What effect did the BREXIT have on the abnormal stock returns of REITs and how do different firm characteristics affect this relationship
Bachelor thesis at the University of Amsterdam
Thesis supervisor: Mario Bersem
Bachelor student: Koen Spelde Student number: 10819606 BsC Economie & Bedrijfskunde Field: Finance & Economics
Statement of Originality
This document is written by Koen Martijn Spelde who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references have been used creating it.
The Faculty of Economics and Business responsible solely for the supervision of completion of the work, not for the contents.
2 Contents:
1. Introduction 5 2. Literature overview 7 3. Methodology 11 3.1 Event study methodology 11 3.2 Regression analysis methodolgy 15 4. Data 18 5. Results 19 5.1 Event study results 19 5.2 Regression analysis results 23 6. Conclusion 24 7. Appendix 25 8. References 32
3 Abstract: The Brexit outcome affected the stock market on almost every sector both domestically as internationally. In this paper the effect of the Brexit on the real estate sector of the UK is examined. This is done by conducting an event study to test how UK REITS performed during the Brexit. The model used is the market adjusted model and found a negative overall effect of cumulative abnormal returns for the REIT sector and negative significant cumulative abnormal returns for 35 of the 39 REITS. Thereafter a regression analysis is provided to test the relation between the cumulative abnormal return and the market capitalization of the REITS. Besides the market capitalization, the leverage ratio, book to market ratio and the dummy variable for the FTSE100 and FTSE250 are included as control variables. The regression analysis found a negative relationship between the CAR and the market capitalization. In increase in market capitalization resulted in a further decrease of the negative cumulative abnormal return.
4 1. Introduction:
On June 24 in 2016, the United Kingdom voted to exit the European Union in a referendum. Of all participants, 51,9% voted in favor to leave the EU (The Guardian, 2016). This outcome was unexpected because the bookmakers expected a 90 percent chance that the UK would remain within the EU (Bloomberg, 2016). This outcome, the so-called Brexit, had many consequences on both domestic and international levels and caused many concerns on the political, social and economical level. Dhingra, Ottaviano, Samson & van Rheenen et al. (2016) found that in case the Brexit would happen, stock prices on the London stock Exchange would be negatively affected. The Brexit affected the returns in different sector types on both domestic and international stock markets. The day after the outcome the FTSE250 fell almost 12 percent in dollar terms. Moreover, an economic consequence is that 63% of UK export goods and services go to EU membership states. When the UK is no longer part of the EU, the UK will face trade tariffs because they cannot oblige to the EU trade agreement anymore. Dhingra et al. (2017) concluded that of all scenarios, the Brexit will reduce the welfare of the average UK citizen. In addition, a political consequence is that the position of EU residents who are living and working in the U.K. became uncertain. Monfared & Pavlov (2017) found prove that many EU residents left the London area due to the in 4 months’ time after the outcome of the referendum. Subsequently, real estate prices dropped between a range of 1,9% to 3%. Real estate and stocks are major components in valuing assets. Zeckhauser and Silverman (1983) found at least 25 percent of the value of corporate firms is associated with real estate. Gyourko and Keim (1992) published a paper and found prove that the real estate market is integrated in the stock market. Therefore, the stock market contains relevant and appropriate knowledge of the real estate market. Both stocks and real estate prices are subject to changes in the economy. Real estate and stocks are important investment vehicles of both individual and large institutional investors. A decrease in stock prices will result in a decrease in personal wealth, but research varies on how the Brexit influenced stock markets and different sectors in the UK. Most of the research was done for multiple sectors at once. Research
5 regarding the Brexit and the performance of real estate investment trusts (REITs) is only shortly mentioned in the paper of Ramiah, Pham & Moosa, (2016). Ramiah et al. (2016) researched the effect of the Brexit respecting different sectors of the UK. This was done calculating the abnormal returns of a 10-day event window regarding the Brexit. However, they found consistent results according to the paper of Dhingra et al. (2016). Moreover, market efficiency showed quick price adjustments of stock prices in 3 days after the outcome Oehler et al, (2017). Therefore, central in this thesis is to re-examine the abnormal returns of real estate stocks which formulate the following research question:
