The effect of the ECB's monetary policy on stock market returns in Europe

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The effect of the ECB’s monetary policy on

stock market returns in Europe

Tim Koks

11323914

BSc Economie en Bedrijfskunde

Financiering en Organisatie: Financiering

Supervisor: Magdalena Rola-Janicka

June 28

th

_{, 2020}

Abstract

This paper tries to analyze the effect of monetary policy actions taken by the ECB on stock market returns in Europe. An event study is used to analyze this effect, an approach that was used by earlier papers for the US environment, but that is used less extensively for stock

markets in Europe. The results show that expected rate changes do not have a significant impact on stock market returns in Europe, while unexpected rate changes do have a significant negative effect on returns. These findings are in line with earlier research that was done in the US

environment. Besides looking at the complete stock index, a distinction between financial and non-financial stocks is made. The results show that monetary policy does not have a significant effect on financial stocks, while the effect on non-financial stocks is the same as for the complete stock index. When analyzing the difference between the effect of monetary policy on stock returns in crisis and non-crisis periods, this paper finds that returns react more significantly in non-crisis period than in crisis periods.

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Statement of Originality

This document is written by Tim Koks, 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 in creating it. The faculty of Economics and Business is responsible solely for the supervision of the work, not for the contents.

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1. Introduction

The European Central Bank (ECB) has an important role in the financial system. By using its monetary policy, it can change supply and demand in several sectors of the system, such as the bond market, the money market and the equity market. The ultimate objective of the monetary policy of the ECB is stated in the Treaty on the Functioning of the European Union, Article 127 (1):

The primary objective of the European System of Central Banks (hereinafter referred to as ‘the ESCB’) shall be to maintain price stability.

The main council in the European System of Central Banks is the Governing Council of the ECB. This council examines the monetary developments and has a meeting approximately every six weeks to make decisions on monetary policy.

In this paper, the effect of the monetary policy of the ECB on stock market returns in Europe will be analyzed. Monetary policy is the name for the different actions a central bank can undertake to influence the supply and demand for money, which results in changes in the interest rate (Mishkin et al., 2013). Changing these rates will change the financing conditions in the eurozone and change the economic activity in the area. The aim of this paper is to study the effect of ECB interest rate policy on stock returns in Europe, by using empirical data of firms across Europe.

Monetary policy decisions of central banks across the world are looked at with great care. Stock market analysts pay attention to changes in interest rates set by central banks, as these changes exert great influence on the real economy, which is why stock markets are expected to react significantly to changes in policy, making it interesting to analyze this relationship.

Expansionary monetary policy is referred to as a decrease in interest rates set by the central bank, while contractionary monetary policy is an increase in interest rates. Looking at previous literature, the expected effect is that expansionary monetary policy will lead to an increase in stock prices, while contractionary monetary policy will lead to a decrease in stock prices (Bernanke & Kuttner, 2005), by changing the interest rate to discount future cash flows and changing the cash flows itself (Campbell & Vuelteenaho, 2004).

Besides the direct effect of monetary policy on stock prices, equity markets also act as one of the first links in many transmission channels monetary policy tries to utilize (Mishkin, 2001). These transmission channels entail changes in private wealth, banks’ balance sheets and stock prices. The main transmission channels will be discussed in more detail in the literature review. Because of the role of stock markets in these channels and their role in transmitting the effects of monetary policy to the real economy (Mishkin, 2001), it is relevant to look at what effect changes in policy have on stock markets.

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5 actions have on financial institutions in particular. Banks and other financial institutions, like insurance companies, are expected to be more dependent on monetary policy and interest rates then other types of firms. Their business models are very dependent on interest rates and therefore very interest-rate sensitive. On the other hand, it has been shown that in low interest rate environments, banks’ stocks tend to show the reverse effect, because banks are reluctant to pass on negative interest rates to customers, which increases their costs and decreases their profitability (Heider et al., 2019). It is therefore interesting to analyze the effect of monetary policy and changes in interest rates on the returns of financial stocks.

The sample period of March 1st_{2009 to March 23}rd_{2016 includes the euro crisis, this}

period is included to get a sample period that is long enough, while still being relevant. Basistha and Kurov (2008) report that the state of the economy has a significant effect on how stock market returns are affected by monetary policy. They show that in periods of recessions and bear markets, stock returns are affected more strongly by monetary policy actions (Basistha & Kurov, 2008). However, when Kontonikas et al. (2013) looked specifically at the financial crisis of 2007-2009 in the US, they concluded that stock returns in this period where far less affected by monetary policy changes than stock returns in normal times. Because the crisis period entails a substantial part of the sample period and because of the earlier research done in the US environment, it is interesting to assess whether stock market returns are influenced differently in this crisis period, with the focus being on the European environment instead of the US environment. The crisis period used is the one also used by Ricci (2015) and covers the period from March 2009 to June 2013.

Earlier studies on the effect of monetary policy on stock markets were done for the US environment by Bernanke and Kuttner (2005), Ehrmann and Fratzscher (2004), Kontonikas et al. (2013), Basistha and Kurov (2008), Thorbecke (1997), Bernanke et al. (2004) and Bjørnland and Leitemo (2009), and for the European environment by Haitsma et al. (2015). Besides focusing on stock market returns, other papers have also looked at the effect on other segments of the financial market. A paper by Kurov (2010) looked at the effect of monetary policy on investor sentiment. Frankel (2009) had its focus on the effect of monetary policy on commodity prices.

Because most research on this topic has been done for the US environment, it is interesting to analyze the effects of monetary policy on stock markets in the European environment, as the ECB takes a different approach then the Federal Reserve on monetary policy, especially in times of crisis, and focusses on other aggregates, with the Fed often neglecting the role of money and these aggregates, while the ECB has clear targets for these aggregates (Kahn & Benolkin, 2014). This paper will conduct an event study, analyzing the effects of interest changes by the ECB on stock market returns in Europe, following the approach of Bernanke and Kuttner (2005). A distinction between unexpected rate changes and the part of the change that was already

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6 anticipated will be made using futures prices, following the approach introduced by Kuttner (2001).

This paper tries to make three contributions to the existing literature. It will use the methodology of Bernanke and Kuttner (2005) to analyze the effect of the monetary policy of the ECB on stocks in Europe, it will analyze whether financial firms are more significantly affected by changes in monetary policy and it will look at the difference of this effect between crisis and non-crisis periods.

