INTERNATIONAL SANCTIONS and THEIR EFFECT on the STOCK MARKET Did International Sanctions Affect the Russian Stock Market During the Ukraine Crisis?

INTERNATIONAL SANCTIONS AND THEIR EFFECT ON THE STOCK MARKET Did International Sanctions Affect the Russian Stock Market during the Ukraine Crisis?

Name: Iris Mulkens, MSc ANR: 232670 SNR: U1259073

Submission date: 24-11-2018

Supervisor: prof. dr. B.J.M. Werker

Management Summary This paper investigates the effect of international sanctions on the Russian stock market during the Ukraine Crisis. International sanctions are defined as actions attempting to force another country into adjusting their behavior towards a desired behavior. In this study, they are sanctions that are declared by the US or the EU during the Ukraine crisis.

A review of existing literature revealed that the Russian economy and the Russian stock market were impacted by the Ukraine crisis. The Ukraine Crisis had a negative impact on the Russian rouble, the amount of capital available and the interest rates. Combined, the negative impact on these factors also forced many Russian companies to limit their investment projects.

This study’s empirical research investigated the effect of international sanctions on the Russian stock market. More specifically, the impact of Ukraine Crisis related international sanctions on the stock market’s price level and trading volume were studied. The first tests investigated whether abnormal returns on the Russian stock market in the event period, where the event period included the sanction announcement day, were significantly different from 0. These tests did not provide enough evidence to conclude that the Ukraine Crisis related international sanctions affected the price level of the Russian stock market. To check whether external factors influenced the tests, control variables were added to control for the day-of-the-week effect. The controlled tests did not lead to a different conclusion regarding the effect of international sanctions on the price level of the Russian stock market. Next, the effect of international sanctions on trading volume was tested. These tests revealed that international sanctions have a positive effect on trading volume. The effect became smaller for event windows that included more days after the announcement date. Sanction related events also had a positive effect on trading volume, though the effect was smaller and less significant. To control for the day-of-the-week effect, controlled tests on the effect of international sanctions on trading volume were also conducted. In the controlled environment, the effect increases compared to the uncontrolled tests’ results, but only very slightly.

1 Table of Contents Management Summary 1

Table of Contents 2

1. Introduction 3 1.1 Problem Indication 3 1.2 Research Question 3 1.3 Structure 3

2. Review of Current Literature 4 2.1 What are International Sanctions? 4 2.2 International Conflicts and their Effect on Stock Markets 4 2.3 International Sanctions and their Economic Influence 5 2.4 The Ukraine Crisis 5 2.5 Russia during the Ukraine Crisis 6

3. Methods 7 3.1. Research Design 7 3.2 Data Collection 7 3.3 Data Analysis 10

4. Results 14 4.1 Data description 14 4.2 Trading Volume Transformed 15 4.3 Testing Abnormal Returns 15 4.4 Testing Abnormal Returns Controlled 16 4.5 Testing Trading Volume 17 4.6 Testing Trading Volume Controlled 19

5. Robustness checks 22 5.1 Adding Restrictions on Estimation Window 22 5.1 Robust Regressions 24

6. Conclusion 27 6.1 Review of Current Literature Concluded 27 6.2 Empirical Study Concluded 27 6.3 Research Question Answered 28 6.4 Implications 28 6.5 Discussion 29

References 31 Appendix 33

2 1. Introduction 1.1 Problem Indication Sanctions against Russia during the Ukraine Crisis have contributed to a fast deterioration of the economic situation in Russia since 2014 (Nelson, 2015). As a result of the Ukraine Crisis and its international sanctions, Russia has seen accelerated capital flight. The Russian ruble has depreciated strongly and inflation has significantly increased. Though there have been other events that may have simultaneously affected the Russian economy, there is no doubt that international sanctions and the Ukraine Crisis have had a negative impact.

Some researchers have studied the effects international sanctions have on their target’s economy. Others have focussed on the effects they have on other aspects of the target country. Additionally, there have been studies that looked at the effects international sanctions can have on the country that is imposing the sanctions. The effect of the Ukraine Crisis on Russia in general and the Russian economy specifically has also been studied by researchers. This study specifically aims to investigate the effect of international sanctions during this crisis, on the Russian stock market.

1.2 Research Question Given the large impact the Ukraine Crisis had on the Russian economy, the fact that it has affected the stock market is not surprising. But did the international sanctions individually affect the stock market? To investigate this in the case of Russia during the Ukraine Crisis, I propose to find an answer to the following question:

What was the effect of international sanctions on the Russian stock market during the Ukraine Crisis?

This research question will be investigated by looking at current literature on the topic. An empirical study will be used to explore the effect of Ukraine Crisis related international sanctions on the Russian stock market price level and on trading volume in the Russian stock market.

1.3 Structure The first step to answering the research question will be a review of current literature on international sanctions and the Ukraine Crisis. This will shed light on the effect of international sanctions on stock markets as well as financial and economic environments in general. It will also give a preliminary overview of the situation in Russia during the Ukraine Crisis. After this literature review, an empirical data analysis will examine the effect of international sanctions on the Russian stock market during the Ukraine Crisis specifically. First, the research methodology will be explained, after which the data analysis and its results will be presented. Finally, some steps that were taken to improve the reliability of the study will be explained and the research will be concluded.

3 2. Review of Current Literature 2.1 What are International Sanctions? International sanctions can broadly be defined as actions attempting to coerce another country into adjusting their behavior towards a desired behavior (Cranmer, Heinrich & Desmarais, 2014). In this definition, the desired behavior is behavior that is in line with international rules and laws and a state of peace and security (Ćwiek-Karpowicz & Secrieru, 2015). Sanctions are initiated by one or more international actors, who are called senders. They pursue these actions against one or more others, the receivers (Carter, 1988).

The most important organ in terms of global peace and security is the Security Council, which is one of the principal organs of the United Nations (UN). It is their responsibility to determine the existence of a threat to peace or act of aggression. The Security Council will call upon peaceful settlement in case of a dispute. It may resort to imposing sanctions or even authorize the use of force to maintain or restore international peace and security (The Security Council, n.d.). Besides the UN Security Council, individual countries or groups of countries may also extend sanctions. Since the UN Security Council has strict protocols for imposing sanctions, the process can take quite long. Therefore, autonomous sanctions by individual countries or groups of countries may be used when the Security Council is not able to impose sanctions quickly enough or even at all. Two important autonomous entities who have declared sanctions against Russia in the Ukraine Crisis are the United States (US) and the European Union (EU).

For the purpose of this study, international sanctions will be defined as sanctions that are declared by the Security Council, the US or the EU. The timing of a sanction will be determined by the official declaration date of the entity that has declared the sanction.

