telecommunications 5 mean 0.015 -0.031 -0.054* -0.081 -0.133** p-value 0.904 0.093 0.039 0.093 0.001

Food and Drug

Retailers 4

mean -0.015 -0.022 -0.010 -0.075** -0.094** p-value 0.330 0.344 0.381 0.000 0.005

Food Producers 10 mean 0.016 0.010 -0.023 -0.095* -0.094* p-value 0.912 0.642 0.216 0.015 0.016

Gas, Water and

Multi-utilities 5

mean 0.024 0.036 -0.033 -0.001 -0.163 p-value 0.979 0.955 0.215 0.492 0.170

General Industrials 3 mean _p-value -0.063 _0.124 -0.070 _0.144 -0.072 _0.110 -0.107 _0.107 -0.103 _0.092

General Retailers 36 mean -0.040** -0.087** -0.090** -0.125** -0.173** p-value 0.000 0.000 0.000 0.000 0.000 Health Care Equipment and Services 19 mean 0.025 0.022 -0.021 -0.090** -0.107** p-value 0.991 0.958 0.074 0.000 0.000

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Household Goods and Home Construction 10 mean -0.098 -0.194** -0.196** -0.211** -0.241** p-value 0.004 0.001 0.000 0.000 0.000 Industrial Engineering 11 mean -0.013 -0.018 -0.041* -0.094* -0.106* p-value 0.173 0.146 0.047 0.017 0.018 Industrial Metals and Mining 9 mean 0.040 0.052 -0.014 -0.048 -0.082 p-value 0.932 0.898 0.898 0.215 0.104 Industrial

Transportation 6 mean p-value -0.007 0.324 -0.010 0.373 -0.037 0.129 -0.084 0.052 -0.111** 0.008

Leisure Goods 7 mean _p-value 0.005 _0.611 -0.016 _0.245 -0.049 _0.055 -0.196** -0.267* _0.003 _0.035

Media 39 mean _p-value -0.002 _0.382 -0.008 _0.271 -0.040** -0.117** -0.152** _0.005 _0.000 _0.000 Mining 53 mean 0.038 0.073 0.035 -0.052* -0.033 p-value 0.999 1.000 0.984 0.024 0.158 Mobile Telecommunications 6 mean -0.017 0.016 -0.031 -0.100 -0.186* p-value 0.224 0.689 0.151 0.056 0.042

Oil and Gas

Producers 45 mean p-value 0.011 0.929 0.031 0.983 0.024 0.769 0.013 0.620 -0.045 0.169

Oil Equipment and

Services 7

mean 0.005 0.015 -0.016 -0.085* -0.153* p-value 0.639 0.722 0.243 0.016 0.040

Personal Goods 4 mean _p-value -0.037 _0.242 -0.008 _0.433 -0.017 _0.291 -0.105* _0.022 -0.088** _0.008 Pharmaceuticals and Biotechnology 47 mean 0.016 0.022 0.003 -0.069** -0.103** p-value 0.990 0.997 0.606 0.000 0.000 Real Estate Investment and Services 25 mean -0.032* -0.060** -0.091** -0.157** -0.226** p-value 0.012 0.010 0.000 0.000 0.000 Real Estate Investment Trusts 11 mean -0.029* -0.084* -0.075** -0.084** -0.129** p-value 0.030 0.016 0.005 0.000 0.000 Software and Computer Services 71 mean 0.006 0.005 -0.027** -0.096** -0.108** p-value 0.861 0.701 0.004 0.000 0.000

Support Services 70 mean _p-value -0.013 _0.085 -0.022* _0.028 -0.049** -0.103** -0.136** _0.000 _0.000 _0.000

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Hardware and

Equipment p-value 0.635 0.922 0.053 0.207 0.234

Travel and Leisure 36 mean -0.009 -0.028* -0.055** -0.117** -0.150** p-value 0.174 0.037 0.000 0.000 0.000 ** indicates statistical significance at the 1% level.