Previewing the results, it can be concluded that unexpected changes in monetary policy do indeed have a significant effect on stock market return. It can also be concluded that expected changes do not have a significant effect, which is in line with the theory of efficient markets (Fama, 1970) and earlier findings by Kuttner (2001), Bernanke and Kuttner (2005) and Haitsma et al. (2016). The results for the financial and non-financial index subsets show that there is no significant effect of monetary policy on financial stocks, which is not in line with earlier research by Kholodilin et al. (2009) and Bredin et al. (2009). When looking at the difference between the crisis and the non-crisis period, it can be concluded that stock market returns in the non-non-crisis period react significantly different from returns in the crisis period. In the non-crisis period, a significant negative effect is found, while in the crisis period this effect is not found.

In the next section, information on theory will be given and earlier findings will be summarized. After that, the method and description of the data will be outlined. Then the hypothesis of the paper will be described. In section 5, the results of the research will be given and at the end of the paper, a conclusion to the hypotheses will be given.

2 Literature Review

2.1 Background

2.1.1 Monetary policy

Together with fiscal policy, monetary policy is one of two ways by which institutions can alter the direction of economic activity (Friedman, 2000). Fiscal policy is mainly conducted by governments, while monetary policy is conducted by central banks, which are independent institutions.

The ultimate goal of the ECB is price stability. There are different ways in which price stability leads to high economic activity: It improves transparency, reduces inflation risk (and inflation risk premia in interest rates) and financial stability is increased (European Central Bank, 2011).

The monetary policy of the ECB is supported by two pillars: the first being monetary analysis, in which the ECB monitors different monetary aggregates, and the second being economic analysis, in which the ECB analyzes different macro-economic trends, such as

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7 developments in output, developments in labor conditions and fiscal policy (European Central Bank, 2020).

From this analysis, the ECB needs to assess which actions need to be undertaken. The ECB has different methods to reach its primary goal of price stability. Conventional monetary policy tools have been used extensively throughout history, while unconventional monetary policy tools have been implemented since the crisis period, when conventional tools proved not to be effective. The main aim of changing interest rates is to steer the short-term money market rates (Eser et al., 2012). Other aims are signaling the monetary policy stance, providing liquidity and ensuring that money markets act the way they should (Eser et al., 2012).

There are different ways through which monetary policy is carried out. The conventional tools of monetary policy entail open market operations (OMOs), reserve requirements and standing facilities (Eser et al., 2012). With open market operations, the ECB buys or sells securities, usually government bonds. By doing this, the supply of bank reserves is increased or decreased, which alters the interest rate. The ECB can also change the reserve requirements set for the banks. The ECB then changes the percentage of funds banks are required to hold as reserves. When reserve requirements are lowered, the demand for reserves is lower. As a consequence, supply of reserves rises, and the interest rate decreases. The third conventional monetary policy instrument of the ECB are standing facilities. The two standing facilities of the ECB are the marginal lending facility, which parties can use to obtain overnight liquidity against assets. The rate of this facility is the ceiling for the market interest rate. The other standing facility is the deposit facility, this facility is used by parties to make deposits at the central bank. The rate of this facility is the floor for the market interest rate (European Central Bank, 2020).

In the crisis period of 2009 onwards, conventional instruments proved not to be effective, because the ECB had its policy rates near the zero bound, which gave rise to a need for additional monetary stimulus, besides the conventional policies already in place (European Central Bank, 2014). Forward guidance is one of these unconventional instruments and is used since 2013. By using forward guidance, the ECB tries to influence the expectations of short-term interest rates by stating their policy standpoint and the way they expect to influence the economic environment, which will then influence the intermediate to medium-term horizons (European Central Bank, 2014). A second unconventional method the ECB can implement is the use of quantitative easing (QE). The goal of QE is to specifically target the level of cash reserves the banks held. The hope of central banks is then that if these reserves rise high enough, eventually this would have a spill-over effect to the rest of the economy, so that asset prices would rise and deflationary forces would disappear (Joyce et al., 2012). This spill-over effect is expected to be significant, because banks act as the main provider of credit to companies and households in the economy. When reserves rise, this means that more money will eventually get into the economy and spending will increase

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8 (Joyce et al., 2012). A third unconventional method used by the ECB are negative interest rates. In 2014, the Governing Council of the ECB decided on a rate cut that would decrease the deposit rate to -0.10 percent. The ECB implemented this strategy to discourage banks to hold reserves at the central bank, so that this money will spill over to the real economy (Bernoth & Haas, 2018).

2.1.2 The role of stock prices in the transmission of monetary policy

The relationship between monetary policy and the stock market is an important one, because the stock market serves as an important part in the transmission mechanisms of monetary policy to the real economy (Mishkin, 1995).

Before discussing the main transmission models of monetary policy, it is useful to explain how monetary policy directly influences the level of stock prices in the economy.

The most used method for the valuation of companies is the discounted cash-flow model, which discounts future value with the cost of capital (Koller et al., 1990). Interest rates play a big role in this cost of capital, so when these rates rise (fall), cost of capital will rise (fall) with it. When cost of capital changes, discounted cash flows will change, which will then change the value of companies and ultimately stock prices (Koller et al, 1990).

Besides influencing the denominator in the DCF model, monetary policy can also have an impact on the numerator in the formula. Campbell and Vuelteenaho (2004) write about the ‘cash-flow beta’ and find that this beta has a significant influence on the valuation of companies. They state that monetary policy can have a significant effect on the expected future cash flows of a company, which in turn leads to changes in the value of companies and changes in their stock prices.

Now that the direct effect of monetary policy on stock prices has been discussed, the transmission channels of monetary policy will be explained.

The main transmission channel discussed in this paper will be the asset-price channel. There are different ways through which monetary policy can influence asset prices and in this case, stock prices (Mishkin, 1995). In the asset-price channel, expansionary monetary policy, in this case declining interest rates, means that stocks will be a more attractive acquisition than other types of assets. This follows from the fact that when interest rates fall, bonds will be discounted with a lower rate and their price will rise, which causes a decrease in their yield (Kuttner, 2001). Taking this into account, equity will be a more attractive acquisition than bonds. Because of this, the prices and thus the returns on stocks should increase (Mishkin, 1995). A higher stock price increases firms’ market value and thus increases firms’ Tobin’s q. Tobin’s q is defined as the market value divided by the replacement costs of a firm. If Tobin’s q is high, this will make investments relatively cheap, which will increase investment activity, which will in turn increase aggregate demand (Mishkin, 1995). Below, a framework for the asset price channel is shown.

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9 M↑ → S↑ → q↑ → I↑ → Y↑

A way in which monetary policy can directly increase consumer wealth is also through a rise in stock prices (Mishkin, 2001). When stock prices rise, portfolios held by consumers will rise in value, which will increase consumer wealth and thus consumption, which will increase aggregate demand.