2.2 International Conflicts and their Effect on Stock Markets Typically, international sanctions are part of a wider international conflict. International sanctions are imposed to change a country’s behavior into a more favorable one. They are used to prevent the escalation of international conflicts into warfare or to support peace efforts in times of international conflict. International conflicts generally influence a country’s economy, which is an effect that scholars have tried to unravel for a long time.

Schneider and Troeger (2006) have tried to find out how stock markets react to international conflict. They studied the influence of three large political conflicts on global financial markets; the Gulf war and subsequent international interactions with Iraq, the conflicts between Israel and the Palestinians and civil wars in ex-Yugoslavia. Their study was based on time-series analyses using daily stock market data. Their results show that within those specific war regions, global stock market reactions to international conflict are mostly negative.

Brune, Hens, Rieger and Wang (2015) have found some less straightforward effects of international conflict on stock markets. These authors discovered that an increase in the probability of a war outbreak leads to decreasing stock prices, and a decrease in the likelihood of a war increases stock prices.

4 They also found that once a war begins, stock market prices do not decrease further and instead increase significantly. However, this was only true for anticipated war outbreaks. When a war that starts unexpectedly, its outbreak does decrease stock prices.

These are just a few examples of stock market movements during international conflict and warfare. However, we are interested in the specific effect of international sanctions on stock market movements. We will now take a closer look at evidence of how international sanctions influence economies and stock markets globally.

2.3 International Sanctions and their Economic Influence As explained before, the purpose of international sanctions is to compel a country to change its behaviour towards a certain desired behavior. To reach this goal, international sanctions have to have an impact on a country that is great enough for that country to change its behavior.

Caruso (2003) has shown that international economic sanctions have a large negative impact on trade flows. His results show that sanctions have a large negative impact on bilateral trade between the United States and 49 target countries. He explains that the extensiveness of the sanctions plays a role. Only extensive and comprehensive sanctions negatively impact bilateral trade, limited and moderate sanctions do not. Caruso also shows that extensive sanctions imposed by the United States have a large negative impact on trading flows between sanctioned countries and other, non-U.S., G-7 countries.

In a large scale study, Neuenkirch and Neumeier (2015) studied 160 countries of which 67 experienced economic sanctions over the period 1976–2012. Their goal was to investigate whether UN and US sanctions affect a target country’s GDP growth. Their results showed that both UN and US sanctions led to a decrease in target countries’ GDP growth. The sanctions led to an aggregate GDP decrease of up to 25%.

Sanctions may also have economic implications for the countries imposing the sanctions. For example, Hufbauer, Elliott, Cyrus and Winston (1997) have found evidence that sanctions imposed by the US reduce US exports.

2.4 The Ukraine Crisis The fundamentals of the Ukraine Crisis go back to 1991, when the country declared its independence from the USSR. 22 years later, on the 21st of november 2013, Ukraine president Viktor Yanukovych refused to sign an association agreement with the European Union. Instead of creating closer trade ties with the EU, Yanukovych’s cabinet seeked closer cooperation with Russia. This refusal first sparked small protests and on the 30th of november a large demonstration fired up in Ukraine’s capital, Kiev (Ukraine Crisis: Timeline, 2014).

After these initial problems, the Ukraine Crisis developed into a political crisis, where pro-Russian separatists wanted to break up the country by fighting Ukraine forces. Some major events that took place during the crisis are the annexation of Crimea by Russia, the crash of

5 airplane MH17, the Minsk Agreement and the October Parliamentary Elections. During the crisis, the US and the EU have imposed sanctions on Russia. The aim of these sanctions was to convince Russian president Vladimir Putin to stop supporting the Russian separatists in Ukraine (Amadeo, n.d.).

For the purpose of this study, the Ukraine Crisis will be defined as the political unrest surrounding the Ukraine following the breach of the EU association agreement on the 21s of November 2013, and the Russian involvement in this unrest.

2.5 Russia during the Ukraine Crisis The international sanctions on Russia have had economical effects not limited to the stock market. For example, Russia has seen a large depreciation of the rouble. Between january 2014 and december 2014, the rouble has lost 40% of its value. This depreciation was partly due to global developments, such as the global price decrease of oil, but can also partly be attributed to the international sanctions on Russia (Dreger, Kholodilin, Ulbricht & Fidrmuc, 2016). Since many of Moscow’s corporations and banks rely heavily on international financing, their debt repayments are mostly denominated in US dollars and other foreign currencies, while their earnings are in roubles. Because of this, these companies are hit hard by the depreciation of the rouble.

International sanctions have also reduced the availability of capital in Russia. This capital shortage has resulted in higher interest rates, as shown by Russia’s three-month interbanking lending rate which increased immensely, from 6.04% in March 2014 to 10.65% in early December of the same year. These increased interest rates combined with currency depreciation have negatively impacted investments in Russia. Many Russian companies were forced to limit investment projects (Dreyer & Popescu, 2014).

6 3. Methods 3.1. Research Design 3.1.1 Research Type and Timeframe The purpose of this research is to quantitatively measure and understand whether international sanctions during the Ukraine Crisis had an effect on stock market index returns and stock market trading volume. The study used data from the start of 2013 until April 2018. The first event took place on the 3rd of March 2014. To warrant a large enough estimation window before the events, the year 2013 was included as a whole. At the time of data collection, the data for April 2018 were the most recent available data.

3.1.2 Sampling This study aims to investigate the effect of international sanctions during the Ukraine Crisis on the Russian stock market. The sample for this study was determined based on this objective.

International sanctions and the Ukraine Crisis were both defined in chapter two. These definitions were used to determine the sample for this study. International sanctions were defined as sanctions that are declared by the Security Council, the US or the EU. The Ukraine Crisis was defined as the political unrest surrounding the Ukraine following the breach of the EU association agreement on the 21st of November 2013, and the Russian involvement in this unrest. Therefore, the sample for this study consisted of all Ukraine Crisis related international sanctions declared by the Security Council, the US or the EU after the 21st of November 2013.

3.2 Data Collection 3.2.1 Index Data For the purpose of this study, it was necessary to gather data on the Russian stock exchange index. The largest access point for Russian financial market is the Moscow Exchange. This exchange is the main liquidity center for Russian instruments. The Moscow Exchange lists a diverse range of asset classes, including equities, bonds, derivatives and more. The Moscow Exchange originated as a merger of the Moscow Interbank Currency Exchange (MICEX) and the Russian Trading System (RTS) in December of 2011. Both the MICEX index and the RTS index are still traded on the Moscow Exchange and are major benchmarks for the Russian stock market (Moscow Exchange, n.d.). Since december 2017, the MICEX Index trades under the name MOEX Russia Index (Main Equity indices of Moscow Exchange, n.d.).