* indicates statistical significance at the 5% level. 5.2 CDS

Table 4 and table 5 show the results of the Brexit referendum on banks' CDS spread changes. Table 4 displays mean abnormal CDS spread changes (ASs) and their p-values of t-tests. Table 5 shows the cumulative abnormal CDS spread changes (CASs) for [-1,1] and [-2,2] and related p-values of t-tests.

In table 4, it is obvious that the abnormal spread changes for all sectors are positive on the Brexit announcement day and the day after referendum announcement day. The significant positive effects are also concentrated on these two days. For example, the abnormal CDS spread changes of Banks, Consumer Goods, Energy, Electric, Gas, Manufacturing, Other Financials, Services increase significantly on the Brexit announcement day. On the first day after the event day, it can be discovered that the Brexit leads to a large and significant increasing CDS for banks, with an average abnormal spread change of 30.667 bps at 1% significant level. The other financials’ abnormal CDS spread changes were positively affected by 9.460 bps at 1% significant level. And the abnormal CDS spread changes of Services also increased by 8.73 bps at 1% significant level. The Energy, Electric and Gas sector’s spread change was also positively affected by 4.773 bps at 5% significant level.

The results from table 4 support the data in table 5. In table 5, for [-1,1] event window, the mean cumulative abnormal CDS spread changes of banks was 46.79 bps, which was significant at 1% level. And the other financials sector's mean cumulative abnormal CDS spread changes were 21.10 bps at 1% significant level. The services sector’s mean cumulative abnormal CDS spread changes were 21.67 bps at 1% significant level. At 5% significant level, the mean cumulative abnormal spread changes in energy, electric, gas, and manufacturing sectors are 7.77 bps and 9.80 bps respectively.

For [-2,2] event window, the cumulative abnormal CDS spread changes of banks, other financials and services are still significantly positive, which are 38.69 bps, 16.54 bps, and 19.87 bps at 1% significance level respectively. In addition, the manufacturing sector's CDS

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market reaction is significantly larger than zero, which is indicated as 8.41 bps cumulative abnormal spread changes. The consumer goods and energy, electric, gas sectors' cumulative adjusted CDS spread changes are 7.09 bps and 6.44 bps at 5% significance level respectively. The cumulative abnormal spread changes of telephone and transportation sectors are positive both in [-1,1] and [-2,2]. However, they are not significant. Moreover, there are no significant negative cumulative abnormal CDS spread changes for any sectors in Britain.

These two tables indicate that the CDS markets of banking sector, the other financial institutions, and services sectors were affected negatively by the Brexit with the positive abnormal spread changes, which means the significant increase of the credit risk in these three sectors. We reject the null hypothesis that Brexit announcement does not affect the CDS market in all sectors. Instead, most sectors are negatively affected in CDS market except the telephone and transportation sectors. The conclusion was consistent with the previous literature and the hypothesis. According to Dirk Schiereck, Florian Kiesel and Sascha Kolaric's (2016) study, the banks and financial institutions' CDS spreads show a substantial rise following the Brexit referendum.

Table 4. CDS event study results

Sectors Banks Consu

mer goods Energy, Electric, Gas Manufactur ing Other Financial s Services Teleph one Transportatio n N 6 6 3 9 23 15 2 3 -2 AS _p-value -2.091 _0.992 -1.361 _0.957 _0.8243-0.664 -1.425 _0.939 -1.361 _0.9895 _1.000-1.841 _0.838-3.422 -0.376 _0.804 -1 AS _p-value -0.908 _0.840 -0.818 _0.903 _0.2640.276 1.804* _0.043 1.522 _0.064 _0.0971.221 _0.756-2.622 -0.222 _0.648 0 AS _p-value 17.034* _0.038 7.622* _0.043 2.726 _0.219 5.461* _0.021 10.119** 11.715** 30.133 19.771 _0.000 _0.004 _0.149 _0.073 1 AS 30.667** 4.532 4.773* 2.535 9.460** 8.730** 13.943 12.608 p-value 0.001 0.094 0.024 0.058 0.002 0.000 0.213 0.077 2 AS -6.013 -2.888 -0.674 0.034 -3.203 0.045 -5.917 -8.049 p-value 0.999 0.888 0.819 0.472 0.999 0.481 0.814 0.900 **indicates statistical significance at the 1% level.

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Chapter 6. Robustness check

The above findings are confirmed by the robustness test results. As a robustness test, I use different event window to measure the cumulative abnormal return, and cumulative adjusted CDS spread changes. To illustrate the findings are robust to lengths other than one or two days, table 3 and table 5 provide an overview based on event window [-5, 5] and [-10, 10]. According to the observations of this part of the analysis, it is reasonable to reject the null hypothesis of no relationships between the Brexit referendum and the stock market. The CDS market indicates the same findings. These results are robust to variations in the length of the event windows.

Table 5. Robustness test for CDS

CAS1 CAS2 CAS5 CAS10

BANKS mean 46.7924** 38.6879** 6.4994 25.1386*

p-value 0.0000 0.0000 0.1987 0.0111 CONSUMER

GOODS mean _{p-value 0.0598}11.3363 7.0872* _0.0491 -3.3784 _0.9068 4.0610 _0.1099 ENERGY, ELECTRIC, GAS mean 7.7745* 6.4364* -3.5979 2.0015 p-value 0.0330 0.0111 0.7467 0.2797 MANUFACTURING mean 9.8002* 8.4088** 4.5036* 13.8701* p-value 0.0121 0.0076 0.0382 0.0188 OTHER FINANCIALS mean 21.1011** 16.5373** 10.4463** 18.9199** p-value 0.0000 0.0000 0.0000 0.0000 SERVICES mean 21.6661** 19.8702** 6.9277** 23.6100** p-value 0.0002 0.0001 0.0032 0.0001 TELEPHONE mean 41.4549 32.1167 2.7917 24.5400 p-value 0.1657 0.1622 0.2791 0.1955 TRANSPORTATION mean 32.1558 23.7308 19.5992 19.7308 p-value 0.0744 0.0685 0.0703 0.0653

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Chapter 7. Conclusion

The paper presents the evidence on the impacts of Brexit referendum event on Britain stock market and CDS market for various sectors. Applying the event study, the cumulative abnormal returns and cumulative abnormal CDS spread changes for each sector are explored during the period from June 10, 2018 to July 8, 2018. The results showed in this study prove the assumption that Brexit would have different sectoral effects, even though most of sectors are affected negatively as shown by negative CARs and positive CASs. It means that the Brexit has adverse effects both on stock and CDS market in most sectors in short-run. As expected, the banking and other financial institutions sectors are affected the most both in the stock market and the CDS market. It means that there would be the most severe decrease of the stock returns and increase of the credit risk in banking and other financial institutions. They are in line with the existing literature and explains why the most of previous researchers did the study on the Brexit effects on banking or financial institutions sector.

However, there are still some limitations of the paper. It studies the sectoral effects of the Brexit announcement on stock and CDS market without determining the factors which lead to the differences among sectors. It is suggested to do the further research on the reasons behind the phenomenon. Besides, the sample for CDS spread analysis includes only 67 active companies, which is not enough for the accuracy and the universality of the results. The data could be downloaded from the Bloomberg or IHS Markit, instead of Datastream, to get a larger sample of firms. Furthermore, the correlations of stock indices or CDS indices from various sectors have not been studied. Since I have examined some co-movements of abnormal stock returns and abnormal spread changes, it is reasonable to assume that there might be positive correlations between stock indices and CDS indices from different sectors. Last but not least, analyzing the Brexit’s sectoral effects on CDS market may be helpful for people such as international investors, traders and portfolio risk managers to avoid the potential loss in their investments. Also, the policymakers can benefit from the results to formulate new capital adequacy frameworks for the UK, particularly for each industry. Uncertainty around the further negotiations between Britain and the European Union remains. And the long-term impacts of Brexit on the United Kingdom's economy and even on the global economy are remained to be studied.

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The sectoral effects of Brexit on the stock and CDS market in Britain in short-term