The Cost of Russian Sanctions on the Global Equity
Markets∗
Lei Huanga
Fangzhou Lua
May 12, 2022
Abstract
We estimate the direct and indirect impact of Russian sanctions on the global equity markets since the Russian invasion of Ukraine. Countries that impose sanctions on Russia have
higher institutional quality and lower corruption scores. Sanctions against Russia on average
cost 0.11 trillion USD for each country’s stock market, and -2.39% for each stock. Given that
the average stock’s market capitalization is 3.79 billion USD in our sample, the average loss
is 90.7 million USD per stock. A back-of the envelop calculation suggests that the Russian
stock market loses between 137 billion and 353 billion USD, which is 7% to 20% of Russian’s
annual GDP. This is the loss from the listed sector alone and from the combined effect of
invasion and the sanctions. The average equity market loss for the country that impose
sanctions on Russia is close to 3% of its GDP, which is between 16% to 43% the loss that
Russian suffers as percentage of its total GDP. We also show that even within country that
impose sanctions on Russia, the firms that publicly announce a withdrawal of business from
Russia suffers an additional 2.3% drop in their stock prices. These firms tend to have higher
ESG governance, social, and environment scores.
JEL Codes: G12, F3, H56, N4
Keywords: Russian invasion, Ukraine, Sanction, International equity markets
∗a
HKU Business School,
hlei123@connect.hku.hk.
The University of Hong Kong.
Please send correspondence to:
Electronic copy available at: https://ssrn.com/abstract=4060927
An Eye for an Eye: The Cost of Russian Sanctions on
the Global Equity Markets
Abstract
We estimate the direct and indirect impact of Russian sanctions on the global equity markets since the Russian invasion of Ukraine. Countries that impose sanctions on Russia have
higher institutional quality and lower corruption scores. Sanctions against Russia on average
cost 0.11 trillion USD for each country’s stock market, and -2.39% for each stock. Given that
the average stock’s market capitalization is 3.79 billion USD in our sample, the average loss
is 90.7 million USD per stock. A back-of the envelop calculation suggests that the Russian
stock market loses between 137 billion and 353 billion USD, which is 7% to 20% of Russian’s
annual GDP. This is the loss from the listed sector alone and from the combined effect of
invasion and the sanctions. The average equity market loss for the country that impose
sanctions on Russia is close to 3% of its GDP, which is between 16% to 43% the loss that
Russian suffers as percentage of its total GDP. We also show that even within country that
impose sanctions on Russia, the firms that publicly announce a withdrawal of business from
Russia suffers an additional 2.3% drop in their stock prices. These firms tend to have higher
ESG governance, social, and environment scores.
JEL Codes: G12, F3, H56, N4
Keywords: Russian invasion, Ukraine, Sanction, International equity markets
Electronic copy available at: https://ssrn.com/abstract=4060927
1
Introduction
The global financial market is shocked by the sudden Russian invasion of Ukraine and the
Russian stock market tumbled more than 50% and eventually the Moscow Exchange shut
down since Feb. 25 and remained closed. The price of global listed Russian firms as depository receipts such as Sberbank plunged into the pennies and are completely wiped out.
Brent Oil Price reached the highest level since 2008 and all commodity prices experience a
large spike. Given the wide range of large economic adjustment globally that deeply disrupt
a lot of firm’s operation, evaluating the impact of sanctions is crucial.
We study the impact of sanction of global equity market, as sanction is one of the most
factors that shape firm’s future cash flow besides the war’s disruption itself. We identify the
sanction both at the country level as well as the firm level. First consider the case where
the sanction is imposed at the country level. When an entity A imposes a sanction on entity
B, the cost may be on A, B, or both A and B. In a world with comparative advantage, a
sanction cost generates even benefits of an entity and the eventual total welfare may not be
a zero-sum game. Entity B may also retaliate by imposing an another sanction on entity
A. Therefore, we attempt to evaluate the average impact of sanction on entity A and B
compared to an unaffected entity C. Even with a country, the sanction may benefit some
industries at the cost of others. therefore, it is also possible to observe distribution effect if
the sanction is imposed at a country level.