This research used the MOEX Russia Index, formerly known as the MICEX Index, to examine the impact of international sanctions on the Russian stock market. Data on the MOEX Russia Index was gathered through Datastream. Daily data on the index price level in Russian roubles as well as trading volume and price in Russian roubles of the stocks underlying the index were gathered. Index level data was used to determine return levels.

7 Many financial studies have a preference towards logarithmic returns as opposed to normal returns. I decided to also use logarithmic returns for this study. Returns were calculated using the following formula:

Returns = 100 * log(indext) − log(indext−1)

Where indext is the index level at time t and indext-1 is the index level one day before time t.

Trading volume and price of underlying stocks are multiplied and summed to determine a proxy for trading volume of the index in Russian roubles.

3.2.2 Event Dates To assemble the appropriate dataset for this study, I established a list of events that are considered international sanctions-events. These events were gathered by analysing sanction overviews and announcements from the European Council and the US Office of Foreign Assets Control. No records were found on sanctions imposed by the Securities Council. This should not come as a surprise, since the Security Council is often not able to impose sanctions quickly enough. Therefore, only records of sanctions imposed by the EU and the US are used to collect data on events.

This qualitative search led to 68 event dates. In the process of analysing the sanctions overview and announcements, the events were classified into three groups: Sanctions, Speculations and Extensions. Sanctions are events where new sanctions are imposed on individuals or groups of individuals. Speculations are events that discuss the situation regarding sanctions, but that do not involve the decision to impose new sanctions. An example of a Speculation is the issuance of regulation concerning implementation of previously imposed sanctions. Extensions are extensions of current sanctions, with no changes to the rule of the sanction.

An overview of all sanctions and their respective classification can be found in appendix 1.

When combining the list of events with the index data, it turned out that two of the events occured on a non-trading day. Therefore, these events are excluded from the study.

8 Table 1 shows the number of events per subgroup. Because the speculations and the extensions group are both too small to analyze individually, these two categories were grouped together in the analysis. Together, they will form the group ‘Sanctions Related Events’.

3.2.3 Control Variables To present results that are as reliable as possible, it is important to control for environmental factors that influence the dependent variable but that are not part of the objective of the study. Unfortunately, the context of this study does not give much room to control for these environmental factors, for a few reasons.

First of all, it is not possible to control for firm specific characteristics. Many studies that investigate an effect on stock price or trading volume control for firm specific characteristics, such as firm size. These characteristics have been shown to constantly affect stock prices and trading volumes in a predictable way (Bamber, Barron & Stober, 1997; Chae, 2005; Chen, Hong & Stein, 2001). However, since I am investigating the stock market as a whole, I am not distinguishing between firms.

Finding external influences on trading volume and market index prices that are consistent over time and across markets is challenging. Apart from firms specific effects, such as the size effect, there are very few variables that steadily and reliable predict stock prices and trading volume. There are little variables that consistently predict the movements of market index prices. The lack of reliable predictors for market index prices makes it almost impossible to reliably control for external influences on these index prices. The same is true for trading volume.

However, there is one effect that has persistently shown to influence both the number of shares that are being traded and the price for which they are traded, namely calendar anomalies. Many researchers have shown that calendar anomalies significantly affect trading volume and trading prices, and do so in a consistent way. Calendar anomalies are effects such as day-of-the-week effects and turn-of-the-month effects, where being on a certain point in the calendar influences the stock market. Calendar anomalies are country specific (Zhang, Lai & Lin, 2017). Multiple studies have investigated calendar anomalies in the Russian stock market. Though they do not

9 agree completely on what day of the week has the greatest impact on returns and trading volume, all have shown that in the Russian stock market, a day-of-the-week effect exists (Ajayi, Mehdian & Perry, 2004; Caporale & Zakirova, 2017; Zhang, Lai & Lin, 2017). Therefore, I will run additional regressions controlling for this day-of-the-week effect.

Day of the week data is implicitly already available in the data as it can be deduced from the date variable. Therefore, it is not necessary to collect additional data for this control variable.

3.3 Data Analysis 3.3.1 Cleaning the Data The data gathered through data stream showed some anomalies. Out of 1,390 observations between the beginning of 2013 and the beginning of 2018, there were 57 cases where the index level was exactly equal to the trading day before. This would lead to a return of 0% in the study. To find out whether this was correct or if there was an error in the data, I compared the data to historical data from Yahoo finance. From this, I came to the following conclusion: ● The data for the first 5 days gathered through datastream were identical. It is expected that the data from these dates is corrupt. Since these days are far before the first event, this is not an issue. These 5 corrupted data points represent 4 out of 57 cases, since the first observation is unique and the next 4 are identical. ● In 51 cases, the date with a datapoint that is identical to its predecessor, is completely non-existent in the yahoo finance list. ● In 1 case the date does exist in the yahoo finance list, but has a trading volume equal to 0. ● In 1 case, the reason for an identical index two days in a row is unclear. To make the empirical study as sound as possible, I have dropped all data points that have an observation equal to the day before, except for the case where an explanation cannot be found, since there is no reason to believe this observation is wrong.

Some stocks underlying the trading volume variable had values missing. Stocks that were added to the index during the analyzed period were not taken into account. Other missing data points were replaced with the - at that point - most recent observation. This was done because a trading-stop or measuring inaccuracy in one stock should not impact the trading volume of the entire index, as it does not reflect an event that affects the entire stock market

3.3.2 Method of Analysis To answer the research question, two models were created and statistically tested.

Abnormal Returns Firstly, the impact of international sanctions on the Russian stock market was analyzed by measuring the difference between the actual and the expected returns on the Russian stock market indexes.

10 There were several options to determine normal returns. Since the aim of this analysis was to study the effect on the complete market, market based normal returns were not appropriate. Therefore, I use the Mean Adjusted Return method to determine the benchmark for normal returns.

The estimation window [T1,T2] to track normal returns is equal to [<,-3] and precedes the event period.

The event date, which is the date of the sanction announcement, is equal to t=0. The event period [t1,t2] includes the day of the event and a variable number of days after the announcement: [0,t2]. In the Mean Adjusted Return method, normal returns are equal to:

T 2 NR = 1 ∑ R i T 2−T 1+1 it t=T 1

Where i denotes an event and t is the number of days from the sanction announcement. R it defines the return of the index belonging to a certain event on day t.

After determining normal returns, abnormal returns in the event window are calculated as follows:

ARit = Rit − NRi

When we are looking at an event window of two or more days, the average abnormal returns will be regarded. These are calculated from:

t2 1 AARi = t ∑ ARit t=0

To determine whether international sanctions have an impact on the Russian stock market, I will test the significance of the abnormal returns. If the abnormal returns are significantly different from zero, this would indicate an effect of the event on the index. This leads to the following hypothesis:

H : E(AARi) ≠ 0

The null hypothesis that I am testing therefore is:

H0 : E(AARi) = 0

Stata will determine the test statistic for testing this hypothesis.

11 At a 5% confidence level, the null hypothesis will be rejected if |TS1| > 1.96. At a 10% confidence level ,the critical value is 1.67, which means the null hypothesis of no abnormal performance will be rejected if |TS1| > 1.67. The critical value at a 1% confidence level is equal to 2.58.

To be able to abandon the assumption of normally distributed abnormal returns, which often does not hold for daily stock data, and thus reliably test for significance, N should be larger than 30. In all cases, N was larger than or equal to 30.

Abnormal returns are tested for both groups of events: ‘sanctions’ and ‘sanction related events’. For each group. different event windows are tested: ○ [0]

○ [0,t2] where t is equal to 1, 2, 3 4 and 5

Abnormal Returns Controlled Besides the basic analysis, additional tests included control variables. The purpose behind adding control variables was to control for changes in these variables that might influence abnormal returns, the dependent variables. As explained in paragraph 3.2.3, there is reason to believe a weekday effect exists on the Russian stock market. This means that the day of the week influences abnormal returns. To make sure this effect did not affect the outcome of the regressions, day of the week dummies were added to control for this effect.

Trading Volume Next to returns, I also wanted to find out whether there is an effect of international sanctions on trading volume on the Russian stock market. To find out whether this is the case, I used a linear model that regresses an event window dummy on trading volume. The model is used to examine whether trading volume in the event window is the same as trading volume outside of the event window.

The basic model looks like this:

T rading V olumeit = α + β * dummy event windowi

The event window dummy was created by building a variable that is equal to 1 when an observation is situated within the event window, and is equal to 0 when the observation lies outside of the event window. As noted before, the event date is equal to t=0. The event period

[t1,t2] includes the day of the event and a variable number of days after the announcement: [0,t2]. Therefore:

dummy event window = 1 if t ∈ [0, t2] dummy event window = 0 if t ∈/ [0, t2]

Stata was used to determine α and β coefficients, and their corresponding t-values. These t-values helped determine whether a coefficient was statistically significant.

Within the above model, multiple submodels were tested to distinguish the following characteristics: ● Sanctions and sanctions related events ● Different event windows: ○ [0]

○ [0,t2] where t is equal to 1, 2, 3 4 and 5

Trading Volume Controlled As explained above, adding control variables will improve the reliability of the tests. The model that included the weekday control variables looked as follows:

T rading V olumeit = α + β * dummy event windowi + β * control variablest

Where each control variable was a day-of-the-week dummy:

T rading V olumeit = α + β * dummy event windowi + β * dummy Mondayt + β * dummy T uesdayt + β * dummy W ednesdayt + β * dummy T hursdayt

13 4. Results This chapter will use the results of the data analysis to answer the main research question. First, the data will be described by summarizing the variables. Then, the two models will be tested. The results will be used to answer the main research question

4.1 Data description Before testing the hypothesis, a brief look was taken at the variables and data. Table 2 summarizes the most important characteristics of the major variables after cleaning the data.

Table 3 shows an overview of the distribution of the dummy variables. This overview shows that the observations are relatively equally distributed amongst all days of the week. Some differences between the different weekdays are present. This is expected, as there are some weekdays where there is no trading, such as national holidays.

14 4.2 Trading Volume Transformed As table 2 shows, trading volume originally had a mean of 32.5 million, a minimum value of 9 million and a maximum value of 140 million. In this case, the mean is extremely close to the minimum value, which indicates that the variable trading volume might be skewed to the right. Figure 1 confirms this positive skewness. To enable a more reliable testing environment, the variable trading volume needs to be less skewed. This was achieved by transforming the variable by taking its natural logarithm.

Figure 1, Distribution Graph of Trading Volume Showing Positive Skewness

4.3 Testing Abnormal Returns These first tests investigated whether abnormal returns in the event period are significantly different from 0. The purpose of this test was to determine whether the events - sanctions and sanction related events - affected returns on the Russian stock market. Different event windows were tested. Table 4 shows the results for these tests.

The top part of table 4 shows the results of the sanctions events as defined in chapter 3. These results indicate that the absolute value of the test statistics are not high enough to reject the null hypothesis. This means that there is not enough evidence to conclude that abnormal returns in the event period are not equal to zero. This test did not provide the necessary proof to show that sanctions events have a significant effect on abnormal returns in the event period.

The bottom part of table 4 shows the result for the sanction related events as defined in chapter 3. These results show that none of the coefficients are significant at p > 0.1. The results indicate that there is not enough evidence to conclude that abnormal returns are unequal to zero in the event window of sanction related events.

4.4 Testing Abnormal Returns Controlled As discussed in chapter 3, the weekday effect may impact abnormal returns, and therefore may influence the test results. Hence there may have been an effect that was not found in the tests, because it was offset by the weekday effect. To test whether this was the case, tests were done that included weekday dummies. Table 5 shows the results of these regressions.

Table 5 shows the results for the regressions that include weekday dummies. The results show that in the controlled regressions, the test statistic still is not large enough to indicate a significant result. Therefore, there is not enough evidence to conclude that international sanctions and sanctions related events have a significant effect on abnormal returns.

4.5 Testing Trading Volume After testing the effect of international sanctions on abnormal returns, I have also investigated the relationship between international sanctions and trading volume. This relationship is studied by testing a linear regression of event window dummies on trading volume. The relationship is

17 tested using multiple event windows. It is investigated for both sanctions and sanction related events. Table 6 shows the results for these tests.

Table 6 shows the results of the linear regression between the event window dummy and the natural logarithm of trading volume. The table shows that a significant effect was found of the event window dummy on trading volume.

When the event window is [0], the effect can be explained as follows: when the event window dummy is equal to zero, trading volume is estimated at e^17.24, which is equal to roughly 31 million Russian roubles. Moving from outside the event window to inside the event window, trading volume increases by e^0.21%, which equals 23,4%. This means that trading volume is expected to grow by almost 7 million Russian roubles when moving into the event window.

Table 6 shows that the effect of the event window dummy increases when moving from event window [0] to event window [0,1]. When also including day t=2, the effect decreases but is still significant. The table also shows the further development of the effect when adding more days to the event window. The effect keeps getting smaller when more days are added. However, even when the event window includes days t=0 up to and including day t=5, the effect remains significant.

The bottom part of table 8 shows the results for sanctions related events. Whereas sanctions had the largest effect in event window [0,1], sanctions related events give the largest effect at event window [0]. The effect for sanctions related events is smaller than the effect for sanctions, at about 12.7%, but still significant. The effect decreases with each day that is added to the event window, and its significance also declines. The effect of sanctions related events on trading volume is no longer significant with event window [0,5].