M↑ → S↑ → Wealth↑ → Consumption↑ → Y↑

Another transmission channel is the balance-sheet channel (Mishkin, 2001). Due to expansionary monetary policy (falling rates), firms’ assets and market values will rise, because future cash flows are discounted with lower interest rates. When net worth rises, firms will be able to pay off more obligations and thus information asymmetry problems become less severe, which makes borrowing less expensive. Because of this, firms can attract more funds from creditors, which will get them to invest more, which will make aggregate demand rise (Mishkin, 2001). The channel is shown below.

M↑ → A↑ → NW↑ → L↑ → I↑ → Y↑

The last channel that will be discussed in this part is the bank lending channel. The idea of this channel is that most small and medium-sized firms depend on banks for their credit, in contrast to large firms, who can also sell bonds, for instance. A contractionary monetary policy may alter the amount of loanable funds a bank holds, which causes banks to lend less credit. As said, small- and medium-sized companies depend on banks for credit. If this credit is not available anymore, they have to incur costs to look for new credit. The bank lending channel then states that the searching costs for this new credit will lower aggregate demand (Bernanke & Gertler, 1995). A lot of contrasting research has been done on the significance of the bank lending channel. Driscoll (2004) finds a significant effect of money-demand shocks on bank lending. However, he concludes that the effect of bank lending on output is insignificant.

The first two channels discussed above are examples of asset-price channels and provide a good example for how monetary policy affects stocks and through these stocks, the real economy. The last two channels are examples of credit channels. These channels show how monetary policy can alter banks’ credit behavior and thus affect the real economy. The main thought in these channels is that financial frictions, such as information asymmetry and higher monitoring costs will affect the lending behavior of banks and via banks will influence aggregate demand (Mishkin, 2001).

Because this paper will look specifically at financial service firms and the effect of monetary policy on their stock prices, these last two channels are relevant.

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10 particular, financial often borrow short-term. Because monetary policy influences short-term rates, the effect of this policy is expected to have an increased effect on the borrowings of financial institutions and increase the ‘income gap’, the difference between assets and liabilities of banks (Landier et al., 2013). A change in interest rates will mean a change in the magnitude of banks’ activities, which rely heavily on the level of interest rates and are expected to experience more interest rate risk than other firms (Landier et al., 2013). Besides this, financial institutions often have a lot of capital invested into stock markets, and with changing interest rates, stock prices will change in the way described at the start of this section, which will lead to banks’ changing in value. It is expected that the effects described above will spill over to the value of the banks’ own stocks.

2.1.3 Efficient market hypothesis (EMH)

In the model used in this paper a distinction between unexpected and expected changes will be made. This is following the methodology introduced by a paper by Kuttner (2001), which introduced an equation for measuring the unexpected part of a policy action. One of the hypotheses in this paper considers the effect of expected rate changes on stock market returns. It is expected that no significant effect of expected rate changes on stock market returns is found. The expectancy of the rejection of this hypothesis is built around the hypothesis of efficient markets, introduced by Eugene Fama (1970). Fama argues that there are three forms of efficiency: the weak form of efficiency states that all past prices should be priced into markets. The semi-strong form goes a step further and states that besides past prices, all publicly available information is also priced in. The strongest form states that enough investors have private information, so that this information is also priced into the market (Fama, 1970).

If EMH is applied to the model in this paper, it can be expected that expected changes should not have an effect on stock market returns, as this information should already be priced into the returns beforehand. This result should be consistent with the findings of Kuttner (2001) for bond yields and Bernanke and Kuttner (2005) for stocks in the US environment.

2.2 Previous studies

Monetary policy and its effect on stock markets has been a subject of particular interest over the years and studies on the subject were done in all parts of the world. However, the main environments in which this subject has been researched have been the United States and Europe.

2.2.1 Studies in the US environment

The effect of changes in federal funds rate and the stock market in the US has been researched by many studies.

The study this paper will follow is the one conducted by Bernanke & Kuttner in 2005. In this paper, they divide the policy changes of the Federal Reserve into an expected and unexpected part.

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11 Bernanke and Kuttner observe that markets experience a significant negative change as a result of unexpected contractionary policy actions. However, when actions are anticipated and thus expected, no significant change in stock markets return can be found. The insignificance of expected changes is in line with the EMH that Fama (1970) introduced.

This paper will try to extend the research done by Bernanke and Kuttner (2005) by applying it to markets in Europe and trying to make a useful distinction between financial and non-financial firms. Ehrmann and Fratszcher (2004) look at industry-specific effects in the US environment. They find that different industries have different responses to interest rate changes and attribute this to different factors, namely interest-rate sensitivity, the importance of exchange rates in business models and lastly the importance of capital in business models. Relevant for this paper is the conclusion that monetary policy seems to have a significant influence on stock market returns in the US.

A paper by Basistha and Kurov (2008) uses the methodology of Bernanke and Kuttner (2005) and specifically looks at the way in which different states of the economy influence the effect of monetary policy on stock markets differently. They find that in recessions and bear markets, stock market returns respond at least twice as much to monetary policy actions, this is interesting for the hypothesis of this paper that unexpected policy actions influence stock market returns differently in the crisis period.

Kontonikas et al. (2013) use the same methodology as Bernanke and Kuttner for the period 1989-2012. They find a contrasting result with previous literature, namely an insignificant effect of federal funds rate changes on stock markets. They contribute this to the finding that in the crisis period of 2007-2009, stock prices did not seem to react to federal fund rate changes, which is a relevant finding for this paper. This contradicts the findings of Basistha and Kurov (2008). Because of these contradictory findings, it is interesting to assess the effect of unexpected rate changes on stock market returns in the crisis period in the European environment.

While most studies use an event study methodology, there are some that use a Vector Autoregressive (VAR) methodology. This has been done in the US environment by Thorbecke (1997), who finds that expansionary monetary policy has large effects on stock returns, both ex-ante and ex-post and that these effects are larger for smaller firms than for large firms. Another paper that uses Vector Autoregression is the one by Maio (2013), who constructs different portfolios and finds that monetary policy changes affect small stocks more than they affect large stocks, which is consistent with the finding of Thorbecke (1997). Also, the paper finds that value stocks are more affected by monetary policy than growth stocks.

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2.2.2 Studies in the European environment

While most research focusses on the US environment, some research has been done in the European environment.

Haitsma et al. (2016) conduct an event study over a period of 16 years (1999-2015) to be able to look at whether monetary policy during the period of economic crisis has a different effect on stock markets than monetary policy during normal times and also make a distinction between conventional and unconventional measures. They find that before the crisis, expected changes have a significant impact on stock prices and that surprise changes in unconventional policy have a significant effect on stock returns during the entire period. They also conclude that conventional surprise changes do not have a significant impact on stock prices, which is consistent with the findings of Kontonikas et al. (2013) in the US environment.

Kholodilin et al. (2009) assess the impact of monetary policy of the ECB on different sectors and find that increase of 25 basis points results in a decrease in the stock market of between 0.3 and 2.0%. Relevant for this paper is that they conclude that financial sector firms’ stocks are significantly negatively affected by rising interest rates.

