how does political instability affect market risk …523632/fulltext01.pdf · abstract analysis and...

Rami Saad

Autum 2011

Supervisor: Professor Jörgen Hellström

Master Thesis, 30 ECTS

Master´s Program in Economics, 120 ECTS

HOW DOES POLITICAL INSTABILITY AFFECT MARKET RISK AND THE RISK PREMIUM IN ISRAEL

Rami Saad

ACKNOWLEDGMENT

I would like to thank my awesome and brilliant supervisor Professor Jörgen Hellström

for his endless patience and guidance, his door was always open to me. Even though

this thesis took more than the allocated time Professor Hellström remained supportive

and motivational. I will not forget to thank my lovely parents, Emil and Fatineh Saad,

for their mental and financial support, during my studies in Sweden.

Abstract

Analysis and assessment of market risk and country risk premium have become a

critical component of valuation in recent years in emerging markets. In these markets

investors look for a higher rate of return on their investments than in developed

countries.

Israel is an attractive country for international investors. This is due to the fact that

Israel has one of the highest concentrations of high-tech companies in the world and

the tourism industry in the country which is highly attractive for its historical places;

especially in a religious manner.

Israel is a country located in Asia and has experienced many political changes (for

many reasons). Thus, it is likely that political decisions taken by the governments

affect the risk premium.

In this paper I considered the issue of market risk and the issue of country risk that

should be considered explicitly in valuation of the risk premium in emerging

countries. Then, the focus, in this paper, is on how the "political instability" in Israel

has affected the market risk and the risk premium in the last decade (from the year

5\2001 till 3\2010).

Standard deviation of the returns (estimated by moving average method) of the Israeli

stock market were used as a proxy for the market risk. The results show that the

political instability affects the market risk. The "Country Default Spread" approach

and the "Relative Equity Market Standard Deviation" approach were used to measure

the risk premium in Israel. The effect of the political instability on the risk premium

was thus found. Further, due to autocorrelation, the robustness of the results was

tested by models including lags of the dependent variable. The results from the

robustness test show, in most of the analyses, weak and less significant (low

confidence level) effect of the political instability on the risk premium.

Contents

1. Introduction……………………….………………………………….1

2. Background – Israel

2.1 Economic development….…………………………………..…...4

2.2 Political situation..….………………………………………..…...6

3. Earlier studies…..…………………………………………………….9

4. Method\Theory…………………………………………………...…11

5. Data……………………………………………………………...…...18

6. Results

6.1 Results for model 1…………………………………………….22



6.4 Robustness test……………….………………..………….……31

7. Conclusions……………....……………....……………………..…...34

Appendix ..……………………………………………………………..36

References.…...…………………………………………………………40

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1. Introduction

Since the world became freer with respect to capital flows during the 1980's1 when

governments deregulated restrictions (regulations) on trade and capital flows,

investors started to invest in foreign countries. Before this period, the international

investments were under regulations that limited the investors from moving their assets

from one country to another. These regulations are almost removed nowadays,

especially in developed countries, which make international capital's investors free

movers.

When it comes to evaluating their investment opportunities, investors look for the

highest return that they can earn consequently with the lowest risk among the

opportunities available in the market. In recent years, when the free trade and capital

flows policies were applied in most of the developed countries, assessment of market

risk and country risk premium has become a critical component of valuation. Every

country contains different risks regarding the economic and the political situation. In

general, countries located in Asia tend to be more risky than countries located in

Europe2. With this pattern, investors will require (for) higher return when they invest

in risky countries rather than in less risky countries to compensate for holding this

risk.

Central parts for the investor’s portfolio are market risk and risk premium. The market

risk or the systematic risk (see CAPM model in section 4.1) is the risk that cannot be

avoided or diversified from a specific investment. This kind of risk usually derived

from the stock market. The standard deviation (square root of variance) of the rate of

returns from the stock market is used as the proxy for market risk.

The risk premium in emerging markets is usually measured in comparison with

developed countries rather than using accepted and known models. It is an important

point that is mention now to understand the methods used in this paper to assess and

measure the risk premium for emerging markets. The reason for using this approach

to measure the risk premium is the fact that using historical data it is difficult to apply

it in the accepted and known models for emerging markets.

Market risk and country risk are affected by two main factors. These two main

important factors are the economic and the political stability of every specific country.

If we consider the previous example of a country located in Asia compared to Europe,

we can see that generally the first is associated with higher risk than the second. This

risk embodied by the fact that Asia is a region where the political situation is more

unstable and at the same time less developed than in most of the European countries.

European countries are more developed in the economic aspect compared to Asian

countries. For instance, Iraq is a country located in Asia with an unstable regime (until

1 The subject was discussed in the paper Capital Flows to Emerging Markets: The Myths and Realities,

"over time countries realized that the free movement of capital could have widespread benefits" by Bill

Block and Kristin Forbes Council of Economic Advisers. 2 this subject was discussed in Asia Risk Monitor: Global risk segmentation and the implications for

risk management in the private and public sectors by Daniel M. Hofmann, Group Chief Economist of

Zurich Financial Services, in this paper it's mentioned that Asia appears to be vulnerable to list of risks

and richer countries tend to be less prone to the same list of risks – Europe included.

- 2 -

the date of this study) and will therefore be classified, in the investors' eyes, as a risky

country compared to Germany; hence, investors will require a higher return in order

to invest in Iraq.