What effect did the BREXIT have on the abnormal stock returns of REITs and how do different firm characteristics affect this relationship
In this thesis, both the interest upon UK REITs and their performance after the Brexit outcome are considered. This is done by conducting an event study. The purpose of this thesis is to indicate abnormal returns for the REITs sector using a smaller event window than the research of Mackinlay, (1997). The aim of this thesis is to provide investors with insights, as they often consider real estate to diversify their portfolio. In addition, real estate is considered to be a relatively stable investment in someone’s overall portfolio. Therefore, it is interesting to consider what effect the Brexit had on these relatively stable stocks. The event study of this thesis calculates the abnormal returns, which will be based on the market-adjusted model. After this, the average t-test statistic is formulated to calculate the overall effect of het performance of UK REITS. Thereafter, a t-test is conducted for every REIT separately to establish their performance compared with the market return. In line with other research respecting abnormal returns and the Brexit, the results of the abnormal returns show a negative relation with the Brexit. After this event study was carried out, multiple regressions were performed. This was done with the use of STATA. Here, the relationship between the cumulative abnormal return and the market capitalization of the REITs was examined. In section 2, the literature overview will be described. The relation between the stock market and the Brexit will be discussed as well as what research was already
6 conducted with respect to the real estate market and the stock market. Thereafter, the first hypotheses will be formed. Moreover, the relation between stock returns and market capitalization will be described. After that, the firm characteristics which were chosen for the regression are explained. This is followed by the second hypothesis. In section 3, the event methodology is described. Then, the assumptions of a multiple regression are defined. In section 4, the collected data will be analyzed, which will be followed by some descriptive statistics. In the last section the results will be discussed, together with a conclusion based on these results.
2. Literature review
Brexit and stock markets Research varies on how the Brexit affected the stock returns. Alkhatib & Harasheh, (2018) published an article on how global financial markets experienced this shock. They found significant positive abnormal returns from US T-bonds on the event date. Moreover, Ramiah et al. (2016) wrote a paper where they conducted research on what impact the Brexit referendum outcome had on different sectors of the British Economy. By measuring abnormal returns, an event study over the period June-July in 2016 was conducted and the results showed that the banking sector and leisure sector were affected the most. The short-term market risk was adjusted by the Bank of England, which resulted in negative abnormal returns and higher risk for this sector. Besides that, the Financial Times wrote that banks will leave the UK when the outcome results in leaving the EU, which would eventually lead to depreciation of the pound. In addition, for UK residents, holidays became more expensive which resulted in the negative abnormal return of the leisure sector. This is consistent with the research of Bonchev and Penchava (2017), who focused on the abnormal returns of bank stocks in Europe and found significant negative abnormal returns. They also concluded that bank size matters in the level of negative abnormal return. Oehler, Horn and Wendt (2016) researched short term price effects of different sectors, and analyzed how the FTSE100 reacted after the Brexit referendum. This was done by taking the abnormal returns of the first 3 days after the FTSE100 opened. The results (figure 1) show that large and medium cap-prices and returns were very volatile for the first 3 days after the Brexit. For example, from June 24 to June 27 the FTSE100
7 ranged between 5798 – 6117 points. This research provided equally weighted mean values from the market capitalization and the standard deviation from the firms of the FTSE100. The statistical t – test of the abnormal and cumulative abnormal returns were found to have significant results at a 1 percent level. The abnormal returns of firms with a higher domestic operating degree were found to have a larger negatively affected return, in comparison to the companies that operate more internationally.