Now consider the case where the sanction happens at the firm level. A sanction can both
affect a firm’s cost and revenue. Through disrupting supply chains, a firm may have to pay
a high cost for its input, through restricting range of operation and access to its customers.
We also attempt to tease out these two effects separately.
Cost of Sanction is very large. Russian government has depleted half of its foreign reserve.
At the end of 2011 Q4, the Moscow stock market has a market capitalization of 353 billion
USD. When the Moscow stock market stopped trading on February 25th, 2022, the total
market capitalization is 216 billion USD. Consider the total market capitalization of the
1
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Moscow stock market is 18.645 percent of its GDP, and major Russian banks such as the
Sherbank almost lose all its market capitalization in London stock exchange, so a back-of
the envelop calculation suggests that the Russian stock market loses between 137 million
USD and 353 billion, which is 7% to 20% of Russian’s annual GDP. This is the loss from the
listed sector alone.
We are more interested in also studying the effect of sanction on countries that enforce
sanctions on Russia. We use event study to study the effect of a sanction. We pick several
potential CAR days, the first one is Feb 24th, 2022, the first day that Russian invades
Ukraines. and the second one is when the United Nations (UN) that conducted the General
Assembly during the the emergency special session demanding Russia to withdraw from
Ukraine. The emergency session was called February 28th and concluded on March 2rd.
Therefore, we use a five day window from February 27th to March 3rd as the event window.
The third day is the day Russian government set up the unfriendly country list, which
includes 43 countries. This day is March 7th on a Monday.
Next we classify the countries that impose sanction on Russia, or Russian would impose
sanction on. We use the list of unfriendly country list posed by Russia as the treatment
group, and the rest as the control group. Of course, Russian government most likely select
this list based on the the country that actually sanction Russia. From the control group, we
also omit countries that vote against (or abstention) in UN’s decisions requesting Russia to
withdraw from Ukraine.
We find that Russian sanction on average cost 0.1 Trillion USD for the each country’s
stock market that impose a sanction on Russia, and -2.395 percent for each stock. Given
that the average stock’s market capitalization is 3.79 billion USD in our sample, the average
loss is 90.7 million USD per stock. The average loss is close to 3% of a sanctioning country’s
GDP, which is between 16.67% to 42.85% the loss that Russian suffers as percentage as total
GDP.
Our research is related to the literature on sanctioning. Torbat (2005) show that financial
2
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sanction is more effective than trade sanction when it comes to sanctioning on Iran. Haidar
(2017) show that after the Iranian sanction, two-third of the world demand originally from
Iran has been shifted to non-sanctioned countries. Tirole (2015) show that sanction may
be useful in an optimal contract when the shock to both countries are equal. Using an
unpredecent one of the largest sanction since the cold war, we evaluate the cost the sanction
of the global equity market.1
2
Data
Figure 1 shows the stock market performance of sanction vs. non-sanction countries. Arithmetic average or median are computed across each subgroup. In the top two graphs, we
classify countries into sanction vs. non-sanction group based on Russian government’s “unfriendly country list” published on March 7th 2022. In the bottom two graphs, we classify
countries into “For” and “Against or abstention” based on each country’s voting during UN’s
emergency session demanding Russian army to withdraw from Ukraine. Before the sanction,
roughly unsanctioned countries and sanctioning countries have a five percent return difference, this difference becomes 10% after the sanction. So on average, a 5% market drop is
seen for countries that impose sanction on Russia.
Figure 2 and 3 show the stock market performance of sanction vs. non-sanction countries
by industry. Clearly we can observe a redistribution effect of sanction. For industries such as
Energy sector in the US, the ban on Russian crude oil make Shale oil looks promising again,
therefore it actually benefit the Energy sector. But most sectors suffer from this sanction,
take the consumer cyclicals and Financial sectors for example, these industries all suffer from
sanction on Russia.
We also show the characteristics of the countries that enforce sanction on Russia and
the characteristics of the countries that do not enforce sanction on Russia. The upper
figure: Russia as partner shows that from those other countries’ perspective, the percentage
1
Also see
2
3
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of Russian export and import as a percentage of its total export and import respectively.
The lower figure: Russia as a reporter shows from Russia’s perspective, the percentage of the
country’s export and import as a percentage of Russia’s total export and import respectively.