Another paper that looks at sector-specific responses in the European (UK and Germany) environment is the one by Bredin et al. (2009). This study follows the event study approach of Bernanke and Kuttner (2005). They find that surprise monetary policy changes have a significant impact on the UK sector indices, including financials, which is relevant for this paper. The results of this study are in line with the study of Bernanke and Kuttner in the US.

Hussain (2011) analyzes both US and European stock indices. This paper uses intraday data (5 min price quotes), which allows for more immediate response analysis then when daily data is used. The results showed that monetary policy decisions have a significant influence on both returns and volatilities of US and European stock markets. Because they use 5 min price quotes, another result is that this effect is usually seen quick after an announcement. Also, the paper shows that the press conference of the ECB that is held 45 minutes after the decisions are made public also have a significant effect on stock returns.

A paper by Ricci (2015) looks specifically at the impact of monetary policy on banks’ stocks, which is relevant for this paper. It finds that unconventional monetary policy methods have more effect on banks’ stock returns than conventional methods, like interest rate decisions. Relevant for this paper is the fact that the sample period used in the paper is that of the financial crisis, from 2007 to 2013.

Some papers analyze the difference in the reaction of the stock markets in Europe to monetary policy changes between the crisis period and the pre-crisis period. Jardet and Monks (2014) use intraday data and find no significant differences in this reaction between these periods.

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13 This paper tries to extend these papers by not looking at the difference between the crisis and pre-crisis period, but rather by looking at the difference between the crisis and post-crisis period.

3 Hypotheses

The research question this paper tries to answer is: What is the effect of the monetary policy of the

ECB on stock markets in Europe distinguishing between expected and unexpected policy actions, are these effects larger for financial stocks than for non-financial stocks and is the effect of unexpected rate changes different in crisis periods than in non-crisis periods?

With this question, five hypotheses can be formulated. The first hypothesis is that the total rate change done by the ECB has a significant impact on stock returns, because of earlier research and theory, this paper expects to reject this hypothesis. The efficient market hypothesis as explained by Fama (1970) states that expected changes should already be priced in and no price drift should occur at the announcement data. Also, previous literature on this topic has also concluded that expected policy actions do not have a significant impact on stock returns. To analyze the difference in expected and unexpected policy actions, this paper will first look at the effect of the total rate change on stock market returns. Because of the fact that rate changes are generally anticipated in advance, this paper expects the expected part of the change to dominate the unexpected part and not reject the first hypothesis.

Hypothesis (1):

H0: Interest rate changes do not have a significant impact on stock market returns. H1: Interest rate changes have a significant impact on stock market returns.

The second hypothesis is that expected changes alone have a significant impact on stock market returns. Because of the efficient market hypothesis by Fama (1970) and earlier research, this paper expects to not reject this hypothesis:

Hypothesis (2):

H0: Expected rate changes do not have a significant effect on stock market returns. H1: Expected rate changes have a significant effect on stock market returns.

The third hypothesis is that unexpected changes have a significant effect on monetary policy, as this part of the policy change was unanticipated and this information is expected to not be priced into the market yet. Falling interest rates are expected to increase stock returns, as spending is increased and company valuations also increase, which is why a negative effect is expected.

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Hypothesis (3):

H0: Unexpected rate changes do not have a significant effect on stock market returns. H1: Unexpected rate changes have a significant negative effect on stock market returns.

The fourth hypothesis of this paper is that returns on financial stocks are more significantly affected by monetary policy actions than returns on non-financial stocks. Due to the different transmission channels of monetary policy as explained by Mishkin (1995) and the interest-rate sensitivity of their demand, financial institutions are expected to play a large role in the transmission of monetary policy. It is therefore interesting to look at whether financial stocks are also more significantly affected by monetary policy changes.

Also, earlier findings of Ehrmann and Fratschzer (2004), Haitsma et al. (2016) and Kholodilin et al. (2009) conclude that financial stocks should be significantly affected by monetary policy changes, while other sectors, such as the construction, industrial and technology sectors do not show a significant impact. Research by Ricci (2015) contradicts these findings and finds that banks’ stocks react less to conventional methods of monetary policy than to unconventional methods in the financial crisis.

Hypothesis (4):

H0: Unexpected policy actions affect financial and non-financial stocks equally. H1: Unexpected policy actions do not affect financial and non-financial stocks equally.

Because the crisis period in Europe entails a large part of the sample period used in this paper, and because of earlier research done on the effect of monetary policy in periods of crisis in the US environment, this paper will look at this effect in the European environment. Because earlier research and the hypotheses expect that unexpected rate change have a significant effect on stock market returns, while expected rate change are expected to not show this effect, this paper will analyze the difference in the effect of unexpected rate changes on stock market returns between the crisis and non-crisis time period. This results in the following and final hypothesis:

Hypothesis (5)

H0: Unexpected rate changes in the crisis period do not have a different effect on stock returns than in the non-crisis period.

H1: Unexpected rate changes in the crisis period have a different effect on stock returns than in the non-crisis period.

4 Data and Methodology

4.1 The model

To test for the effect of monetary policy actions on index returns, the approach introduced by Bernanke and Kuttner (2005) is used. In this approach, a distinction between expected and

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15 unexpected policy actions is made. To control for global stock market movements outside Europe, the MSCI World ex Europe returns are included as a control variable. All regressions will be done using OLS and the regression results will include robust standard errors. The baseline regression will not yet make the distinction between expected and unexpected actions and is the following:

𝑅𝑡 = 𝛼1+ 𝛽1∆𝑟̃𝑡+ 𝛽2𝑀𝑆𝐶𝐼 + 𝜀𝑡 (1)

Where 𝑅_𝑡 is the percentual return on the index of interest (STOXX 50, STOXX 600, STOXX 600 ex Financials or STOXX 600 Financials) on day t, starting with the announcement on March 5th_2009,

∆𝑟̃𝑡 is the change in interest rate on day t, C is the return on the MSCI World ex Europe index which

is included as a control variable to control for movements in world-wide stocks and 𝜀_𝑡 is an error term.

Stock index returns for day t are calculated with the following formula:

𝑅𝑡 =

𝑝𝑡− 𝑝𝑡−1

𝑝𝑡−1

× 100

In which 𝑝_𝑡 is the price level of the index on day t of the announcement and 𝑝𝑡−1 is the price level

of the index on the day prior to the announcement.

Equation (1) will be used to test hypothesis (1), which asks whether interest rate changes have a significant effect on stock market returns.