Figure 1: The FTSE100 index from 23/6/2016 – 30/6/2016
Definition of REITs: A REIT is a company or corporation which use the combined investments of all types of investors to purchase real estate property, Before REITs were created this was only available for large and wealthy individuals. A REIT is a company that owns, operates or finances income-achieved activities. REITs can be classified if at least 75 percent of the REIT’s profits are related from rental properties. Secondly, REITs are required to pay out 90 percent of their income. In addition, it is not possible to have shareholders who have a larger stake of 10% equity shares. When this is obliged, the REITs are not subject to corporate tax. The payout is done by paying dividends to their shareholders and investors. It is not rare the dividend yield is between 5 and 15%.
Relationship stocks and real estate: The public real estate market has developed into an asset class, which provides the possibility of extending the scope of commercial real estate without acquiring property (Ling and Naranjo, 2002). According to research, investors tend to invest in real estate
8 because they have a low correlation with other assets. REITs are originally seen as a mix between exposure and risk. Investors are likely to invest in REITs to diversify their risky portfolio. This implies that the REITs return and the volatility of their stocks are also related to the same macro-economic variables that affects bonds (Clayton & MacKinnon, 2003). The relationship and direction between the stock market and real estate stock is widely tested. Likewise, there is research done in previous papers about the causality for trends in stock markets and real estate. Okunev, Wilson & Zurbruegg, (2000) performed their research by conducting both linear and nonlinear causality tests of the relationship between trends in the stock market and real estate. They conduct their research of using REITs and the S&P500. They found a relationship between their observations and data, and between stock markets and real estate prices between 1972 and 1998. Therefore, there is a linear relationship between the two assets but there is a lag of time before equity REITs return are affected by the S&P return. Moreover, research done by Gyourko and Keim (1992) found evidence that the stock market contains relevant and appropriate knowledge of the real estate market. They regressed US equity REITs against the S&P500 and found results that the S&P returns have predictionary power in predicting Equity REIT returns. This supports the research of Andersson (2014), which is about the causality between the stock market and the housing market.
Previous research provided from Oehler et al, (2016),Ramiah et al. (2016) and Bonchev et al. (2016), caused the researcher of the current paper to expect that the cumulative abnormal returns of the REIT sector are negatively affected through the Brexit. Therefore, the first hypothesis is proposed:
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In order to find what could influence the cumulative abnormal returns of the REITs sector, three firm characteristics are explained which have a relationship with the stock market. These firm characteristics are market capitalization, leverage ratio and book to market ratio.
9 Firm characteristics:
In this paper, it is important to examine the relationship between stock returns and market capitalization. Market capitalization is measured by number of shares outstanding times the market price. Previous research showed a strong relationship of stock returns and market capitalization. For instance, Van Dijk (2011) aggregated previous research conducted on this relationship. Van Dijk combined the research of Banz (1981), Keim (1983) Lamoureux and Sanger (1989) and concluded that the papers had in common that a correlation exists between these two variables. In addition, Oehler et al. (2016) stated that abnormal returns of stocks which have a larger domestic degree are affected more negatively through the Brexit. The research of Bonchev and Pencheva, (2017) found that higher market value of the banks resulted in a larger negatively cumulated abnormal return regarding the Brexit. Therefore, it is expected that the relation between these two variables negatively affect each other. Moreover, it is expected that a relatively high market capitalization will increase the negatively cumulative abnormal return even further.
Secondly, Leverage ratio is determined by total debt divided by total assets. This ratio is a measure of the financial risk a company has. Opler and Titman (1994) provided evidence on how financial leverage affects corporate performance. Their research found prove that highly leveraged firms will perform worse in an economic downturn. This could be explained by the fact that highly leveraged firms will often have a greater difficulty to pay interest payments. Therefore, it is expected that this variable will show a negative relation with the cumulative abnormal returns.