4.6 Testing Trading Volume Controlled Even though the results are already significant in the uncontrolled model, the results may still be influenced by the weekday effect. Table 7 shows the results for the regressions that include day of the week dummies.

The results in table 7 show that the impact of the event window dummy increases slightly when adding day of the week control variables.

20 For sanction events, the effect is .01 higher at event window [0] and [0.1]. For sanctions related events, the effect is .01 higher at event window [0,1] and .02 higher at event window [0,2]. Practically this means that when including control variables, the effect of the event dummy for for example sanction events in event window [0] is 24.6%, where it was equal to 23.4% when the regression was not controlled using the weekday dummies.

The significance of the event window dummy does not change when adding the weekday dummies.

21 5. Robustness checks This chapter describes some steps that were taken to improve the reliability of the study.

5.1 Adding Restrictions on Estimation Window The model dat tests the effect of international sanctions on abnormal returns is tested using an estimation window of [<,-3] to create normal returns. Since our hypothesis assumes that abnormal returns are stable before the event window, this should not give us any problems. However, the model did not return any significant results. To test whether this was caused by the fact that the returns before the event date were not stable, I decided to run additional regressions using a smaller event window of six weeks before the event date: [-33,-3]. The results for these regressions can be found in table 8. As the table shows, this model also did not return any significant results.

In the model that investigates the effect on trading volume, an estimation window was not used since normal returns were not determined. However, to determine whether comparing the event window to a more restricted period would lead to different results, I have performed some additional regressions. For these regressions, I dropped all data after the event window.

By dropping all data after the event window, the event window was only compared to data that came before the event, not any data after the event. I decided to do this since it was not certain how long an effect, if present, would exist. Therefore, comparing the index prices and trading volumes in the event window to those after the event window, may have led to clouded results. By dropping all data after the event window, only the data before the event window served as the comparative period.

22 The results for these analyses can be found in table 9. Though the results are slightly different, they lead to the same conclusions as the ones deduced in chapter 4.

23 5.1 Robust Regressions To make sure the conclusions were valid and not based on results that were affected by the existence of extreme outliers, I have used stata to perform robust regressions. The results for these regressions on abnormal returns are shown in table 10. These results are exactly the same as the results in chapter 4. Therefore, robust regressions did not change the conclusions drawn from the results.

24 Table 11 shows the results of robust regressions of the event window dummy on trading volume. The results in this table are slightly different compared to the results in chapter 4. For the sanction event, the results from the robust regression are exactly the same as they were in the regular linear regression.

25 However, for the sanction related events, the robust regressions show a slightly different picture. Table 12 shows the results of the regular linear regression and the robust regression side by side. In this table, the differences between the two regression types are highlighted in red. As the table shows, the results for the robust regression start losing significance more quickly. At event window [0,1], the coefficient is only significant at the 10% level. At event window [0,2], the coefficient is no longer significant.

26 6. Conclusion The aim of this chapter is to answer the main research question: ‘What was the effect of international sanctions on the Russian stock market during the Ukraine Crisis?’. This chapter reflects on the empirical findings that emerged from the study and puts them in the context of the existing literature of this topic. It also discusses some factors that may have influenced the findings and conclusions.

6.1 Review of Current Literature Concluded From the review of current literature in chapter 2, international sanctions were defined as actions attempting to coerce another country into adjusting their behavior towards a desired behavior. For the purpose of this study, only the sanctions that are declared by the US and the EU were used.

The review revealed a connection between international sanctions and international conflict. Previous studies have uncovered mostly negative effects of international conflicts on stock prices.

Previous studies have shown that international economic sanctions have a large negative impact on trade flows, both between the sender and the target company as well as between the sanctioned country and countries that are not involved in the sanction. It has also been shown that international sanctions imposed by the UN and the US can have a negative effect on the the sanctioned country’s GDP growth. These examples suggest that international sanctions generally have a negative effect on a countries economy.

More specifically, other researchers have suggested a negative impact of international sanctions on the Russian economy, as shown by a depreciation of the rouble, capital shortage and increased interest rates.

6.2 Empirical Study Concluded The research question was answered using two different models. The models were tested and their results were discussed in chapter 4.

The first model investigated whether abnormal returns in the event period were different from 0. The purpose of this model was to examine whether international sanctions had an impact on the Russian stock market price level through testing their effect on the MOEX index price. These tests did not find evidence that abnormal returns were not equal to zero. Therefore, it can be concluded from the first model that there is not enough proof to reject the statement that international sanctions do not have an impact on the MOEX index price and therefore the Russian stock market price level.

The purpose of the second model was to find out whether international sanctions have an effect on trading volume, by testing the linear relationship between the announcement of sanctions and sanctions related events and the natural logarithm of trading volume of the stocks

27 underlying the MOEX index in Russian Roubles. The results have shown a significant positive effect of both sanctions and sanctions related events on trading volume. For sanctions, the largest effect was found when both the announcement day and the day after the announcement were taken into account. After that, the effect decreased but stayed significant when including the days up to one week after the event. For sanctions related events, the largest effect was found when the event window only included the announcement day. The size of the effect decreased with each day that was added to the announcement day. For sanctions related events, the effect’s significance also decreased with each additional day. When including days 0 to 5 in the event window, the effect was no longer significant. Altogether, the results of these tests indicated that international sanctions associated with the Ukraine Crisis had a positive effect on the daily trading volume of the Russian stock market.

6.3 Research Question Answered The aim of this study was to understand whether the announcement of international sanctions associated with the Ukraine Crisis impacted the Russian stock market, and to answer the following question:

What was the effect of international sanctions on the Russian stock market during the Ukraine Crisis?

A review of current literature has shown that international sanctions did impact the Russian economy, by affecting the Russian rouble, the amount of capital available and interest rates in the country. The subsequent empirical study did not provide enough evidence to conclude that the Ukraine Crisis related international sanctions affected the price level of the Russian stock market. However, proof was found that these sanctions affected trading on the Russian stock market. It was shown that international sanctions related to the Ukraine Crisis increased the trading volume on the Russian stock market.

6.4 Implications 6.4.1 Implications for Theory This study adds to the existing literature on international sanctions by revealing aspects of their effect on the Russian stock market. It also adds to existing literature on trading volume determinants, by showing that international sanctions may influence trading volume. However, all findings are specific to the Russian stock market during the Ukraine Crisis. To find out if the results are also applicable in different situations, further studies in different settings are necessary.

6.4.2 Implications for Practice Besides adding to existing research, this study also has implications for practice. If traders on a stock market know that international sanctions influence trading volume, this may influence their behavior and the choices they make in times and markets where international sanctions are likely. However, as mentioned before, the findings from this study currently cannot be applied to

28 other markets. To find out whether the results are more generally applicable, more research is necessary.