Figure 4 shows that countries that Russian rely more on countries that impose sanction on
them. These countries tend to be more developed countries with a higher GDP number.
3
Effect of sanction on the global equity market: Identified at the country level
3.1
Methodology
We use two kinds of empirical specifications
CARk,i,c,e = αk + β1 Sanctionc + β2 Controlsk + γF E (zi,e ) + k,i,c,e
(1)
where the subscript k refers to the firm, i refers to the industry of the firm, c is the
country where the firm’s headquarter is, and e is the country where a firm is listed, and
CAR is the cumulative abnormal return, -1 to +1 days relative to the event day. Sanctionc
is a dummy variable that equals one if a firm’s headquarter or main source of revenue
is from a country c that applies sanction on Russia, or is imposed a sanction by Russia.
Notice that a firm’s headquarter may be very different from its country (location) of listing.
F E(zi,,c,e ) represents the fixed effects. We include exchange fixed effect, industry fixed effect
in F E(zi,c,e ) in different specifications to absorb unobserved heterogeneity exposure to the
Russo-Ukraine invasion. Standard errors are clustered at the firm level to allow for serial
dependence of the error term. The coefficient of central interest is β1 , where it measure the
effect of sanctions on firm’s return during this invasion.
We pick several potential CAR days, the first one is Feb 24th, 2022, the first day that
Russian invades Ukraines. and the second one is when the United Nations (UN) that con4
Electronic copy available at: https://ssrn.com/abstract=4060927
ducted the General Assembly during the the emergency special session demanding Russia to
withdraw from Ukraine. The emergency session was called February 28th and concluded on
March 2rd. Therefore, we use a five day window from February 27th to March 3rd as the
event window. The third day is the day Russian government set up the unfriendly country
list, which includes 43 countries. This day is March 7th on a Monday.
Next we classify the countries that impose sanction on Russia, or Russian would impose
sanction on. First we use the list of countries that vote for the UN’s decisions demanding
Russian to withdraw from Ukraine as the treatment group, and the countries that vote
against or give up their vote (abstention) as countries in the control group. The downside of
this approach of course, is that the countries that vote against this UN decisions may suffer
similar sanction as Russian and lost more than the economic costs incurred by the countries
impose the sanction.
The second approach is that, we use the list of unfriendly country list posed by Russia
as the treatment group, and the rest as the control group. Of course, Russian government
most likely select this list based on the the country that actually sanction Russia. A third
approach, is to based on the countries that vote Yes in the UN decisions, we classify those
that listed by Russia as unfriendly country as the treatment group, and those that have not
been listed by Russia as unfriendly country as the Control group. This approach theoretically
isolate Russian sanction effect. The fourth way is based on the second approach, but from
the control group omitting countries that vote against or absent in the UN decisions. A fifth
way is based on the third approach, but from the control group omitting countries that vote
Yes in the UN decisions.
3.2
Results
Using the day that Russia draft the sanction list as event day, Table 1 shows that for the
each country’s stock market that impose a sanction on Russia, average stock drops -2.395
percent. Given that the average stock’s market capitalization is 3.79 billion USD in our
5
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sample, the average loss is 90.7 million USD per stock. The average loss is close to 3% of a
sanctioning country’s GDP, which is between 16.67% to 42.85% the loss that Russian suffers
as percentage as total GDP. We do not find a similar result for the day Russia first invaded
Ukraine, or the day UN requesting Russia to retreat, suggesting that on those days, the
market did not expect the sanction on Russia to be very severe, or the exact list of countries
that would enforce sanctions on Russia were unclear.
4
Conclusion
Cost of Sanction is very large. Russian government has depleted half of its foreign reserve.
At the end of 2011 Q4, the Moscow stock market has a market capitalization of 353 billion
USD. When the Moscow stock market stopped trading on February 25th, 2022, the total
market capitalization is 216 billion USD. Consider the total market capitalization of the
Moscow stock market is 18.645 percent of its GDP, and major Russian banks such as the
Sherbank almost lose all its market capitalization in London stock exchange, so a back-of
the envelop calculation suggests that the Russian stock market loses between 137 million
USD and 353 billion, which is 7% to 20% of Russian’s annual GDP. This is the loss from the
listed sector alone.