There are several differences between developed countries and emerging ones. In this

paragraph some characteristics mentioned below may help to distinguish between the

developed and emerging countries. In the developed countries, in general, a stable

economic environment associated with low risk can be found. This is due to clear

rules and regulations settled by the developed governments which control the market

and the transactions. The developed countries are unionized with the organization so

called OECD (Organization for Economic Cooperation and Development). The

emerging countries commonly are associated with rapid growth in production and

have a potential for higher profit with higher risk than other developed or

underdeveloped countries.

Political instability is a situation in a specific county where the political system

experiences tensions. This situation can appear in terms of wars, turmoil, elections, or

other events that can cause tension in the political regime. These periods are

characterized by non-convenience situation and hurt the economic stability in the

country.

The purpose of this paper is to study how and to which extent political instability

affects market risk and the country risk premium as well. The study is a case study

focusing on this issue for Israel.

Israel is located in Asia and classified as an emerging market (up to April 30, 2010). I

found that Israel is a suitable country to examine the affect of the political instability

on the market risk and the country risk premium for many reasons. The most

important reason is the fact that Israel attracts many investors from all over the world,

so this thesis could provide important information for those who are looking to invest

in Israel. On the other hand, Israel has also experienced many politically instable

periods. The purpose of this research is to study the market risk and the risk premium

in the Israeli market focusing on political changes under the assumption that Israel is

an emerging market.

In Israel, the domestic security situation was difficult in the recent 10 years, as the

governments were trying to sign peace agreements with Arab and Muslim(s) countries

with which Israel had no prior diplomatic relations. It is worth mentioning that in

general, the security situation did not influence the daily running of the industries and

other sectors except of special short term cases such as the war in Lebanon3 in the

year 2006.

This research is important for all investors who are investing in the Israeli market.

This paper provides investors with a sufficient background about the market and the

country risk and with information how these risks change during the political

instability periods. It is as well of academic interest as it provides evidence of the link

between political instabilities and financial risk.

3 According to ANIMA Investment Network, project funded by European Union.

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It was not easy to find historical data in order to calculate risk premiums. The data

concerning the Israeli market which was found is strictly limited and only from the

past decade. Therefore, I was able only to work with the available restricted data. The

problem with the data available for a short time may come with a large standard error.

The politically instable periods that I choose are subjectively selected. The unstable

periods cover eight events from 2001 to 2010.

In Section 2, a background of the economic development and political situation in

Israel is provided. Section 3 contains a review about the most relevant studies for the

current question at hand. Section 4 includes the methods used for measuring market

risk and country premium. Section 5 contains the data available for measuring market

risk and risk premium. Section 6 shows the results of market and country risk in

Israel. Section 7 summarizes the paper and presents the conclusions.

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2. Background – Israel

The economic and political background of Israel is introduced to the reader.

2.1 Economic development

On the May 14, 1948 the Jewish Agency claimed independence, one day before the

British Mandate expired, and gave the name to the country Israel.

Israel is considered today as one of the most industrial developed and economically

advanced countries in Asia. It is worth mentioning that Morgan Stanley Capital

International (MSCI) announced that Israel will be classified as a developed country

starting in May 2010. However, in this paper Israel is considered as an emerging

market. The country has been ranked third in the region on the World Bank's Ease of

Doing Business Index (in 2006) and had the second largest number of start up

companies after the US.

Despite a shortage of natural resources, developments in the agriculture and industry

sectors made Israel in the past 10 years self sufficient in food, especially in grains and

beef. Israel imports fuels, raw materials and military equipment, while the country

exports fruits, vegetables, pharmaceuticals, software, chemicals, military technology

and diamonds. Israel is a leading manufacturer of these products in the world. The

tourism sector in Israel, especially for religious people, is an important industry, since

beaches, archaeological and historical sites with convenient temperature may be

found in all parts of the country. Almost 3 million tourists visit Israel each year.

The gross domestic product (GDP) per capita is ranked around 30th

in the world. It

has grown rapidly since Israel claimed independence in 1948. The growth rate of

Israel (in fixed prices) from December 1995 to March 2010 is presented in Figure 2.

The quarterly gross domestic product (GDP) per capita (in current prices) from

December 1995 to March 2010 is illustrated in Figure 1.

Figure 1: Gross domestic product per capita for Israel

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Figure 2: Growth rate for Israel

According to ANIMA Investment Network, in the past 20 years, Israel has developed

an industrialized economy despite being classified as an emerging market and

carrying ongoing political tensions in the country region. Nowadays, it is a regional

economic power with a GDP of US$ 190 billion (NIS 699 billion) recorded in 2009.

The main reasons for this strong growth were exports, private consumption, and

expansion in high technology industries and tourism. The number of foreign investors

in the recent 20 years has been also grown rapidly.

The domestic currency in Israel is the New Israeli Shekel (NIS) and it's a free

convertible currency in the world. On June 5, 2010, the exchange rate for Shekel to

Dollar is 3.853 and to Euro 4.703.

Despite Israel being an emerging market, it presents and offers the economic stability

of a developed country and simultaneously it continues to offer growth and profit

opportunities of an emerging market.

To encourage both local and foreign investments, the State of Israel offers a wide

range of incentives (such as tax benefits and grants) and benefits to investors in

industry, tourism and real estate. The government attempts to give special attention to

investors in hi-tech companies and also R&D activities. The hi-tech industry in Israel

is recognized as one of the world's outstanding technology centers and, as mentioned

above, is the second largest in terms of start up companies. A major factor in the

success of this sector is the clear government policy of leadership, support and

encouragement of industrial R&D of the Office of the Chief Scientist (OCS) at the

Israeli Ministry of Industry, Trade and Labor.