6.5 Discussion This section discusses some factors that may have influenced the reliability of the test results and/or the conclusions in this study.

6.5.1 Noise in Returns Models As discussed, the results indicated that there was not enough evidence to prove that international sanctions and sanctions related events during the Ukraine Crisis had an effect on MOEX index returns. While this conclusion could be driven by the fact that there indeed was no effect of these events on the index’s returns, there are other factors that could have caused this lack of significant results.

The fact that no significant results were found may have been caused by a great amount of noise surrounding the analysis. In the analysis, it was assumed that all other factors were constant. In reality however, it is not strange to expect that there were other factors that also influenced index results and therefore clouded the results of the analysis. It may have been the case that these other factors were stronger than the influence of the international sanctions, which might have caused the fact that no significant relationship between international sanctions and index returns was found.

6.5.2 Persistence of Significance of Effect on Trading Volume As discussed in chapter 4, sanctions and sanctions related returns both have a significant positive effect on trading volume. The significance of the effect of sanctions related returns diminishes when the event window broadens, and the effect eventually becomes insignificant. However, while the size of the effect of sanctions on trading volume also decreases, the results remain significant when the event window broadens.

The fact that this is happening is somewhat surprising, as any type of information usually does not have such a long lasting effect on the stock market. This might indicate that international sanctions lead to a permanently higher transaction volume level, as opposed to a temporary rise in the transaction volume. Further research might be able to uncover the reason behind these results.

6.5.3 Measurement choice One variable that may have influenced the tests, and therefore may have led to insignifiant results, was the measurement that was chosen for the tests. The Russian stock market was proxy’d by the major index on the Moscow Exchange, the MOEX Russia Index.

The MOEX Russia Index may have been the wrong proxy for the Russian stock market. For example, it may have been the case that only a select part of the Russian stock market was influenced by the international sanctions. In that case, an industry index may have been more

29 appropriate. Or maybe only large firms were affected, in which case it would may been more appropriate to look at individual, large firms.

6.5.4 Timing Another variable that may have influenced the tests, was the timing of the measurement. The announcement day was taken as the timing of choice. However, this decision may have influenced the tests. In a day, a lot can happen on the stock market. Therefore, looking for example at hourly stock prices may have led to more accurate results.

Moreover, taking the announcement day as the measurement of event time, any information that was already on the market about the sanction was ignored. For example, if it was already known by the general public two days in advance that a sanction would be announced, the stock market reaction may have happened at a different time as well. This may have influenced the results found in this research.

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32 Appendices

APPENDIX 1, List of Events and Classifications Date Institution Sanction Name/Number Sanction or non-sanction Code Sanction Source 140303 EU Foreign Affairs Council meeting Speculation EUNS01 Extraordinary meeting of the Foreign Affairs Council on the situation in Ukraine. "In the absence of de- 1 escalating steps by Russia, the EU shall decide about consequences for bilateral relations between the EU and Russia," stated the Council. The measures may include suspending bilateral talks on visa matters as well as on the New Agreement. In addition, the Council has decided "to remain permanently seized [of the matter], in order to be in a position to take rapidly all necessary measures".