Compared to Russia, we find that We find that for the rest of the world, russian sanction
on average cost 0.1 Trillion USD for the each country’s stock market that impose a sanction
on Russia, and -2.395 percent for each stock. Given that the average stock’s market capitalization is 3.79 billion USD in our sample, the average loss is 90.7 million USD per stock.
The average loss is close to 3% of a sanctioning country’s GDP, which is between 16.67% to
42.85% the loss that Russian suffers as percentage as total GDP.
6
Electronic copy available at: https://ssrn.com/abstract=4060927
References
Bedowska-Sojka, B., Demir, E., Zaremba, A., 2022. Hedging geopolitical risks with different
asset classes: A focus on the russian invasion of ukraine. Available at SSRN .
Deng, M., Leippold, M., Wagner, A. F., Wang, Q., 2022. Stock prices and the russia-ukraine
war: Sanctions, energy and esg. Swiss Finance Institute Research Paper .
Haidar, J. I., 2017. Sanctions and export deflection: evidence from iran. Economic Policy
32, 319–355.
Tirole, J., 2015. Country solidarity in sovereign crises. American Economic Review 105,
2333–63.
Torbat, A. E., 2005. Impacts of the us trade and financial sanctions on iran. World Economy
28, 407–434.
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Figure 1: Global Equity Market Performance: Sanction vs. non-sanction countries
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Electronic copy available at: https://ssrn.com/abstract=4060927
Note: This figures shows the stock market performance of sanction vs. non-sanction countries. Arithmetic average or median
are computed across each subgroup. In the top two graphs, we classify countries into sanction vs. unsanction group based on
Russian government’s “unfriendly country list” published on March 7th 2022. In the bottom two graphs, we classify countries
into “For” and “Against or abstention” based on each country’s voting during UN’s emergency session demanding Russian army
to withdraw from Ukraine.
Figure 2: Global Equity Market Performance: Sanction vs. non-sanction countries by industry
9
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Note: This figures shows the industry level (Datastream ten industry classification) stock market performance by sanction vs.
non-sanction countries. The four subfigures show the Energy, Healthcare, Utility, and Real Estate sector.
Figure 3: Global Equity Market Performance: Sanction vs. non-sanction countries by industry
10
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Note: This figures shows the industry level (Datastream ten industry classification) stock market performance by sanction
vs. non-sanction countries. The six subfigures show the Industries, Consumer Cyclicals, Consumer Non-Cyclicals, Financials,
Technology, and Basic Material sector.
Figure 4: Characteristic of sanction vs. non-sanction countries (2020)
11
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Note: This figure shows the characteristics of the country that Russia government label as an unfriendly country and impose a
mutual sanction (blue bar) and the characteristics of the country that Russia government does not label as an unfriendly country
and thus unlikely to have imposed an sanction on Russia. The upper figure: Russia as partner shows that from those other
countries’ perspective, the percentage of Russian export and import as a percentage of its total export and import respectively.
The lower figure: Russia as a reporter shows from Russia’s perspective, the percentage of the country’s export and import as a
percentage of Russia’s total export and import respectively.
Figure 5: Impact of sanction in characteristics matched sample
Note: This Figures shows the when the sanction countries and non-sanction countries are
one-to-one matched based on the percentage of Russian export and import as a percentage
of its total export and import respectively, the country level stock market index performance
difference between the sanction vs. non-sanction countries.
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Table 1: CAR based on the day Russian draft retaliation country list
This Table presents results using specification (1). We pick the day Russian government set up the
unfriendly country list, which includes 43 countries as the CAR days. This day is March 7th on a
Monday. Next we classify the countries that impose sanction on Russia, or Russian would impose
sanction on. First we use the list of countries (F or) that vote for the UN’s decisions demanding
Russian to withdraw from Ukraine as the treatment group, and the list of countries (N onf or) that
vote against or give up their vote (abstention) as the control group.The second approach is that,
we use the list of unfriendly countries (Sanc) list posed by Russia as the treatment group, and the
rest as the control group (N onsanc). Of course, Russian government most likely select this list
based on the the country that actually sanction Russia.