Hypothesis (1): H0: 𝛽1 = 0

H1: 𝛽1 ≠ 0

After running the baseline regression, the distinction between the expected part and the

unexpected part of a policy action will be included in the model and the model will look like this: 𝑅𝑡= 𝛼1+ 𝛽1∆𝑟̃𝑡𝑒+ 𝛽2∆𝑟̃𝑡𝑢+ 𝛽3𝑀𝑆𝐶𝐼 + 𝜀𝑡 (2)

Where ∆𝑟̃_𝑡𝑒_{is the expected part of a policy action on day t and ∆𝑟̃}

𝑡𝑢 is the unexpected part of a

policy action on day t.

For determining the unexpected part of a policy change, the approach introduced by Kuttner (2001) is followed and futures data is used. The data that is used is the Euribor

continuous futures rate. Bernoth and Von Hagen (2004) have shown that this can be regarded as an unbiased and efficient predictor of ECB policy rates. The formula that is used to obtain the unexpected rate change is the following:

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16 Where 𝑓_𝑠,𝑡0_{is the Euribor futures rate on day t of the announcement and 𝑓}

𝑡−10 is the Euribor futures

rate on the day before the announcement. The futures rate is calculated by subtracting the futures price from 100.

In the paper by Kuttner (2001) the difference was scaled because only monthly data was available. Since there is daily data available for Euribor futures, this scaling is not done for the data on Euribor futures (Bredin et al., 2009).

To get the expected part, the unexpected part of the change is subtracted from the total change that followed from the meeting of the ECB:

∆𝑟̃_𝑡𝑒_{= ∆𝑟̃} 𝑡− ∆𝑟̃𝑡𝑢

With the returns now divided into an unexpected and expected part, the data to run the second regression is available and the regression equation can be designed to distinguish expected and unexpected policy actions.

Equation (2) is used with the indices’ returns to test hypotheses (2) and (3): Hypothesis (2): H0: 𝛽₁= 0 H1: 𝛽₁≠ 0 Hypothesis (3): H0: 𝛽₂= 0 H1: 𝛽₂ < 0

To analyze hypothesis (4), Equation (2) is used with returns on the STOXX 600 ex Financials and returns of the STOXX 600 Financials index as dependent variable, to analyze the difference in effect of monetary policy on these two subsets.

For analyzing the difference in the effect of unexpected rate changes in the crisis and non-crisis period, a non-crisis dummy CRISIS and interaction variables CRIUN (=non-crisis*unexpected rate change) and CRIEX (=crisis*expected rate change) are added to the second regression, with STOXX 50, STOXX 600, STOXX 600 ex Financials and STOXX 600 Financials as dependent variables, which results in:

𝑅𝑡 = 𝛼1+ 𝛽1𝐶𝑅𝐼𝑆𝐼𝑆 + 𝛽2∆𝑟̃𝑡𝑒+ 𝛽3∆𝑟̃𝑡𝑢+ 𝛽4𝐶𝑅𝐼𝑈𝑁 + 𝛽5𝐶𝑅𝐼𝐸𝑋 + 𝛽5𝑀𝑆𝐶𝐼 + 𝜀𝑡 (3)

Hypothesis (5) statistically looks like this:

Hypothesis (5) H0: 𝛽₄= 0 H1: 𝛽₄≠ 0

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17

4.2 Data

To analyze the effect of changes in monetary policy on stock market returns, an event study is conducted. The period for which data is used is March 1st_{2009 to March 23}rd_{2016. Dates of the}

meetings in which the Governing Council of the ECB decided upon monetary policy have been included in the sample. Together, this sums up to a total of 79 meeting days, in which 11 meetings resulted in a change of the interest rate of the ECB. The first meeting included in the dataset is the meeting and following announcement on monetary policy of the Governing Council of the ECB on March 5th_{The dates of meetings and monetary policy announcements is retrieved from the official}

website of the European Central Bank. The meetings on which no change in interest rate was made are also included, as this is also regarded as a decision on policy. By doing this, the effect of a lack of change is also analyzed. The crisis period used for hypothesis (5) is from March 2009 to June 2013, which is the period also used by Ricci (2015) for his analysis on bank stock returns during the financial crisis.

For the baseline regressions, the EURO STOXX 50 and EURO STOXX 600 indices are both analyzed. In this paper, ‘EURO STOXX’ is abbreviated to ‘STOXX’. The STOXX 50 index provides an overview of the stocks of market leaders across Europe, while the STOXX 600 gives a broader view and includes small, mid-sized and large market capitalization companies. Including the STOXX 600 index is useful for comparing the results for financials and non-financial stocks to the baseline regression.

Figure 1 Figure 2

Figures 1 and 2 provide visual data points for different variables used. The data points correspond with the dates on which the ECB decided on monetary policy. Figure 1 shows STOXX 50 index returns on the y-axis and the surprise part of a rate change in the x-axis. Figures with returns of the other indices used can be found in the appendix.

Figure 2 shows surprise rate changes on the y-axis and total rate change on the x-axis.

Figure 3 shows the ECB interest rate during the sample period of March 1st_{2009 to March 23}rd

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18 To analyze the difference in effect of monetary policy on financial and non-financial stocks, subsets of the STOXX 600 index are used. The first subset is the STOXX 600 ex Financials index, which excludes companies that are allocated to the Financials industry, following the Industry Classification Benchmark (FTSE, 2020). The second subset used is the STOXX 600 Financials index, which only includes stocks that are allocated to the Financials industry, according to the Industry Classification Benchmark. Data for the return of the indices, for the continuous Euribor futures data and for the MSCI World ex Europe index was retrieved from FactSet. Table 1 provides descriptive statistics for the data used.

Variable Observations Mean SD Minimum Maximum

STOXX 50 Return 79 0.143% 1.800% -4.69% 5.67% STOXX 600 Return 79 0.140% 1.468% -3.60% 4.94% STOXX 600 Financial Services 79 0.226% 2.185% -7.77% 8.66% STOXX 600 excluding Financials 79 0.125% 1.350% -3.33% 4.16% Total Rate Change 79 0.123% 0.254% -0.40% 0.75% Surprise Change 79 0.005% 0.043% -0.09% 0.17% Expected Change 79 -0.009% 0.079% -0.36% 0.25%

Table 1: Descriptive statistics for variables used. Observations are days on which the Governing Council of the ECB met to make decisions on monetary policy. N = 79.

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19

5 Results

5.1 Baseline regression using only complete rate change

Table 2 provides results for the baseline regression (1) with only the complete rate change of the ECB, following the approach by Bernanke and Kuttner (2005), using robust standard errors and using returns on the MSCI World ex Europe index as a control variable for global stock market movements.

From this regression it can be concluded that a rate change in itself does not have any significant effect on both index returns, which is in line with the conclusion of Bernanke and Kuttner (2005) for the US environment. Now that the total change is used, this total change is split up into an unexpected and expected part, following the methodology of Bernanke (2001).

5.2 Regression results using unexpected and expected rate changes

The findings in Table 2 are consistent with the first hypothesis and with the findings of Bernanke and Kuttner (2005) for the US environment. Unexpected rate changes are found to have a significantly negative effect on stock market returns in Europe, which is in line with the hypothesis that unexpected rate changes should affect stock market returns, while expected changes do not have a significant effect on stocks, which is in line with the hypothesis that due to market efficiency, stock market returns should not be significantly affected by rate changes that were expected. Because for the unexpected part, this paper expects a negative relationship, the

Regressor STOXX 50 STOXX 600

(1) (2) (1) (2)

Intercept -0.0000946

(0.0012268) (0.0012123) -0.0000006 -0.0000744 (0.001061) (0.0009986) 0.000161

Total rate change 0.1428418

(1.202719) - -0.4336161 (1.052957) - Expected rate change - -0.29112799 (1.190061) - -0.8339821 (1.023895) Unexpected rate change - -5.064193* (2.914558) - -5.235771** (2.409057) MSCI ex Europe 1.26904*** (0.1117649) 1.307053*** (0.1167929) 1.025303*** (0.0940742) (0.1076893) 1.06036*** R2 _0.6589 _0.6707 _0.6388 _0.6539

Table 2: Regression results for baseline equation (1) and equation with distinction between expected and unexpected changes (2). Sample consists of 79 ECB Governing Council meetings on monetary policy in the period from March 1st_{2009 to March 23}rd_2016.

Significance on a 10% level is denoted with *, on a 5% level with ** and on a 1% level with ***. Value in parentheses is the robust standard error.

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20 hypothesis can be tested one-sided and for both indices, a 5% significance if found. From this, it can be concluded that when monetary policy is not expected, this paper finds a significant negative effect of this on stock market returns, which means that contractionary monetary policy results in a decrease in stock market returns in Europe. However, when monetary policy is expected, these actions do not have any effect on stock market returns in Europe. These results extend earlier findings for the US environment into the European environment and provide interesting conclusions for future monetary policy decisions by the European Central Bank.

5.3 Financial and non-financial stocks

Table 3 shows regression results for Non-Financial stocks, regressed by taking the baseline regression with STOXX 600 ex Financials index subset returns as the dependent variable, and Financial stocks, done by running the same baseline regression with STOXX 600 Financials index subset returns as the dependent variable.

Looking at non-financial stocks, the same results as for the baseline regression are found, namely a significant (10%) effect of unexpected rate changes on the index return and an insignificant effect of expected rate changes on the index return, which means that contractionary policy with rising interest rates results in a decrease of stock market returns, when financials are not included. Changing the focus from non-financials stocks to financial stocks, no significant effect can be found in both regressions, which leads to the conclusion that monetary policy does not have an effect on the returns of financial stocks. This result contradicts with earlier research, which suggests that financial stocks should be significantly influenced by monetary policy actions. As no other papers

Regressor Non-Financials Financials

(2) (2) Intercept 0.0000927 (0.0010168) (0.0013462) 0.0006614 Expected rate change -1.159573 (0.7950386) (2.711005) 0.6791152 Unexpected rate change -5.391673** (2.510352) -4.124339 (3.77996) MSCI World ex Europe 0.934796*** (0.106868) 1.577399*** (0.1792467) R2 0.5956 0.6779

Table 3: Regression results for STOXX 600 ex Financials and STOXX 600 Financials returns. Sample consists of 79 ECB Governing Council meetings on monetary policy in the period from March 1st_{2009 to March 23}rd_{2016. Significance on a 10% level is denoted}

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21 exist that specifically look at financial stocks in Europe and this paper finds contradictory results when compared to earlier research, this provides scope for further research on this topic.

5.4 Difference between crisis and non-crisis period

Table 4 shows the results for equation (3), which includes a crisis dummy and interaction variables for unexpected and expected rate changes in the crisis period, defined as the period from March 2009 to June 2013. The results confirm hypothesis (5), namely that an unexpected rate change in the crisis period has a different effect on stock market returns than in the non-crisis period. This is shown statistically by the high significance of the unexpected rate change in crisis period interaction variable CRIUN (1% significance) for all indices. When looking at the values of the estimators, it can be concluded that in a non-crisis period, unexpected rate changes have a very significant negative effect on stock market returns. In crisis periods, however, this negative relationship tends to almost completely reverse, and stock index returns do not react very significantly to unexpected rate changes. This result can be of importance for future monetary policy decisions in crisis periods and provides scope for future research on the effect of monetary

Regressor STOXX50 STOXX600 Non-Financials Financials

(3) (3) (3) (3)

Intercept 1.223753

(0.0021124) (0.0018247) 0.0019503 (0.0018148) 0.0019692 (0.0021748) 0.0022896

Expected rate change -0.4440106

(3.527356) (2.948919) 3.19621 (2.604751) 4.561182* (4.643627) -1.664583 Unexpected rate change -34.00384*** (57.892355) -24.67346*** (6.165039) -24.39689*** (5.557878) -27.9218*** (10.16847) Crisis dummy -0.0032176 (0.0024411) (0.0020559) -0.0027715 (0.0020356) -0.0028076 (0.0026966) -0.0029283 Unexpected change and crisis interaction

34.55423***

(8.54839) (6.739002) 23.9502*** 23.71611*** (6.20184) (10.96919) 28.0925***

Expected change and crisis interaction

0.3017989

(3.712508) -4.117723 (3.13745) -5.886656** (2.729156) (5.417772) 2.565085

MSCI World ex Europe 1.223753***

(0.1120528) 0.9884448*** (0.0962526) 0.8577024*** (0.092267) 1.517102*** (0.1787335)

R2 0.7513 0.7448 0.7208 0.7093

Table 4: Regression results for equation (3), with STOXX 50, STOXX 600, STOXX 600 ex Financials and STOXX 600 Financials returns as dependent variables. Sample consists of 79 ECB Governing Council meetings on monetary policy in the period from March 1st

2009 to March 23rd_{2016. Significance on a 10% level is denoted with *, on a 5% level with ** and on a 1% level with ***. Value in}

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22 policy in other crisis and bear market periods, such as the one after the Brexit referendum and the Covid-19 crisis.

6 Conclusions

This paper tries to find an answer to the question: What is the effect of the monetary policy of the ECB on stock markets in Europe distinguishing between expected and unexpected policy actions, are these effects larger for financial stocks than for non-financial stocks and is the effect of unexpected rate changes different in crisis periods than in non-crisis periods?