The Israel Stock Exchange market called as well Tel Aviv Stock Exchange (TASE) is

the only stock exchange in Israel and is located in Tel Aviv city. TASE is supervised

by the Israel Security Authority and it is a private company controlled by banks and

other corporations. TASE plays important role in the Israeli economy. In this

marketplace all types of securities such as stocks, bonds, funds etc. are traded.

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Different kinds of companies are listed in TASE, for instance, companies dealing with

commerce and service, industry, real estate and construction, investment and holding,

as well as with insurance.

The leading index in TASE is TA-25, which contains the 25 largest stocks in TASE;

TA-100 contains the 100 largest stocks in TASE; and TA-75 contains the stocks of

TA-100 not listed in TA-25. In Figure 3 below the weekly TA-100 index from

January 2000 to April 2010 is presented.

Figure 3: TA-100 Index for the last decade

Figure 3 shows that there is an increasing pattern in the TA-100 index from 2002 to

2008. In 2008, the effect of the global financial crisis can be clearly visualized. After

slower growth in 2008 and 2009, due to the global slumps caused by the financial

crisis, the stock market started to recover again according to new records in the stock

market in 2009 as can be seen in Figure 3.

2.2 Political situation

Israel has a democratic parliamentary system. It is recognized to have the most

democratic government in the Middle East, according to Zionism (Jewish national

liberation movement) and Israel. All Israeli citizens over 18 years old have the right to

vote for a government. This political system includes, as in every democratic system,

legislative, executive and judicial branches. Israel applies the power of separation

between legislative, executive and judicial branches. The Knesset is the parliament

which includes 120 members assembled by the parties selected in the election. Today

there are main three parties in Israel; Likud – right party (Zionist and capitalist),

Kadima – central party (right and Zionist) and Labor – central party (left and Zionist).

In order to completely understand the political situation in Israel, it is important to

mention the Israel-Palestine conflict. This conflict is an ongoing political tension

between two nations and countries. It is unclear when this conflict has appeared but it

is mentioned already in the Old Testament of the Bible. The conflict mainly focuses

on the controlling of the land, especially Jerusalem. Many attempts from other

countries were focused on negotiation in order to find a solution for this conflict. So

far, the conflict is still ongoing and the tension between two nations remains.

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- 7 -

As it was mentioned previously, Israel is highlighted in the media as a place which

constantly experiences political changes. Therefore, eight different political tension

periods are presented to be used later to measure the effect of political instability

periods on the market risk and risk premium:

1- The Second Intifada War took place during the period from 5/2001 to 10/2003.

During this period Israel experienced a period of intensified Palestinian-Israeli

violence, which began in late September 2000 and ended in October 2003. I covered

the period starting from 5/2001 because of lack of data before this period. The death

toll was big and included both military and civilian casualties. Approximately 3,333

Palestinians, 1,000 Israelis and 64 foreign citizens were killed (according to Haaretz

Israeli news). According to these numbers it is obvious that this period, the Second

Intifada, is an essential event which is worth to focus on and to find out how this

event affects the risk premium in Israel.

2- The election for the 17th Knesset took place during the period from 3/2006 to

4/2006. The election results were surprising and unexpected. The voter turnout of

63.2% was the lowest ever.

3- The 2006 Lebanon War took place during the period from 7/2006 to 9/2006. It is

also called the Israel-Hezbollah 2006 War and known in Lebanon as the July War and

in Israel as the Second Lebanon War. It was a 34-day military conflict in Lebanon and

northern Israel. The war started on the July 12, 2006, until United Nations achieved

ceasefire on the August 14, 2006. During the war, at least 1,244 people were killed,

and at least one million people were left without homes (according to BBC news).

4- The Gaza War took place during the period from 12/2008 to 1/2009. This war took

place in Gaza during the winter 2008 for three weeks. The aim of this war was to stop

rocket attack from Gaza to Israeli regions. Israeli forces attacked buildings belonging

to government, police and military. Over 1,000 Palestinians and 13 Israelis were

killed (according to BBC news, Jerusalem).

5- The elections for the 18th Knesset took place during the period from 2/2009 to

3/2009. The elections came after the Prime Minister Ehud Olmert resigned from the

Kadima party and the successor Tzipi Livni failed to form a new government. If

Olmert remained in his office or if Livni had formed a coalition government, the

elections would have been scheduled for 2010 instead.

6- In 9/2009, a UN special mission headed by Judge Richard Goldstone, produced a

report accusing both Palestinian militants and Israeli Defense Forces of war crimes

and possible crimes against humanity, recommending to bring those responsible to

justice. The UN Human Rights Council endorsed the report, criticizing Israel but not

Hamas.

7- In 1/2010, Israel experienced serious tension with Turkey on the January 11, 2010

after Israeli Vice president for Foreign Affairs, Minister Danny Ayalon invited the

Turkish ambassador Ahmet Oguz Celikkol to the meeting. During the session,

Celikkol was seated below Ayalon, with cameras rolling. The aim of this appointment

was to reproach Turkish policies against Israel. In response, Turkey wanted to return

http://en.wikipedia.org/wiki/Israeli%E2%80%93Palestinian_conflict

http://en.wikipedia.org/wiki/Knesset#Composition_of_the_17th_Knesset_Assembly_.28elected_2006.29

http://en.wikipedia.org/wiki/Knesset

http://en.wikipedia.org/wiki/War

http://en.wikipedia.org/wiki/Lebanon

http://en.wikipedia.org/wiki/Israel

http://en.wikipedia.org/wiki/United_Nations

http://en.wikipedia.org/wiki/Ceasefire

http://en.wikipedia.org/wiki/Knesset#Composition_of_the_17th_Knesset_Assembly_.28elected_2006.29

http://en.wikipedia.org/wiki/Knesset

http://en.wikipedia.org/wiki/United_Nations_Fact_Finding_Mission_on_the_Gaza_Conflict

http://en.wikipedia.org/wiki/Richard_Goldstone

http://en.wikipedia.org/wiki/UN_Human_Rights_Council

- 8 -

the ambassador back from Israel but in the last minute Israel released an apology to

Turkey. Currently, the tension is still ongoing.