(1)
(2)
(3)
(4)
CAR
CAR
CAR
CAR
Panel A: Based on equity’s country of exchange
For
(5)
CAR
(6)
CAR
(7)
CAR
(8)
CAR
-3.127**
(-2.70)
Nonfor
2.813*
(2.21)
Sanc
-2.237*
(-2.06)
Nonsanc
2.055
(1.87)
Panel B: Based on equity’s country of issuance
For
-3.206**
(-2.79)
Nonfor
2.905*
(2.30)
Sanc
-2.395*
(-2.22)
Nonsanc
Constant
N
2.213*
(2.02)
-0.103
(-0.11)
36205
-2.942***
(-4.98)
36205
-0.922
(-1.07)
36205
-3.042***
(-4.71)
36205
-0.0682
(-0.07)
36205
-2.977***
(-5.03)
36205
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-0.847
(-1.00)
36205
-3.116***
(-4.80)
36205
Table 2: CAR based on the days UN hold special sessions
This Table presents results using specification (1). We pick the day UN holds emergency session
regarding Ukraine, which is between February 28th 2022 and March 3rd 2022. This day is March
7th on a Monday. Next we classify the countries that impose sanction on Russia, or Russian
would impose sanction on. First we use the list of countries (F or) that vote for the UN’s decisions
demanding Russian to withdraw from Ukraine as the treatment group, and the list of countries
(N onf or) that vote against or give up their vote (abstention) as the control group.The second
approach is that, we use the list of unfriendly countries (Sanc) list posed by Russia as the treatment
group, and the rest as the control group (N onsanc). Of course, Russian government most likely
select this list based on the the country that actually sanction Russia.
(1)
(2)
(3)
CAR
CAR
CAR
Panel A: Based on equity’s country of exchange
trade country for
(4)
CAR
(5)
CAR
(6)
CAR
(7)
CAR
(8)
CAR
-14.17
(-1.11)
trade country nonfor
12.83
(0.91)
trade country sanction
-13.73
(-1.14)
trade country nonsanction
13.04
(1.07)
Panel B: Based on equity’s country of issuance
base country for
-14.41
(-1.13)
base country nonfor
13.06
(0.94)
base country sanction
-14.19
(-1.19)
base country nonsanction
cons
N
13.47
(1.11)
-0.228
(-0.02)
36205
-13.11*
(-2.01)
36205
-1.672
(-0.18)
36205
-14.83*
(-2.08)
36205
-0.156
(-0.01)
36205
-13.23*
(-2.02)
36205
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-1.525
(-0.16)
36205
-15.10*
(-2.10)
36205
Table 3: CAR based on the day Russian initiated the invasion
This Table presents results using specification (1). We pick the day Russian first invaded Ukraine as
the CAR days. This day is February 24th on a Thursday. Next we classify the countries that impose
sanction on Russia, or Russian would impose sanction on. First we use the list of countries (F or)
that vote for the UN’s decisions demanding Russian to withdraw from Ukraine as the treatment
group, and the list of countries (N onf or) that vote against or give up their vote (abstention) as the
control group.The second approach is that, we use the list of unfriendly countries (Sanc) list posed
by Russia as the treatment group, and the rest as the control group (N onsanc). Of course, Russian
government most likely select this list based on the the country that actually sanction Russia.
(1)
(2)
(3)
(4)
(5)
CAR
CAR
CAR
CAR
CAR
Panel A: Based on equity’s country of exchange
For
(6)
CAR
(7)
CAR
(8)
CAR
-16.80
(-0.89)
Nonfor
15.24
(0.73)
Sanc
-17.07
(-0.96)
Nonsanc
16.29
(0.90)
Panel B: Based on equity’s country of issuance
For
-17.04
(-0.90)
Nonfor
15.46
(0.75)
Sanc
-17.53
(-0.99)
Nonsanc
Constant
N
16.71
(0.93)
-0.165
(-0.01)
36205
-15.45
(-1.60)
36205
-1.373
(-0.10)
36205
-17.76
(-1.68)
36205
-0.111
(-0.01)
36205
-15.57
(-1.60)
36205
-1.261
(-0.09)
36205
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-18.05
(-1.69)
36205