140306 EU Extraordinary meeting of EU Heads of Speculation EUNS02 Extraordinary meeting of EU Heads of State or Government on Ukraine. EU leaders condemned 1 State or Government on Ukraine Russia's actions in Ukraine and decided to start preparing individual restrictive measures (assets freeze and travel bans). 140306 US EO13660 Sanctions EUNS02 Blocking Property of Certain Persons Contributing to the Situation in Ukraine 2 140316 US EO13661 Sanctions Excluded from Study Blocking Property of Additional Persons Contributing to the Situation in Ukraine 2 140317 EU Foreign Affairs Council meeting Sanctions EUS01 Introduction of a first set of restrictive measures against 21 Russian and Ukrainian officials 1 140320 EU European Council meeting Sanctions EUS02 Following the annexation of Crimea and Sevastopol to the Russian Federation, 12 names were added 1 to the list of Russian and Crimean officials subject to EU travel bans and asset freezes. In addition, the European Council cancelled a planned EU-Russia summit and noted that member states will not hold any bilateral regular summits with Russia. EU leaders also requested the European Commission to prepare broader economic and trade sanctions that could be imposed if Russia further destabilised Ukraine. 140320 US EO13662 Sanctions EUS02 Blocking Property of Additional Persons Contributing to the Situation in Ukraine 2 140411 US Office of Foreign Assets Control Sanctions USS04 Pursuant to the authorities it is given under E.O. 13660 (targeting individuals responsible for violating 2 the territorial integrity of Ukraine), OFAC designated an additional 7 individuals and 1 entity, Chernomorneftgaz, to its SDN list. 140415 EU Foreign Affairs Council meeting Sanctions EUS03 The Council decided to strengthen sanctions against persons responsible for misappropriating 1 Ukrainian state funds and targeted additional individuals under the assets freeze and travel ban. 140428 US Office of Foreign Assets Control Sanctions USS05 Pursuant to the authorities it is given under E.O. 13661, OFAC designated 7 individuals and 17 entities 2 to the SDN list. 140508 US Office of Foreign Assets Control Speculation USNS01 Set of regulations issued by OFAC to implement E.O. 13660, E.O. 13661, and E.O. 13662 2 140512 EU Foreign Affairs Council meeting Sanctions EUS04 Agreement on a new set of sanctions. In light of events in Eastern Ukraine and the illegal confiscation of 1 entities in Crimea, the Council agreed on a new set of sanctions and took note of the preparatory work done by the Commission and Member States on possible targeted measures, as requested by the European Council in March. 140620 US Office of Foreign Assets Control Sanctions USS06 The United States adds an additional 7 individuals to the OFAC SDN list pursuant to E.O. 13660, most 2 of them targeted for being involved in separatist activities in eastern Ukraine. The most notable targeted individual is separatist leader Igor Strelkov. 140623 EU Foreign Affairs Council meeting Sanctions EUS05 Import ban on goods from Crimea. The Council adopted measures to implement the EU's policy of non- 1 recognition of the illegal annexation of Crimea. Goods originating from Crimea or Sevastopol may not be imported into the EU unless they have been granted a certificate of origin by the Ukrainian authorities. 140626 EU European Council Speculation EUNS03 Regarding sanctions, the European Council is committed to reconvene at any time to adopt further 1 significant restrictive measures if a detailed list of concrete steps are not taken by Russia and the separatists by Monday 30 June 140716 EU Special meeting of the European Council Sanctions EUS06 EU leaders regretted that Russia and the separatists had not taken the requested steps set out in the 1 June European Council conclusions. They agreed to target Russia with a new set of 6 restrictive measures including restriction on economic cooperation with Russia. 140716 US Office of Foreign Assets Control Sanctions EUS06 OFAC introduces the Sectoral Sanctions Identifications (SSI) List for the purposes of applying tailored, 2 “sectoral” sanctions to a number of entities in accordance with E.O. 13662, which was issued on March 20, 2014. OFAC also added 4 new individuals, including Alexander Borodai, and 11 entities to its SDN list. Of the 11 entities listed, 8 are state companies active in the Russian military/defense sector, including Kalashnikov Concern, which produces the iconic AK-47. 140718 EU European Council Speculation EUNS04 As agreed by the European Council of 16 July, the Council has today widened the legal basis for EU 1 restrictive measures in view of the situation in Ukraine. 140722 EU Foreign Affairs Council meeting Speculation EUNS05 The Council asked for an acceleration of the preparation of the measures agreed at the special meeting 1 of the European Council on 16 July. A list of entities and persons falling under the enhanced criteria adopted by the Council on 18 July should be established immediately. 33 140725 EU European Council Speculation EUNS06 The Council today adopted reinforced EU sanctions in view of the situation in Ukraine, following up on 1 the request by the European Council of 16 July and the Foreign Affairs Council of 22 July. This decision gives legal value to an agreement reached at the Committee of Permanent Representatives yesterday.The Council also widened the designation criteria in the legal basis for the restrictive measures. This paves the way for imposing asset freezes and visa bans on persons and entities that actively support or are benefiting from Russian decision makers responsible for the annexation of Crimea or the destabilisation of Eastern Ukraine. 140729 EU European Council Sanctions EUS07 Today the European Union has agreed a package of significant additional restrictive measures targeting 1 sectoral cooperation and exchanges with the Russian Federation 140729 US Office of Foreign Assets Control Sanctions EUS07 OFAC designates United Shipbuilding Corporation to the SDN List pursuant to E.O. 13661, and 2 designates 3 entities – Bank of Moscow, Russian Agricultural Bank, and VTB Bank – to the SSI list under Directive 1. 140730 EU European Council Sanctions EUS08 The Council today adopted further EU restrictive measures in view of the situation in Eastern Ukraine 1 and the illegal annexation of Crimea. 140731 EU European Council Sanctions EUS09 The Council today adopted EU restrictive measures in view of Russia's actions destabilising the 1 situation in eastern Ukraine. This decision gives legal value to an agreement reached at the Committee of Permanent Representatives on Tuesday 29 July and announced by European Council President Herman Van Rompuy and Commission President José Manuel Barroso. 140830 EU Special meeting of the European Council Speculation Excluded from Study President Poroshenko of Ukraine attended part of the meeting and informed EU leaders in details about 1 the recent dramatic escalation of the situation. All efforts need to be made to stop violence on the ground, the EU Council is extremely concerned by the presence and actions of Russian armed forces on the Ukrainian territory. In July, the European Council already approved the adoption of significant economic sanctions against Russia. It now stands ready to take further steps in the light of the evolution of the situation on the ground. The European Council has asked for these new sanctions to be ready for adoption within a week. 140912 EU European Council Sanctions EUS10 A new package of restrictive measures targeting exchanges with Russia in specific economic sectors 1 entered into force, reinforcing the measures adopted on 31 July. 140912 US Office of Foreign Assets Control Sanctions EUS10 OFAC issues an amended Directive 1 reducing the maturity term for dealings in new debt of the 2 relevant sanctioned entities (operating in the Russian banking/financial sector) from 90 to 30 days. Furthermore, OFAC also issues Directives 3 and 4, which lay out tailored restrictions for entities deemed to be operating in the Russian military/defense and oil/gas sectors, respectively. OFAC also added 5 entities, all of which operate in the military/defense sector in Russia, to the SDN list, including JSC Concern Almaz Antey, which had been blocked by the EU in July 2014. 141117 EU Foreign Affairs Council meeting Speculation EUNS08 Ukraine was the main focus of the Foreign Affairs Council. EU ministers asked the European External 1 Action Service (EEAS) and the European Commission to present a proposal on further sanctions against separatists. 141128 EU European Council Sanctions EUS11 As requested by the Foreign Affairs Council of 17 November, an asset freeze and an EU travel ban 1 were imposed to 13 persons and five entities involved in action against Ukraine's territorial integrity.

141209 US EO13685 Sanctions USS10 Blocking Property of Certain Persons and Prohibiting Certain Transactions With Respect to the Crimea 2 Region of Ukraine 141218 EU European Council meeting Speculation EUNS09 EU leaders discussed the situation on the eastern borders of Europe, support to Ukraine and relations 1 with Russia. They welcomed the strengthening of the sanctions on investment, services and trade with Crimea and Sevastopol. 141218 US UFSA/H.R. 5859 Speculation EUNS09 The Ukraine Freedom Support Act of 2014 (UFSA/H.R. 5859) is signed into law by President Obama. 3 The UFSA provides the U.S. president with a menu of nine different types of sanctions (e.g. revocation of visas; prohibition of the exportation or provision of a defense article or service to the targeted entity, etc.) that the President may apply to persons operating in the Russian defense and energy sectors.