8- In 2/2010, according to the media, a big controversy was among several countries

(especially European countries) concerning the identity of the killer of al-Mabhouh

(senior Hamas military commander). Al-Mabhouh was killed after being followed by

at least 11 individuals carrying fake passports from various European nations. The

countries which were involved because of the fake passports accused Israel for using

their passports for their own political interests. In this period a pressure was on the

Israeli government and most of the European countries asked to open an investigation.

I focused on these eight periods with intent to analyze the effect of political instability

on the market risk and the risk premium in Israel. Even though, there is infinity of

political changes throughout the past decade, I found these events to be the most

essential concerning political changes and instability.

These eight political instability periods are collected from the available media in the

internet. I went through the Israeli news websites such as www.ynet.co.il,

www.walla.co.il, www.haaretz.com and www.jpost.com. These entire websites

contain daily news covering mainly Israel and the Middle East.

http://en.wikipedia.org/wiki/Hamas

http://www.ynet.co.il/

http://www.walla.co.il/

http://www.haaretz.com/

http://www.jpost.com/

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3. Earlier studies

There is a number of papers discussing market risk, risk premium and country risk.

The most relevant study to my thesis is the paper by Aswath (2003). In this paper

Aswath focuses on two main questions. The first is whether the companies should

take into account country risk when it pertains to investments in emerging countries.

The second is how to measure the exposure to country risk in emerging countries. In

this paper two approaches for estimation of country risk premium are presented as

well. The first is a historical risk premium approach, while the second is an implied

premium approach. In the first approach, the historical potential return of the stock

market is compared to the return from risk-free assets in the same periods, difference

between the returns gives us the risk premium. The author claims that this approach is

not relevant for emerging markets (such as Israel) because of the large standard error

that we can have. He proposed an alternative approach, so called “modified historical

risk premium”, to measure country risk in order to avoid the noise that can come from

the emerging markets’ data. The second approach does not require any historical data

but requires the use of the present value equation to extract the required return on

equity (see the paper by Aswath (1999). For this thesis part of the first approach

(modified historical risk premium) is used, which includes two methods “Country

Bond Default Spreads” and “Relative Equity Market Standard Deviations” to measure

the risk premium in Israel.

The paper by Soultanaeva (2008) analyzes the impact of political news on the return

and volatilities of the Baltic's stock markets. The results indicate that the political

news have led to lower uncertainty in the stock market of Riga and Tallinn in the

period 2001-2003 regarding foreign and domestic news, except of Russian. Political

news from Russia increased volatility in Tallinn stock market in the same period.

Furthermore, it seems that in the period 2004-2007 the effect of political news on the

Baltic's stock markets was significantly lower as compared to the period 2001-2003.

Relatively,Vilnius stock market seems to be unaffected by political news in the

periods 2001-2003 and 2004-2007. The main conclusion from this paper is that the

sensitivity of the Baltic's stock markets seems to decrease over the two sample

periods.

The paper written by Hellstrom and co-author Soultanaeva (2011) studies almost the

same subject as was mentioned in the previous paper. Accordingly, the authors used

different methods to test the causes of stock markets’ jumps followed by political

news. The results are in line with those of the previous mentioned paper.

The paper by Hung et al. (2007) tests the jump intensity and volatility in both Taiwan

stock and foreign exchange markets during presidential elections. The results indicate

that during the presidential elections the jump intensity and the volatility of both

markets increase.

The paper by Chan (2001) tests the impact of salient political and economic news on

the stock return volatility, the price volatility and the daily volume in the Hong Kong

stock market. Subsequently, the author found that the salient political news cause a

- 10 -

negative effect while salient economic news cause a positive effect on the stock

market.

The paper by Jean-Claude and Jean (1991) came after famous business and financial

magazines “Euromoney” and “International Investor” which published rating of

countries "creditworthiness" in 1987. In their paper authors tried to replicate the

results from “Euromoney” and “International Investor's” ratings, which was

successfully done. Their results indicate that country risk rating responds to the most

economic and political variables. For instance, in both magazines they rank less

indebted countries higher than more indebted countries. In conclusion, both

“Euromoney” and “International Investor's” results are highly correlated and both are

agree on factors or variables that determine the country risk of the assessed countries.

Another paper by Aswath (1999) suggests a new approach to measure risk premium.

All known methods are based on historical data, which is a main component in

measuring risk premium, as in the CAPM model and others. In this new method

which differs from the known and traditional methods, no historical data are needed.

In addition, the author suggests deriving the equity risk premium from equity prices.

In this method we can take externally (without using historical data) the value of the

market, the expected dividends next period, and the expected growth rate. From these

values we can extract the required return on equity by using simply the present value

equation of the market value, and by subtracting the risk-free rate from the required

return on equity we get the risk premium. Aswath mentioned in his paper the

disadvantage from using historical data which sometimes tend to be limited and noisy

and comes with higher standard errors. Therefore, he suggests this new method to

measure risk premiums without the need of historical data.

There is another interesting paper by Ekpenyong and Umoren (2010), in which the

authors turn their attention to the political risk issue as an integral part of almost every

business. The definition of political risk is wider in this paper. Companies usually use

defensive or integrative strategies to cope with political risk. The writers suggest

adopting the modified integrative strategy to cope with political risk.

The paper by Clare and Gang (2010) studies the effect of exchange rate and political

risks in foreign direct investments. According to the paper, companies investing in

developed countries observe the past and the present variation in exchange rates (they

assume that in developed countries the political issues are stable over time). When the

investments are made in less developed countries (emerging markets) they observe

the present and the future variation in exchange rate (they rely more on the

expectations since political situation is less stable than in developed countries).

Decreasing political risks will increase foreign direct investments. The main results

are negative effect of exchange rate risks to foreign direct investments and positive

effect of political stability to foreign direct investments.

For summarizing the main findings from previous papers, I have found that political

risks either in terms of election, wars or unstable regime affect the market risk and the

risk premium of the country. These papers, mentioned above, found explicit link

between the political risk, market risk and risk premiums and some of them encourage

companies to take these risks into account when it comes to investments in emerging

or other undeveloped markets.

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4. Theory\Method

When it comes to evaluating their investment opportunities, investors look for the

highest return that they can earn corresponding with the lowest risk among the

opportunities available in the market. Hence, the valuation of market risk and risk

premium is an important factor for the investors when they decide whether to make a

move to a specific market or not, especially in Israel, because of political changes.

There are several ways to calculate the risk premium by using accepted models. In

this section the reader is presented to the most two appropriate methods (in section

4.2.2) from the total prior selection (in section 4.1). The way of calculating the market

risk is presented (in section 4.2.1) and two ways of calculating the variance of the

returns are presented by a moving average method and by using GARCH models.

Clarification of “market risk” and “risk premium” is therefore required.

Market risk reflects the risk of declines or losses in the value of any portfolio due to

uncertain factors related to the market. The market value of a well diversified

portfolio is affected by so called uncertain macro-economic factors, such as interest

rate, stock prices and foreign exchange rate. Market risk is also called systematic risk

(see CAPM model in section 4.1). This kind of risk cannot be diversified away from

the entire risk in any portfolio. In other words, holding a not well diversified portfolio

may include market risk and other risks.

Risk premium reflects the difference in the risks associated with two or more different

investment choices faced by the investor. For instance, the investor will choose

between risk free bonds and other risky asset. Then, the difference between the return

of the specific risky asset to the bond is the risk premium, or one can say that the term

"risk premium" is the reward for holding a risky investment rather than a risk free

one.

4.1 Measuring Risk Premium

All risk and return models break the return from any investment into two components.

The first is the "built in" risk for a specific investment (unsystematic risk), the second

is the market risk that cannot be diversified or eliminated (systematic risk).

As stated above, there are several different models for measuring the risk premium.

For instance, there is the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing

Theory model (APT), and the Multi Factor model4. In this paper the CAPM is

presented shortly as a background for the reader to understand how the risk premium,

in general, is measured since the CAPM model is the most widely used model

concerning this subject.

4More details about measuring risk premium models mentioned above are available in the book

“Investments”, 8th

edition, by Bodie Z., Kane A., and J. Marcus A. Chapter 9 p. 279 and chapter 10

p.319.

http://www.businessdictionary.com/definition/reward.html

http://www.investorwords.com/2599/investment.html

- 12 -

The CAPM model is used to determine the required rate of return on investing in a

risky asset, when investors believe that they should be compensated over the expected

value of the theoretical risk free rate. It takes into account the sensitivity of the assets

to the market risk, which is usually denoted by Beta and the expected market return

(the Beta of the company is the risk of investing in the specific company compared to

the risk in investing in the overall market). In this model there are also some

assumptions shown like no transaction costs and no taxations.

The CAPM formula is:

Rr= R

f + β * (R

M- R

f)

Where:

Rr is the required rate of return on the risky asset.

Rf is the risk free rate of return in the market.

RM

is the expected return in overall market.

β is the specific Beta of the company or the sector of the assets.

(RM

- Rf) is the expected risk premium

When the risk free rate of return is observed, the expected return from the overall

market and the appropriate Beta, the required rate of return on the specific assets can

be simply measured. Then the CAPM is actually pricing the assets. When the assets

are traded below the expected return, then the assets are undervalued and vice versa.

For instance, if β is equal to 1 (β=1), consequently, the risky asset(s) has the same risk

or standard deviation as the market portfolio, both move in the same direction. When

β is larger than 1 (β>1), consequently, the risky asset(s) is more sensitive than the

market portfolio. In this case, if the market portfolio increases in 1%, the risky asset

will increase in more than 1%. When β is less than 1 (β<1) the risky asset is less

sensitive than the market portfolio. In this case, if the market portfolio increases in

1%, the risky asset will increase in less than 1%.

4.2 Measuring market and country risk

4.2.1 Estimating the market risk Market risk is usually measured with the standard deviation of returns for an

appropriate stock market index. Two methods to estimate the variance of the returns

from the stock market are presented here: “moving average” method and the

“GARCH model”. The variance of the returns will be used later to measure the

market and the country risk. Here GARCH model is used to test the robustness of the

results from measuring the risk premium (only) based on the “moving average”

method.

- 13 -

Moving average:

The “moving average” method is a statistical tool widely used to smooth the noisy

data in order to create the trend of the data. It is simply taking the average value over

specific time periods or specific subset from the entire data, as follows:

σ2

t=(1/M)*∑

This method was used to measure the market risk in Israel (in section 4.2.2) and to

measure the country risk in the method "Relative Equity Market Standard Deviation"

(in section 4.2.3) for both Israeli and USA stock markets. It is widely acceptable in

measuring the standard deviation of the returns by the “moving average” to assume

that the mean of the returns is zero (ȓ≈0). The standard deviation of the rate of return

from the stock market is widely used as a proxy of market risk. For this purpose

(measuring market risk) I calculated the returns of the Index-100 from the Israeli

stock market (TASE). The standard deviation is calculated by the moving average

method. The returns are in weekly terms, so I took the first eight weeks and calculated

the standard deviation; this is my first observation. The second observation is the

standard deviation of the returns from week two to week nine. The third observation

is the standard deviation of the returns from week three to week ten and so on. Thus,

each observation (standard deviation) is the average of eight returns’ standard

deviations. In this way I calculated the standard deviation from the Israeli stock

market which will be used later as a proxy of the market risk.

GARCH model:

GARCH (generalized autoregressive conditional heteroskedasticity) is a part of the

ARCH family. The main objective of using this method is the fact that the volatility of

return/risk premium can vary over time. In other words, the volatility of the return is

not constant over time.

To understand the need for models like GARCH, we need first to understand the term

“homoscedasticity”. Homoscedasticity refers in econometrics to the assumption that

the variance of the dependent variable is constant and do not vary over time. This

assumption is important since when the variance is constant, the estimated

coefficients in the model will be consistent and efficient5. If we have

heteroskedasticity it means that the Ordinary Least Square (OLS) estimator will be

inefficient.

When the variance of the dependent variable in the model is not constant, i.e. vary

over time, it is called “heteroskedasticity”. This case is the opposite of

homoscedasticity. According to the paper by R. Perrelli 2001, in most of the cases in

financial data large and small errors occurs in clusters, which means that large errors

usually follow large errors and small errors usually follow small errors – clustering.

All these facts allow us to conclude that the variances are not constant over time, it

vary over time, so the assumption of homoscedasticity is violated. That is why we

need to use the GARCH model to test if the time series have the clustering

characteristic.

5 Consult the book Econometric Analysis, 6

th edition, by William H. Greene.

- 14 -

The main issue in this method is to analyze the volatility of the error term over the

political instability periods under the assumption of heteroskedasticity. For this

purpose the software Stata (statistical package for data analysis) was used to produce

the variance of the rate of returns. To proceed with this model I assumed

GARCH(1,1), which mean we have lag one for the variance of the error term and lag

one for the error term itself.

The estimated standard deviations (square root of variance) from the GARCH model

is used to analyze the risk premium from the method "Relative Equity Market

Standard Deviation" (presented in section 4.2.3).

The consequent procedure of producing the variance is presented by using the

software Stata.

The first step in this procedure is to find the error term, for this purpose I regress the

following:

rt=α+β*rt-1+εt

where rt is the rate of return at time t, rt-1 is the rate of return lagged one period and εt

is the error term of this regression. To model the conditional variance a GARCH (1,1)

model is specified as

εt= σt * ut

where ut is standard normally distributed (i.e. ut ~ N(0,1)) and

σ2

t=γ0+γ1* εt-1+γ2* σ2t-1

The error term εt is conditionally heteroscedastic with respect to εt-1,

Var (εt│εt-1) = γ0+γ1* ε2

t-1

4.2.2 Country risk Israel is classified as an emerging market for the period of this study. In both papers

"Measuring Company Exposure to Country Risk: Theory and Practice" and

"Estimating Equity Risk Premiums" by Aswath (2003), it is not applicable to use

short and volatile historical data in order to measure risk premium in emerging

markets, as the models mentioned in section 4.1 require. Aswath, in his paper

"Estimating Equity Risk Premiums" (2003) shows the same tendency in Europe when,

for example, Germany is a mature country in economy aspect but the market, on the

other side, does not have to share the same characteristics of mature market. In the

same paper the author estimates risk premiums for several European countries for 26

years from 1970 to 1996 and these results come with 5% standard errors. Thus, we

can imagine how much it will be noisy and useless to use historic data to measure risk

premium in emerging markets such as Israel. Therefore, I will use the US market as a

benchmark since investors often see the US market as one of the safest markets in the

world.

- 15 -

For the reasons mentioned above, I adopted the alternative method, by Aswath

(2003), to measure the risk premium in an emerging market. This alternative method,

called the "Modified Historical Risk Premiums", is presented as follows:

The expected equity premium for emerging markets can be written as:

Expected return = Expected return from mature country + Country risk

The country risk can be represented as the differences between the expected return of

the country minus the expected return from mature country. The purpose is to

measure the country risk that can reflect the risk premium for every specific country.

The following 2 methods are used widely to measure country risk:

1- Country Bond Default Spreads is the most common and easiest method used

in measuring country risk. In this method we look at the yields to maturity

from Treasury bonds in the two countries, the mature and the country in

question. The difference in the yields to maturity between the two countries

should reflect the country risk and the default risk hidden in the specific

country.

2- Relative Equity Market Standard Deviation, where we measure the country

risk by using the volatility of the stock exchange markets. We believe that

stock exchange markets associated with high volatility reflect more risky

markets rather than low volatility. If we divide the standard deviation of the

stock market in the country by the standard deviation of the stock exchange

market of the mature country, we obtain the relative standard deviation.

Relative Standard DeviationSpecific country

= σIs

/σUS

If the relative standard deviation is multiplied by the premium which is used

for the mature market, the equity risk premium for the specific country is

obtained.

Equity Risk PremiumIsrael

=Risk PremiumUSA

*Relative Standard DeviationIs.

For the purpose of my research I adopted the approach of "Country Default Spread"

and the approach of "Relative Equity Market Standard Deviation" for two main

reasons. First of all, these approaches are the most widely used measures of country

risk. Secondly, collecting data for Israeli market was not that easy and the limitation

of time only enabled me to work with the available data that I could obtain. Finally, I

found that the "Country Default Spread" and the "Relative Equity Market Standard

Deviation" are the most suitable approaches in this case study of Israel.

- 16 -

In the method "Relative Equity Market Standard Deviation" the standard deviation,

which comes from the moving average method, and the variance from the GARCH

model, are used.

Hence, "Country Bond Default Spreads" and "Relative Equity Market Standard

Deviation" are used to study the effect of the political instability on the Israeli market.

In the "Country Bond Default Spreads" method, monthly measured average of the

yields to maturity of the Israel Treasury bond for 10 years are compared to USA

Treasury bond for 10 years. The differences between the yields are used as the default

spread or the risk premium for the Israeli market. In the "Relative Equity Market

Standard Deviation" method, the ratio of the volatility on Israeli Equity Market to the

volatility on the USA Equity Market is observed. Finally, the changes in the risk

premium, through the past decade focusing on the political tension periods, are

analyzed.

4.3 Econometric models

To test if the market risk/risk premium is affected by political tension three

econometric models are used in order to analyze the data. The first model is specified

as:

(1) σt = α + β1 * MRt + β2 * (SD GDP)t + β3 * PIt + εt.

(2) RPt = α + β1 * MRt + β2 * (SD GDP)t + β3 * PIt + εt.

Here, in equation (1) σ is the market risk in Israel, measured by stock market standard

deviation. In equation (2) RP is the risk premium of Israel, measured either as bond

spread or relative stock market standard deviation. MR (in equation (1) and (2)) is the

Moody's rating of Israeli Treasury bonds. SD GDP (in equation (1) and (2)) is the

ratio between the volatility in GDP growth in Israel to the volatility in GDP growth in

USA. PI (in equation (1) and (2)) is a dummy variable controlling for periods of

political instability. For periods of political instability the dummy variable PI take the

value 1, otherwise zero. The "β" are associated coefficients for the variables and the

"ε" is a random i.i.d. term.

The need for other variables, except of political tension periods, is to control for

different factors that can affect the market risk/risk premium. The market risk/risk

premium could be affected from different factors except of political changes, for

instance, Moody’s rating and the growth in GDP as well. For these potentially

changes, the variables MR and SD GDP are added to the model to control the effects

of other factors, so I can extract the effect of political instability.

The second model is specified as:

(1) σt = α + β1 * MRt + β2 * (SD GDP)t + β3 * Elt + β4 * PI2t + εt.

(2) RPt = α + β1 * MRt + β2 * (SD GDP)t + β3 * Elt + β4 * PI2t + εt.

- 17 -

Here, in equation (1) and (2), the variables σ, RP, MR and SD GDP are described in

the first model. El (in equation (1) and (2)) is a dummy variable controlling for

periods of elections. PI (in equation (1) and (2)) is a dummy variable controlling for

periods of political instability (without elections). For periods of political instability

the dummy variable PI take the value 1, otherwise zero and for periods of elections

the dummy variable El take the value 1, otherwise zero. The "β" are associated

coefficients for the variables and the "ε" is a random i.i.d. term.

The purpose of the second model is to check and to control the effect of the political

instability periods on risk premium in Israel. It can be argued that elections are not

political instability in the definition so I decide also to separate the elections periods.

The third model is specified as:

(1) σt = α + ∑ + β9 * MRt + β10 * (SD GDP)t + εt.

(2) RPt = α +∑ + β9 * MRt + β10 * (SD GDP)t + εt.

Here, in equation (1) and (2), the variables σ, RP, MR and SD GDP are described in

the first model. PIit (in equation (1) and (2)) is a dummy variable controlling for 8

periods (exactly in the same order as in section 2.2) of political instability. For periods

of political instability the dummy variable PIit take the value 1, otherwise zero. The

"β" are associated coefficients for the variables and the "ε" is a random i.i.d. term.

The purpose of the third model is to check and to control the effect of each political

instability periods separately on market risk and risk premium in Israel. There are 8

political periods and this model tests to which extend each period of political

instability affects the market risk and risk premium in Israel.

It is important to note that the four regressions have been run for every model

estimated by ordinary least squares (OLS). The first regression ran equation (1) when

the market risk (dependent variable) is the stock market standard deviation estimated

by moving average method. The second regression ran equation (2) when the risk

premium (dependent variable) is the difference between the yields to maturity on

Treasury bonds. The third regression ran equation (2) when the risk premium

(dependent variable) is the relative standard deviation on the equity markets estimated

by moving average method. The fourth regression ran equation (2) when the risk

premium (dependent variable) is the relative standard deviation on the equity markets

estimated by GARCH model.

To summarize, equation (1) is concerning market risk, equation (2) is concerning the

method "Country Default Spread" and the method "Relative Equity Market Standard

Deviation".

- 18 -

5. Data

As it is described in the previous section, the return standard deviations (estimated by

the moving average method) of the Israeli stock market will be used as a proxy for

market risk. "Country Bond Default Spreads" method and the "Relative Equity

Market Standard Deviation" method are used to test the effect of the political

instability on the risk premium in Israel. The monthly yields to maturity on bonds

issued by Israel Treasury and US Treasury bond for 10 years are collected, starting

from the period 5/2001 to 3/2010. These 10 years yields to maturity are to be used for

the "Country Bond Default Spreads" method. For the "Relative Equity Market

Standard Deviation" method the weekly indexes from Tel Aviv 100 in Israel and from

S&P500 in USA in weekly returns are collected from 1/2001 to 3/2010. The monthly

yields to maturity of the Israeli Treasury bond are collected from the website of the

Bank of Israel (central bank) and the monthly yields to maturity of the US Treasury

bond are collected from the website of the USA Central Bank (Federal Reserve

System). The weekly rate of returns of the Israeli market are collected from the

website of the Tel Aviv Stock Exchange (TASE) and the weekly rate of returns from

the S&P500 in USA are collected from the website of Standard & Poor’s (S&P).