The baseline regression results indicate that a rate change by the ECB does not have an effect on stock market returns. This result is in line with what theory about efficient markets predict (Fama, 1970) and with earlier research by Bernanke and Kuttner (2005) and Haitsma et al. (2016). The regression with separate estimators for expected and unexpected changes also show an insignificant effect of expected rate changes on stock market returns.

The results reject the second null hypothesis and find a significant effect of unexpected monetary policy on stock market returns, namely a significant negative effect of changes in interest rates on monetary policy. The methodology of Kuttner (2001) was used to distinguish unexpected policy actions and the results show that these unexpected changes contribute to the returns on the stock market in Europe. This result is in line with earlier research by Basitha and Kurov (2008), Ehrmann and Fratszcher (2004), Kholodilin (2009), Haitsma et al. (2016) and Thorbecke (1997).

Contradictory to the findings of Haitsma (2016), Kholodilin (2009), and Ehrmann and Fratschzer (2004), this paper does not find any significant effect of monetary policy on financial stock returns. However, when analyzing the baseline regression with only the total change as an independent variable, a more significant effect of monetary policy on the index can be seen than when financial stocks are included. This is remarkable, because when looking at earlier findings by Kholodilin (2009), Haitsma et al. (2016), Ehrmann and Fratszcher (2004) and Bredin et al. (2009), one would expect that the significance of the effect of ECB policy on financial stocks would lead to a decrease of significance when these stocks are excluded from the data sample.

The hypothesis of this paper was that because of the perceived interest-rate sensitivity of demand of financials (such as banks and insurance companies) and their dependence on interest rates for their business models, interest rate changes by the central bank would hit their returns harder than the returns of non-financials stocks (Landier et al, 2013). However, the results do not confirm this hypothesis. One reason for this could be that the financial crisis covers a big part of the sample period used, and that according to Ricci (2015), conventional methods have less of an impact on financial stocks during the financial crisis. Another explanation could be that in low interest rate environments, banks’ stock value declines, particularly because banks are reluctant to pass on negative interest rates to customers, which increases their cost for funding and their

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23 profitability (Heider et al., 2019). Because of this remarkable result, further research on this topic would be interesting.

One of the limitations of the baseline regressions is the sample period used. The euro crisis covers a rather large part of this sample period, which might distort some findings. Basistha and Kurov (2008) and Kontonikas et al. (2013) find that stock returns react differently during crisis periods and bear markets, which might expose problems for the external validity of this paper, when applied to ‘normal’ times. This paper tries to address this limitation by testing the difference in stock returns in the crisis period of March 2009 to June 2013 compared to the non-crisis period of June 2013 to the end of the sample period. From the results found, it can be concluded that there is a significant difference in the way that stock indices react to unexpected rate changes in the crisis period compared to the non-crisis period, namely that stock returns tend to react far more significantly during the non-crisis period than during the crisis period, which is in line with what which is in line with the findings of Kontonikas et al. (2013) for the US environment and that of Ricci (2015) in the European environment.

When looking at crisis and non-crisis periods separately, another limitation will come into play, because the separate sample periods are smaller, which could distort some findings. Future research could cover a longer sample period and include other crisis and bear market periods, like the aftermath of the Brexit referendum and the Covid-19 crisis. A second limitation is that the crisis in the period around 2010 has different causes than crises we are dealing with today, like the ones mentioned in the previous sentence. Because this is the case, this could pose problems to external validity.

Another limitation of this paper is that only interest rate changes were included in the sample of monetary policy changes, further research could include other (unconventional) monetary policy actions, such as forward guidance or quantitative easing. Haitsma et al. (2016) and Ricci (2015) show that these unconventional methods have different effects on stock market returns than conventional methods, like the ones used in this paper.

Despite these limitations, this paper provides evidence on the effects of monetary policy on stock market returns in Europe, while also analyzing differences between financial and non-financial stocks and differences between the crisis and non-crisis period. The findings in this paper can be used in future monetary policy decisions and can help to make specific decisions for specific circumstances. Besides this, the paper makes contributions for future analysis into the effect of monetary policy on the financial sector and in bear market periods.

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24

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8 Appendices

Appendix A

ECB Governing Council policy meetings Change in interest rate

March 5th, 2009 -0.50% April 2nd, 2009 -0.25% May 7th, 2009 0% June 4th, 2009 0% July 7th, 2009 0% August 8th, 2009 0% September 3rd, 2009 0% October 8th, 2009 0% November 5th, 2009 0% December 3rd, 2009 0% January 14th, 2010 0% February 4th, 2010 0% March 4th, 2010 0% April 8th, 2010 0% May 6th, 2010 0% June 10th, 2010 0% July 8th, 2010 0% August 5th, 2010 0% September 2nd, 2010 0% October 7th, 2010 0% November 4th, 2010 0% December 2nd, 2010 0% January 13th, 2011 0% February 3rd, 2011 0% March 3rd, 2011 0% April 7th, 2011 0.25% May 5th, 2011 0% June 9th, 2011 0% July 7th, 2011 0.25% August 4th, 2011 0% September 8th, 2011 0% October 6th, 2011 0% November 3rd, 2011 -0.25% December 8th, 2011 -0.25% January 12th, 2012 0% February 9th, 2012 0% March 8th, 2012 0% April 4th, 2012 0% May 3rd, 2012 0% June 6th, 2012 0% July 5th, 2012 -0.25% August 8th, 2012 0% September 9th,, ₂₀₁₂ _0% October 4th, 2012 0% November 8th, 2012 0% December 6th, 2012 0% January 10th, 2013 0%

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28 February 7th, 2013 0% March 7th, 2013 0% April 4th, 2013 0% May 2nd, 2013 0% June 6th, 2013 0% July 4th, 2013 0% August 1st, 2013 0% September 9th, 2013 0% October 2nd, 2013 0% November 7th, 2013 0% December 5th, 2013 0% January 9th, 2014 0% March 6th, 2014 0% April 3rd, 2014 0% May 8th, 2014 0% June 5th, 2014 -0.10% July 3rd, 2014 0% August 7th, 2014 0% September 4th, 2014 -0.10% October 10th, 2014 0% Novembber 6th, 2014 0% December 4th, 2014 0% January 22nd, 2015 0% March 5th, 2015 0% April 15th, 2015 0% June 3rd, 2015 0% July 16th, 2015 0% September 3rd, 2015 0% November 22th, 2015 0% December 3rd, 2015 -0.10% January 21th, 2016 0% March 10th, 2016 -0.10%

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29

Appendix B

EURO STOXX 50 Constituents

Diageo plc Bayer AG

British American Tobacco p.l.c. BASF SE

HSBC Holdings Plc Allianz SE

Unilever PLC Daimler AG

Prudential plc Unilever NV

Rio Tinto plc Sanofi

Vodafone Group Plc Banco Santander S.A.