Lastly, book to market ratio is mentioned in this paper. According to Fama and French (1992), stock returns are positively related to the book-to-market ratio. A book-to- market ratio higher than 1 implies that the NPV is higher than the value investors pay. This implies that a high book-to-market ratio results in a higher stock return. Moreover, the coefficient of this variable is expected to be positive for explaining the CARs.
As previous mentioned, important drivers of returns are market capitalization, leverage ratio and book-to-market ratio. After controlling for the last two variables, it is expected
10 that market capitalization negatively affects the cumulative abnormal return. Therefore, the second hypothesis is stated as follows:
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3. Methodology: In this section, the methodology of an event study is described and discussed. Thereafter, the regression analysis is described as well as the assumptions of an OLS- regression.
3.1 Event study methodology:
To analyze the reaction on the core real estate market of the Brexit, an event study is conducted. An event study measures the impact of a specific event on the value of the firm (Mackinlay, 1997). The event study of this paper is based on a one-day-event. Therefore, it a relatively smaller event window when compared to the event study literature from Mackinlay, (1997). However, the paper by Ederington, Guan and Yang (2015) show examples of event studies which are similar to the event study of this study. Conforming to the literature of event studies (Mackinlay, 1997), an estimation window is important to define. The paper of Mackinlay states that the average estimation window lies between 210 and 120 days. This is the period before the event without considering the event date. In addition, literature from Brown and Warner, (1985) conducted event studies using an estimation window of 240 days. Literature has shown (e.g. Mackinlay, 1997, Ahern, 2008) that the sampling error fades away by using a large estimation window. Different papers have shown that the chosen estimation window would be aligned between 90 days and 240 days prior the event. The estimation window is used to determine the benchmark of the index behavior. Therefore, in this paper the estimation window will be 180 days.
11
Figure 1: source De_Jong_2007
In this thesis, the return of the UK REITs listed on the London Stock exchange will be analyzed. This is done by using financial market data, which is the best way to explain event studies because the event influences the stock price almost immediately. The result of the Brexit vote came after the close of the British stock market. Therefore, the impact of the event was observable after the day after the referendum. Hence, the date of the event will be considered as June 24, 2016. Conforming to the literature of Ederington et al. (2015), the event window of this paper will be 2 days prior the Brexit and 2 days after the Brexit. This is often used for a small window, because it reduces the type 2 error. Evidence has shown a bias exists when aggregating abnormal returns. The event window is the time prior to the event and at least 1 day after the ‘event date’, to capture the changes in stock returns caused by the event (Ederington et al., 2015). In addition, the estimation window of 180 days is quite long. Therefore, to add more robustness for the estimation window, a shorter estimation window was chosen. Hence, the other estimation window is 90 days instead of 180 days, which is consistent with the literature of Mackinlay (1997). In the appendix there is a table which show the abnormal return calculated with the estimation window of 90 days.
Models:
Mean-adjusted model: A variety of models have been developed that can be used to calculate abnormal returns of event studies. The mean-adjusted model calculates the expected return of the average of the values T1 and T2. Where T = T2 – T1 + 1 equals the number of daily datapoints chosen to calculate the normal return. This model uses the normal returns as
12 benchmark from the chosen estimation window. This is obtained by the following formula: 1 �� = � �
A disadvantage of the mean-adjusted model is the average of the chosen benchmark given a certain estimation window. Following different papers this period is rather arbitrary. The mean adjusted model ignores wide stock price fluctuations related to benchmark period returns. This is especially the case with the same type of companies where the shares of those companies behave the same when the whole market goes up or down during the event period. This results in biased abnormal returns, which is not caused by the event but rather by price fluctuations between markets. To correct for this, the market-adjusted model is used to calculate the expected return of the different REITs
Market-adjusted model: According to an event study, the daily return of the securities stock and the market index return will be matched separately for each day of the estimation window. This is done by running a single index model regression to obtain each security’s alpha and beta. Alpha is the intercept term and beta the slope of the regression of the firm return against the corresponding market return. This is obtained with the following formula: