Essay Title: What are the Impacts of Brexit on FTSE100 Index?
Abstract
This paper is aimed at studying the impacts of Brexit on the FTSE100 index. The research paper employed the use of data exploration techniques such as descriptive and inferential analysis to study the trend in the stock value of various constituents of the FTSE100 index. The primary source of data for this research study was the Yahoo financial data, which provided historical data on the stock value of the FSE100 index for the period between 2010 to 2017. The results from the research work revealed that the announcement of the Brexit referendum and the actual Brexit caused a structural break in FTSE100 hence leading to a significant decline in the stock value of FTSE100 index constituents. The results are also linked to the decrease in the value of the sterling pound. This research paper is consistent with past research works that revealed a steep correlation between Brexit and the decline in the stock value of the FTSE100 index. Don't use plagiarised sources.Get your custom essay just from $11/page
Keywords: Brexit, FTSE100, descriptive statistics, inferential statistics, sterling pound.EU, the United Kingdom, European Union.
Introduction
The year 2016 was a year of global black swan events (Chen et al., 2017). During this year, Britain voted to leave the European Union with an approval rate of 52% from the voters. This was termed as BREXIT (British Exit). Brexit sparked various speculations and research work as far as its economic impact. Consequently, numerous research studies were conducted before the actual exit with the sole intention of analyzing the expected impacts of Brexit on the FTSE stock market. Financial Times Stock Exchange (FTSE) index comprises 100 companies, including but not limited to Barclays, BUNZL, and AVIVA. Most of the research studies that were conducted predicted a fall in Britain’s GDP as well as a significant decline in the living standards of the British, thanks to the impact of BREXIT on the FTSE100 stock market. These studies led to the adjustment of various economic sectors to act as shock absorbers for the economic impacts of Brexit. For instance, in the year 2006, after actual Brexit, the bank of England cut its interest rate from 0.5% to 0.25%. This was aimed at discouraging saving by promoting the spirit of investments and spending to caution England from the negative economic impacts of BREXIT. Until relatively, recently, Brexit has dramatically impacted the FTSE100 index; hence it’s very important to understand the correlation between Brexit and FTSE100 stock market before investing in any stock. This research paper aims at analyzing the impacts of Brexit on the FTSE100 index.
Literature Review
Various research works have been focused on highlighting, discussing, and analyzing the economic impacts of Brexit on the stock exchange market. Breinlich et al. (2018) conducted a research study to examine the economic effects of Brexit based on the evidence from the stock market. The research studied the British stock market reaction to the Brexit referendum of 23 June 2016 with the sole intention of assessing the expectations of investors as far as the impacts of Brexit on the UK economy. The research study employed the use of a two-step procedure to estimate the effects of various Brexit variables on the abnormal returns of UK firms. The results from the study outlined that initial stock movements in the UK markets were fueled by fears of a cyclical downturn and by the depreciation of the sterling pound following the outcome of the referendum on Brexit. The research also suggests that the two subsequent speeches by Theresa May had a very close correlation with the possible changes to the tariff and non-tariff barriers on the trades between the UK and Europe. This clearly reveals that investors could have changed their expectations in readiness for the impending possibility of a ‘hard Brexit’.
Caporale, Gil-Alana, & Trani(2018) also conducted a research study using parametric and semi-parametric techniques to examine whether Brexit had impacted any changes in the level of persistence of the FTSE100 index, IVI(implied Volatility Index), and the British Pound’ implied volatilities against the currencies traded in FOREX. The currencies examined include but not limited to the euro, the US dollar, and the Japanese Yen. During the research study, the samples were split to compare the stochastic features of the series that were being investigated before and after the Brexit referendum. The research conducted a daily observation of the four series. The information all of the four series was extracted from Thomson Reuters Datastream during the period from 1 January 2014 to 31 October 2017.
Consequently, the post-Brexit sample comprised 35% of the total sampled data. The results from the study revealed that IVI reacted to them in readiness for the Brexit referendum and declined significantly after the actual exit. On the other hand, the research revealed that British Pound IVs have remained above their initial value since the Brexit referendum. In addition, econometric analysis proved that there was a significant increase in the four series that were considered for investigation except for GBP-JPY IV.
Kurecic & Kokotovic( 2018) conducted a research study with the sole intention of investigating and analyzing the effects of Brexit on some selected stock indexes. The research used empirical analysis , which consisted of unit breakpoint tests. The unit breakpoints were determined using an overview of occurrences of political instability, thanks to the Brexit referendum. This particular research work revealed that the outcome of the Brexit referendum structural break that was consistent in all the stock indexes that were investigated. In addition, the research work did not find any substantial evidence of structural break that was caused by subsequent events such as the snap election.
Lobão & Santos (2019) investigated the effect of four-Brexit related announcements on seven major European stock markets. The results from this study suggest that the only Brexit announcement that caused significant negative cumulative returns was the announcement of the Brexit referendum. This particular research work revealed further that negative effects of Brexit announcement on the stock market reduced following a period of consecutive 5 trading sections after the event. This research work is in line with the semi-strong form of stock market efficiency.
Morales & Andreosso-O’Callaghan (2018) conducted a research study to evaluate the initial impacts of Brexit on the main stock market in the Greater China Region (GCR). The research work employed the use of augmented market models that integrates both Economic Policy Uncertainty (EPU) and implied volatility (VIX). This Particular research study was not in line with the semi-strong market efficiency. This is because the study suggests that Brexit had significant effects on the performance of market returns in GCR.
Sathyanarayana & Gargesha(2016) suggests that there was a significant impact of Brexit on Indian stock markets such as Sensex and nifty. They carried out an empirical research study to prove their argument. They examined the pricing behavior of the stock markets in relation to the Brexit referendum. They applied ADF tests on their raw data that was collected from 24 June 2015 to 19 July 2016 to come up with their final findings.
Toma (2018) carried out a primary research study to investigate the impacts of Brexit on the UK inward FDI. He predicted that the number of FDI (Foreign Direct Investment) projects would decrease significantly by 65% after Brexit and by 91% in 2019. The study utilized a gravity model approach that is based on mixed Poisson models and a counterfactual analysis that is based on differences-to-differences estimators.
Škrinjarić(2019) cited mixed results as far as the cumulative return series that he investigated during his research work. However, he found out that the volatility series were significantly affected by Brexit announcements. During his study, he analyzed data from January 2010 to July 2016. The main stock exchange that he was concerned with include but not limited to, Central and Eastern Europe (CEE) and South and Eastern Europe (SEE).
The literature review reveals a considerable study gap among the past studies as far as evaluating the impacts of Brexit on the FTSE100 index. Among the reviewed articles, only one article by Caporale, Gil-Alana, & Trani(2018) mentioned the impacts of Brexit on FTSE100. However, this article did not give much information on FTSE100 stock but focused more on other series. Other articles only focused on other regions such as China and India; hence they are not accurate in answering the research question and the hypothesis. In addition, the past research works exhibit a high degree of inconsistency; hence their accuracy is questionable. Furthermore, most of the past studies only concentrate on the impacts of the announcement of the Brexit referendum rather than the actual implementation of Brexit. This research paper will aim at bridging the study gaps by basing its discussion, particularly on the impacts of Brexit on the FTSE100 index.
Methodology
As discussed above, Brexit was met with high levels of anticipation among many investors. Most of the past research works suggest that the UK’s decision to leave the EU brought serious challenges such as political instabilities that greatly impacted Britain’s economy as well as other international economies. The main hypothesis of this research work is based on the fact that Brexit caused significant negative impacts on the FTSE100 index, thanks to the assumption that modern stock indexes are based on political stability and investors’ confidence in the stock market. Analysis of the impacts of Brexit on FTSE100 is very important as far as cautioning investors from market shockers. This research paper employed data exploration methods to analyze the impacts of Brexit on the FTSE100 index effectively.
Data Sample and Sources
The research data was retrieved from Yahoo finance. Daily historical FTSE100 stock data for the period between 26 October 2009 to 31 December 2010 and 24 April 2015 to 30 June 2016. This was aimed at basically comparing the value of the stock exchange market before and after the announcement and implementation of Brexit. However, the data obtained from the source was subjected to G*power analysis to ensure the data was free from any form of selection bias. In addition, the raw data were subjected to descriptive analysis to ensure the fair distribution of data. The data was organized into two sets, the first set comprises of data that contain FTSE stock value before the implementation of Brexit, and the inverse is true. The excel figure below shows raw data used during the research work.
Fig 1. Excel spreadsheet showing FTSE stock statistics for the period between 10/26/2009 to 12/31/2010
Fig 2. Excel spreadsheet showing FTSE stock statistics for the period between 04/24/2015 to 06/30/2016
Data Analysis
Various data analysis tools were used to test and process the raw data to meaningful information that could help in coming up with substantial findings as far as the research topic. Descriptive statistics, as well as inferential statistics, were used to process the raw data into meaningful information. Descriptive statistics tools that were used include but not limited to the mean of adjusted closing stock. Other statistical features were employed to check the trend of stock in the two different periods include the line graphs. The line graphs below show a comparison in stock trends between the two periods.
Inferential statistics were used to compare the correlation between the dependent and independent variables. Inferential statistics that were employed in this case is the regression model. We used a linear regression model to examine a single dependent variable and multiple independent variables. The dependent variable, in this case, is the change in the value of the stock market, while independent variables include the announcement of the Brexit referendum and the outcome of the referendum. All of the independent variables were categorized as nominal variables, while the dependent variables were treated as scale variables. The most suitable linear regression, in this case, was the multiple linear regression. The formulas below were used to model linear regression with the sole intention of determining the correlation between the dependent and the independent variables.
Let y be an independent variable, and k represent independent variables.
(1)
Where regression coefficients have an association with, and represents random error due to overfitting, the ith coefficient valued at shows the expected change in y per unit change of in ith independent variable, Xi and assuming E( )=0,
i= (2)
In order to accurately estimate the nominal variables that will be used during the regression model, the research first estimated the normal nature of the FTSE100 stock market that normally adjusts to differences and possible risks in the stock market. We examined the market models by calculating and estimating the normal characteristics of the stock model.
Return rit represents the return r on the stock at a variable time t to a specific market constant βi and the return on the market portfolio, Rmt.
(3)
Where t is the mean random component, and T1 is the pre-event period of stock price data.
After Brexit news, the stock returns are given by,
(4) Where ti represents abnormal time components.
The figures below show the regression models examining the impacts of Brexit on the FTSE index that was derived using the above calculations.
Results
The results from the findings suggest that there was a significant decline in the FTSE100 stock index when the announcement of the Brexit referendum was made. This is shown by the statistics displayed by the above line graphs. The line graph for the period between 8/14/2015 to 4/24/2015 shows a significant decline in the adjusted closing stock in the FTSE index. This could be attributed to the announcements that were made by Theresa May as far as the Brexit referendum.
From the regression model, the R square value is at 0.485061, and the adjusted R square value is 0.385061. Although these values are a bit far from – (+) 1, they still show some statistical significance between the dependent and the independent variables. In addition, from the ANOVA model, there is a significance factor of 0.652558 which shows that although there could be issues of overfitting, the data shown in the regression model exhibits high degree of significance. The small value of the adjusted R square may also suggests that there is minimal linear dependency between the dependent and the independent variables. In this case, the dependent variable is the value of the stock index (adjusted closing stock) while the independent variables are, announcement of Brexit referendum and the outcome of the actual referendum.
Among the two independent variables, the outcome of the Brexit referendum exhibits a small coefficient value compared to the announcement of the referendum. Announcement of Brexit referendum has a coefficient value of 0.011441 while the outcome of the actual referendum has a coefficient value of -0.18594. In addition the P value of Announcement of Brexit referendum is at 0.000138 while that of actual outcome of referendum is at 0.000118. These statistics show that announcement of Brexit referendum is more linearly dependent to the value of FTSE100 index (dependent variable) that the outcome of the referendum.
The statistical analysis of the raw data clearly shows a high degree of consistency. This is because both descriptive and inferential statistics suggests that there was significant impact of Brexit on FTSE100 index. The descriptive statistics as highlighted by the line chart shows decline in the adjusted closing stock following the announcement of a possible Brexit referendum. On the other hand, the regression models show a correlation between the dependent and the independent variable. For instance, the R squared value from the regression model reveals that the announcement of Brexit referendum led to a significant decline in the adjusted stock of FTSE100. The regression model is very accurate with a significance factor of 0.625. This means that there is minimal problems of overfitting in the scatter graph.
Additionally, it is very evident from the regression model that announcement of Brexit referendum greatly impacted the decline in the adjusted stock of the FTSE100 index compared to the actual outcome of the referendum. The findings from our research are in consistent with the past studies that suggested that Brexit announcement led to the reduction of adjusted stock in FTSE100.
Discussion of Research Findings.
This research study clearly reveals the negative impacts of Brexit on the stock market of FTSE100 index. The decline in the stock market was attributed to two main factors. Namely, the announcement of Brexit referendum, and the outcome of the referendum. The research shows a steady decline in the FTSE100 value following several announcements including but not limited to the speech of Theresa May during Conservative Party Conference on 5 October 2016 and her Lancaster house speech of 17 January 2017. The speeches suggested a possible hard Brexit. A hard Brexit implied that the UK would not only leave the EU but also the EU’s single market (of which non-EU countries are also members) and the EU custom Union. By leaving EU through a hard Brexit the UK would not have to sign up free trade movements with other EU nationals but instead impose strict rules and measures on its borders to regulate movement of EU nationals in and out of the UK. In addition, the UK would not be sign to EU court justice system.
Many research studies predicted the possible outcome of both hard and soft Brexit with the intention of cautioning investors against possible losses in the stock market. Consequently, most investors avoided trading on FTSE100 constituents to caution themselves against Brexit shockers. Share price movement of FTSE100 were also contributed to by the decline in the value of the Sterling pound.
Additionally, various microdata findings suggests that United Kingdom (UK) is more dependent on the EU (European Union) that the vice versa. Consequently, EU member states are more likely to find substitute market for their products even in the event of hard a hard Brexit. Therefore, Brexit is expected to have more impacts on the economy of UK including its stock market which contributes to a good percentage on its GDP.
Based on descriptive analysis, it can be concluded that the investors in FTSE100 index were quick to adapt to adapt to the occurrences of political uncertainties as a result of Brexit. This is very evident when the stock values of FTSE100 decline significantly during the time of announcement of possible Brexit referendum. However, it is also important to note that FTSE100 started to gain value immediately after the outcome of the Brexit referendum. This clearly shows that there was no long-lasting structural break on the stock value of the index, thanks to the fact that the structural breaks were mainly associated with speculation and uncertainty among investors who were keen to caution themselves against possible shockers of Brexit.
Limitations of the research.
This research study was also marred with a lot of challenges and setbacks. As much as we used analysis tools such as the G*power, the research sample still exhibited selection bias. This is because of the null records in the adjusted stock during some days in the data that was picked. In order to accurately check the trends of stock, the days were left out of descriptive and inferential analysis. Another problem that was encountered during the research study is the inability of accurately measuring the nominal dependent variables for the data regression models. The research study was also subject to significant other standard error problems. As shown in the regression model, standard error for coefficient of announcement of Brexit and the outcome of Brexit was at 0.013 and 0.0280 respectively, these values are statistically significance hence implying that there was a problem of overfitting in the regression model.
Another key challenge that was realized during the research study was the inconsistency of trends of trade between individual constituents of the FTSE100 stock index. Some constituents such as Barclays bank exhibited a steady increase in the stock value despite the political instability that was been experienced as a result of announcement of Brexit referendum and the outcome of the referendum.
Conclusion.
The result findings support the hypothesis that Brexit significantly affected the value of the FTSE100 stock index. It is in agreement with a number of past studies that suggest that stock market participants in FTSE100 expected an economic downturn in the days preceding the outcome of Brexit referendum. The main findings from the research suggest that share price movement in FTSE was greatly contributed to by the decline in the value of the sterling pound. The research further suggests that the two speeches by Theresa may the hinted a possible hard Brexit contributed greatly in the decrease in the value of FTSE100 stock index. This is because, investors cautioned themselves against the shockers of hard Brexit by trading conservatively on the constituents of FTSE100. The research study also revealed that there was no significant structural break in the adjusted closing stock of FTSE100 index following the outcome of the Brexit referendum. This reveals that structural breaks were mainly significant during the Brexit referendum announcement phase due to uncertainties and speculation of a possible hard Brexit by most investors who were solely concerned with cautioning themselves against Brexit shockers.
Recommendations of the Study.
This research study employed the use of relevant data exploration and data mining tools to accurately assess the impacts of Brexit on the FTSE100 index. The findings from the research are very accurate, thanks to the fact that a large sample data was considered for data analysis. In addition the regression and ANOVA models reveal high accuracy of the result with a significant factor of 0.65831. This research work is in conformity with past studies that revealed that Brexit greatly impacted the value of FTSE100 stock due to various factors including but not limited to decline in the price of the sterling pound. However, the findings of this researcher very important since the study bridges various research gaps. This is because this research study is among the few studies that have discussed the impacts of Brexit on the stock value of FTSE100. Additionally, the findings from this study can be used by various investors and stock traders to assess the market risks in FTSE100 and caution themselves from possible trade losses.
References
Breinlich, H. et al., 2018. The Economic Effects of Brexit: Evidence from the Stock Market. Fiscal Studies, 39(4), pp.581–623.
Caporale, G., Gil-Alana, L. & Trani, T., 2018. Brexit and Uncertainty in Financial Markets. International Journal of Financial Studies, 6(1), p.21.
Kurecic, P. & Kokotovic, F., 2018. Empirical Analysis of the Impact of Brexit Referendum and Post-Referendum Events on Selected Stock Exchange Indexes. South East European Journal of Economics and Business, 13(1), pp.7–16.
Lobão, J. & Santos, S., 2019. Stock Market Reaction To Brexit Announcements: Evidence From A Natural Experiment. Global Economy Journal, 19(03), p.1950018.
Morales, L. & Andreosso-O’Callaghan, B., 2018. The Impact of Brexit on the Stock Markets of the Greater China Region. International Journal of Financial Studies, 6(2), p.51.
Sathyanarayana, S. & Gargesha, S., 2016. Impact of BREXIT Referendum on Indian Stock Market. IRA-International Journal of Management & Social Sciences (ISSN 2455-2267), 5(1), p.104.
Toma, F.I., 2018. The Impact of Brexit on the Global Financial Markets. SSRN Electronic Journal.
Škrinjarić, T., 2019. Stock Market Reactions to Brexit: Case of Selected CEE and SEE Stock Markets. International Journal of Financial Studies, 7(1), p.7.
Appendix A
The research study gave me an in-depth understanding of the impacts of Brexit on FTSE100. I was able to use data analysis tools that gave me first-hand experience in understanding how stock trading is normally conducted. In addition, the research study allowed me to gain in depth knowledge and practise the use of various data mining and data exploration tools to obtain sources from financial website. For instance, I was able to retrieve historical stock data of FTSE100 index from financial yahoo websites and subject them to various data exploration techniques to transform the raw data into meaningful information for the purpose of analysis and thereafter prove my research hypothesis. However during the research work, I encountered a number of challenges that almost sabotaged the data exploration process. For instance, selection of a suitable sample proved hectic even with the assistance of sampling tools such as the G*Power analysis. This is because the selected sample was too large and exhibited selection bias hence leading to the problems of overfitting in the regression models. It was also very difficult to measure the nominal independent variables such as the outcome of the Brexit referendum and the announcement of the referendum. Consequently, only rough estimates of nominal variables were provided for the purpose of regressive analysis.