Reckitt Benckiser Group plc Siemens AG

RELX PLC Deutsche Telekom AG

BP p.l.c. ASML Holding NV

Lloyds Banking Group plc Zurich Insurance Group Ltd

GlaxoSmithKline plc Novo Nordisk A/S Class B

AstraZeneca PLC AXA SA

National Grid plc Novartis AG

Air Liquide SA ABB Ltd.

Airbus SE Roche Holding AG

L'Oreal SA Nestle S.A.

LVMH Moet Hennessy Louis Vuitton SE Enel SpA

Safran S.A. Eni S.p.A.

Intesa Sanpaolo S.p.A. ING Groep NV

Anheuser-Busch InBev SA/NV BNP Paribas SA Class A

VINCI SA Royal Dutch Shell Plc Class A

Schneider Electric SE Iberdrola SA

SAP SE UBS Group AG

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30

Appendix C

EURO STOXX 600

Constituents Prosus N.V. Class N Electrolux Professional AB Class B Brenntag AG GEA Group Aktiengesellschaft Roche Holding AG

LANXESS AG Bollore SA Adecco Group AG

Telefonica Deutschland

Holding AG Mediobanca S.p.A. LafargeHolcim Ltd.

EXOR N.V. Compagnie Generale des

Etablissements Michelin SCA Tecan Group AG Banco de Sabadell SA Danske Bank A/S Clariant AG

Carnival plc Genmab A/S Nestle S.A.

freenet AG Continental AG Baloise-Holding AG

MTU Aero Engines AG OC Oerlikon Corporation AG LPP S.A.

Banco BPM SpA Deutsche Post AG Equinor ASA

Orion Oyj Class B Siemens Gamesa Renewable Energy, S.A.

JC Decaux SA InterContinental Hotels

Group PLC Nokian Renkaat Oyj Skanska AB Class B

LEG Immobilien AG Norsk Hydro ASA Enel SpA

Raiffeisen Bank International AG

OMV AG Eni S.p.A.

Aggreko plc VERBUND AG Class A Amplifon S.p.A.

ITV PLC Pargesa Holding SA Temenos AG

Helvetia Holding Ltd Pernod Ricard SA Logitech International S.A.

Experian PLC Renault SA Santander Bank Polska SA

Telecom Italia S.p.A. Rubis SCA ING Groep NV

Euronext NV TOMRA Systems ASA Sonova Holding AG

IWG Plc Telenor ASA Davide Campari-Milano S.p.A.

Julius Baer Gruppe AG Remy Cointreau SA Kuehne & Nagel International AG

Chr. Hansen Holding A/S Merck KGaA Straumann Holding AG Elia Group SA/NV Anheuser-Busch InBev

SA/NV Mapfre SA

Rightmove plc Sartorius Stedim Biotech SA Credit Suisse Group AG Standard Life Aberdeen PLC SKF AB Class B Swatch Group Ltd. Bearer

WPP Plc Saipem S.p.A. Lundin Energy AB

Aroundtown SA RWE AG EssilorLuxottica SA

G4S plc Schibsted Asa Class A bioMerieux SA

Loomis AB Class B SEB SA Snam S.p.A.

Galapagos NV Sika AG Credit Agricole SA

John Wood Group PLC Skandinaviska Enskilda Banken AB Class A

ageas SA/NV

Bankia, S.A. VINCI SA Boliden AB

Telenet Group Holding NV Sofina SA CD Projekt S.A.

SalMar ASA Solvay SA BNP Paribas SA Class A

Deutsche Wohnen SE SGS SA Fabege AB

Antofagasta plc Flutter Entertainment Plc Alfa Laval AB Ashtead Group plc Schneider Electric SE Lonza Group AG

Severn Trent Plc Vivendi SA Schindler Holding AG Pref

(31)

31 Signature Aviation Plc Swedbank AB Class A Compagnie de Saint-Gobain

SA

Barratt Developments PLC Storebrand ASA Enagas SA Bellway p.l.c. Svenska Cellulosa

Aktiebolaget Class B

Wendel SE

British Land Company PLC Trelleborg AB Class B Melrose Industries PLC

Tullow Oil plc Total SA Atlantia S.p.A

Bunzl plc Altran Technologies SA Royal Dutch Shell Plc Class A

AVEVA Group plc Air France-KLM SA Hera S.p.A.

easyJet plc Valeo SA Sodexo SA

Capita plc Volvo AB Class B Informa Plc

Diploma PLC E.ON SE Wirecard AG

Aviva plc voestalpine AG ams AG

Croda International Plc Holmen AB Class B Dufry AG

Diageo plc Swedish Match AB Bolsas y Mercados Espanoles

Schroders PLC UPM-Kymmene Oyj Tryg A/S

DCC Plc PUMA SE AAK AB

BAE Systems plc Tele2 AB Class B Scor SE

Derwent London plc Bayer AG Indutrade AB

British American Tobacco p.l.c.

Stora Enso Oyj Class R Elekta AB Class B Man Group PLC Henkel AG & Co. KGaA Pref Ipsen SA

Electrocomponents plc BASF SE Koninklijke DSM N.V.

Spectris plc Beiersdorf AG Hikma Pharmaceuticals Plc

Getlink SE Hochtief AG Electricite de France SA

Greggs plc HeidelbergCement AG Grifols, S.A. Class A Halma plc Fresenius Medical Care AG &

Co. KGaA

Hargreaves Lansdown plc Hammerson plc Interpump Group S.p.A. ICA Gruppen AB

Standard Chartered PLC ASM International N.V. Iliad SA

Hays plc Orange SA GALP Energia SGPS SA Class

B

Next plc Sampo Oyj Class A Britvic plc

Hiscox Ltd Randstad NV TGS-NOPEC Geophysical

Company ASA

Imperial Brands PLC Allianz SE SES SA FDR (Class A)

Intermediate Capital Group

plc Castellum AB SBM Offshore NV

IMI plc Royal Ahold Delhaize N.V. Neste Corporation

Johnson Matthey Plc Hermes International SCA Ferrovial, S.A.

JD Sports Fashion Plc Subsea 7 S.A. Partners Group Holding AG Anglo American plc KGHM Polska Miedz S.A. Admiral Group plc

Compass Group PLC NIBE Industrier AB Class B Powszechna Kasa

Oszczednosci Bank Polski SA

HSBC Holdings Plc Endesa S.A. Proximus SA de droit public

Howden Joinery Group PLC Deutsche Lufthansa AG Legrand SA

Legal & General Group Plc Erste Group Bank AG Husqvarna AB Class B

Centrica plc Munich Reinsurance

Company ENGIE SA

Unilever PLC Alstom SA Mondi plc

Meggitt PLC Dassault Systemes SA EutelsVarianceat

The effect of the ECB's monetary policy on stock market returns in Europe