141219 US Office of Foreign Assets Control Sanctions USS11 OFAC designates another 17 individuals and 7 entities to the SDN List 2 150129 EU Foreign Affairs Council meeting Extension EUE01 the Council agreed to extend the existing individual restrictive measure 1 150209 EU Foreign Affairs Council meeting Sanctions EUS12 The Council unanimously adopted additional listings concerning separatists in Eastern Ukraine and their 1 supporters in Russia. These consist of an asset freeze and a travel ban on 19 persons and 9 entities involved in action against Ukraine's territorial integrity. To give space for diplomatic efforts and the Minsk talks, the Council put the entry into force of the measures on hold until Monday 16 February 2015. 150212 EU Informal meeting of heads of state or Speculation EUNS10 At an informal meeting of heads of state or government, EU leaders gave cautious support to the Minsk 1 government agreement. They indicated that they will not hesitate to take the necessary steps if the agreement is not implemented and the ceasefire is not respected. 34 150216 EU European Council Sanctions EUS13 As requested by the Foreign Affairs Council of 9 February, an asset freeze and an EU travel ban were 1 imposed to 19 persons and 9 entities involved in action against Ukraine's territorial integrity. 150305 EU European Council Extension EUE02 The Council has extended EU restrictive measures focused on the freezing and recovery of 1 misappropriated Ukrainian state funds. 150311 US Office of Foreign Assets Control Sanctions USS12 OFAC adds another 14 individuals and 2 entities to the SDN List, all of them either involved in the 2 misappropriation of Ukraine’s state assets, the annexation of Crimea by Russia or separatist activities in the eastern regions of Ukraine. 150313 EU European Council Extension EUE03 The Council extended until 15 September 2015 the application of EU restrictive measures targeting 1 action against Ukraine's sovereignty, territorial integrity and independence. 150319 EU European Council Sanctions EUS14 Leaders decided to align the existing sanctions regime to the implementation of the Minsk agreements. 1 Economic sanctions will remain enforced until the end of 2015 when the last point of the peace plan is to be implemented: Ukraine regaining control over its borders in the east. 150605 EU European Council Extension EUE04 Extension of EU sanctions over misappropriation of Ukrainian state funds. The Council extended the 1 asset freeze for three persons covered by measures applying until 6 June 2015. 150619 EU European Council Extension EUE05 Extension of restrictions in response to the illegal annexation of Crimea and Sevastopol 1 150722 EU European Council Extension EUE06 The Council extended EU economic sanctions until 31 January 2016. These sanctions were introduced 1 in response to Russia's destabilising role in Eastern Ukraine. They target certain exchanges with Russia in the financial, energy and defence sectors and dual-use goods. 150730 US Office of Foreign Assets Control Speculation USNS03 OFAC issues advisories to the public on important issues related to the sanctions programs it 2 administers. While these documents may focus on specific industries and activities, they should be reviewed by any party interested in OFAC compliance. 150914 EU European Council Extension EUE07 Extension of EU sanctions over action against Ukraine's territorial integrity 1 151005 EU European Council Extension EUE08 Extension of EU sanctions over misappropriation of Ukrainian state funds 4 151221 EU European Council Extension EUE09 The Council prolonged EU economic sanctions against Russia until 31 July 2016. . In March 2015, EU 1 leaders decided to align the existing sanctions regime to the complete implementation of the Minsk agreements, which was foreseen for the end of December 2015. Since the Minsk agreements will not be fully implemented by 31 December 2015, the duration of the sanctions has been prolonged whilst the Council continues its assessment of progress in implementation. 160304 EU European Council Extension EUE10 The Council extended by one year asset freezes against 16 people identified as responsible for the 1 misappropriation of Ukrainian state funds or for the abuse of office causing a loss to Ukrainian public funds. 160310 EU European Council Extension EUE11 The Council extended until 15 September 2016 EU restrictive measures against 146 people and 37 1 companies, in view of the continuing undermining or threatening of the territorial integrity, sovereignty and independence of Ukraine. 160617 EU European Council Extension EUE12 The Council extended the restrictive measures in response to the illegal annexation of Crimea and 1 Sevastopol by Russia until 23 June 2017. The measures apply to EU persons and EU based companies. They are limited to the territory of Crimea and Sevastopol. 160701 EU European Council Extension EUE13 The Council prolonged the economic sanctions targeting specific sectors of the Russian economy until 1 31 January 2017. 160915 EU European Council Extension EUE14 The Council prolonged until 15 March 2017 the application of sanctions targeting actions against 1 Ukraine's territorial integrity, sovereignty and independence. These sanctions consist of an asset freeze and a travel ban against 146 persons and 37 entities. 161109 EU European Council Sanctions EUS15 EU adds six members of the State Duma from Crimea to sanctions list 1 161219 EU European Council Extension EUE15 The Council extended the application of economic sanctions targeting specific sectors of the Russian 1 economy, until 31 July 2017. 170112 US Office of Foreign Assets Control Speculation USNS04 OFAC issues interpretive guidance on specific issues related to the sanctions programs it administers. 2 These interpretations of OFAC policy are sometimes published in response to a public request for guidance or may be released proactively by OFAC in order to address a complex topic.

170303 EU European Council Extension EUE16 The Council extended until 6 March 2018 the asset freezes against 15 people identified as responsible 1 for the misappropriation of Ukrainian state funds or for the abuse of office causing a loss to Ukrainian public funds. 170313 EU European Council Extension EUE17 The Council prolonged for a further six months, until 15 September 2017, the application of sanctions 1 targeting actions against Ukraine's territorial integrity, sovereignty and independence. The measures consist of asset freezes and a travel ban applying to 150 people and 37 entities. 170619 EU European Council Extension EUE18 The Council extended the restrictive measures in response to the illegal annexation of Crimea and 1 Sevastopol by Russia until 23 June 2018. The measures apply to EU persons and EU based companies. They are limited to the territory of Crimea and Sevastopol. 35 170628 EU European Council Extension EUE19 The Council prolonged economic sanctions targeting specific sectors of the Russian economy until 31 1 January 2018. This decision follows an update from President Macron and Chancellor Merkel to the European Council of 22-23 June 2017 on the implementation of the Minsk Agreements.

170804 EU European Council Sanctions EUS16 The EU has added 3 Russian nationals and 3 companies involved in the transfer of gas turbines to 1 Crimea to the list of persons subject to restrictive measures in respect of actions undermining Ukraine's territorial integrity, sovereignty and independence. 170914 EU European Council Extension EUE20 The Council prolonged for a further six months, until 15 March 2018, the application of sanctions 1 targeting actions against Ukraine's territorial integrity, sovereignty and independence. 170929 US Office of Foreign Assets Control Sanctions USS13 Directive 1 under executive order 13662 amended 2 171031 US Office of Foreign Assets Control Sanctions USS14 Directive 4 under executive order 13662 amended 2 171121 EU European Council Sanctions EUS17 "Governor of Sevastopol" added to sanctions list over actions against Ukraine's territorial integrity 1 171221 EU European Council Extension EUE21 The Council prolonged economic sanctions targeting specific sectors of the Russian economy until 31 1 July 2018. This decision follows an update from President Macron and Chancellor Merkel to the European Council of 14 December 2017 on the state of implementation of the Minsk agreements.

180305 EU European Council Extension EUE22 The Council extended until 6 March 2019 the asset freezes against 13 people identified as responsible 1 for the misappropriation of Ukrainian state funds or for the abuse of office causing a loss to Ukrainian public funds. The restrictive measures against two persons were not extended. This decision was based on the annual review of the measures. 180312 EU European Council Extension EUE23 The Council prolonged for a further six months, until 15 September 2018, the application of sanctions 1 targeting actions against Ukraine's territorial integrity, sovereignty and independence. The measures consist of asset freezes and a travel ban applying to 150 people and 38 entities. Abridged sanction descriptions are copied from subpages of: 1. consilium.europa.eu 2. treasury.gov 3. congress.gov 4. eur-lex.europa.eu Appendix 1 shows all international sanctions events used in the research. International sanctions were defined as sanctions that are declared by the Security Council, the US or the EU during the Ukraine crisis. All events were classified into three groups: Sanctions, Speculations and Extensions. The information in this table is sourced from webpages that track and gather international sanctions. The general webpage source can be found in the footnotes of the table. Specific sources for each sanction are available on request.