The "Country Bond Default Spreads" method focuses on the difference between the

yields to maturity that the Israeli's bond gives over the US Treasury bond. The

difference expresses the risk premium hidden in the Israeli market. In this method I

focused mainly on the difference in the risk premium between the two countries and I

gave explanations of the volatility through time while the attention is directed towards

the changes in the political instability. For the "Relative Equity Market Standard

Deviation" method the analysis of the difference in the standard deviations (estimated

either by moving average or GARCH model) between Israel and USA equity markets

is given. This shows the volatilities in the market that can reflect the risk premium in

Israel.

To this data, information about Moody's rating of the Israeli Treasury bond is added

through the time in aim to analyze and explain the changes in the Israeli risk premium

regarding any kind of disturbances.

The changes in monthly yields to maturity on Israel and USA Treasury bonds

between May 2001 and March 2010 are presented in Figure 4 below.

- 19 -

Figure 4: Changes in monthly yields to maturity on Israel and USA Treasury bonds.

Figure 4 shows an almost stable difference in yields to maturity between USA and

Israel. The big difference can be seen between the years 2001 to 2003 mostly

followed by the Second Intifada.

Figure 5 below presents the weekly standard deviation (estimated by moving average

method) in Israel and USA equity market between January 2001 and March 2010.

Figure 5: Weekly standard deviation in Israel and USA equity markets.

Figure 5 shows that during the last 10 years the US and Israeli equity market standard

deviation are in the interval from 0.02 to 0.08, except for the period in the Second part

of 2008. It seems to be the results of the financial crisis in the global market 2008-

2009.

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- 20 -

In order to estimate risk premium (RP) with the GARCH model, Table 1 shows the

outcome from the Stata software for the Israeli stock market and Table 2 shows the

outcome from the Stata software for the USA stock market:

Table 1: GARCH model, Israeli stock market

Coef. Std. Err. z Return: rt-1 .026 .048 0.54 constant 000. .001 2.55 Arch: arch L1 .1 .022 4.59

garch L1 .831 .044 19.04

constant .000 .000 2.16

Table 2: GARCH model, USA stock market

Coef. Std. Err. z Return: rt-1 -.046 .056 -0.83 constant .002 .001 2.03 Arch: arch L1 .227 .028 8.06

garch L1 .731 .036 20.35

constant .000 .000 2.94

Table 1 and 2 together show that we have ARCH term (εt-1) and GARCH term (σ2

t-1)

for both markets (at 5% level), which means that γ1 and γ2 are significantly different

from zero. This information indicates that we have conditional “heteroskedasticity”

and the data is clustered.

The last step is to produce the fitted or the estimated variances of the error term σ2

t,

for both Israel and USA, σ2

tIs

and σ2

tUS

, respectively. This step is also done in Stata.

Table 3 gives descriptive statistics for the dependent variables that are analyses in the

models used in this study and for the independent variable measuring the ratio in the

changes between Israel to USA in "standard deviation in gross domestic product" as

well:

Table 3: Descriptive Statistics.

Default

Spread

Relative

Equity

Market SD

(by

“moving

average”)

Relative

Equity

Market

SD (by

GARCH

model)

Ratio in

GDP

quarter

changes

(SD

GDP)

Political

Instability

(PI)

Moody’s

Rating

(MR)

Mean 2.578 1.289 1.250 2.244 0.393 0.224

Standard deviation 1.637 0.560 0.358 2.783

0.491

0.419

Variance 2.681 0.314 0.128 7.747 0.241 0.176

Max 7.788 3.545 2.372 12.872 1 1

Min 0.130 0.494 0.464 0.311 0 0

- 21 -

Moody's rating and the political instability independent variables presented in Table 3

are dummy variables that can take values 0 or 1. For political instability the dummy

variable PI take the value 1 when there is political instability situation in the specific

period, otherwise 0. When Moody's rating upgrade the Israeli Treasury bond, the

dummy variable MR take the value 1, otherwise 0. It is worth mentioning that I did

not include control variables for the period of financial crisis in the global market

2008-2009. Thus, I assume that both countries, Israel and USA, are affected equally

by the financial crisis in this period.

The political tension periods, mentioned in section 2.2, are used to analyze the market

risk/risk premium over time. Afterwards, the yields to maturity, standard deviation

from Israel and USA equity market and the information in section 2.2 are the basic

data used to analyze the effect of the political instability on the market risk/risk

premium in Israel.

- 22 -

6. Results

In this section, the results from the empirical analysis are presented. The results are

presented separately for the three models. In Model 1, political instability periods are

aggregated into one dummy variable. In Model 2, political instability periods are

separated in two dummy variables between election periods and other political

instability periods. In Model 3, all political instability periods are separated into eight

dummy variables to test the effect of each individual period of political tension.

6.1 Results for Model 1: Table 4 shows the results from running a regression when the dependent variable is

the market risk in terms of returns’ standard deviation, estimated by moving average

method. The independent variables are Moody's rating to Israeli Treasury bond, the

ratio in GDP standard deviation between Israel and USA and the political instability

periods as given by:

σt/ RPt = α + β1 * MRt + β2 * (SD GDP)t + β3 * PIt + εt.

For this regression the residuals are significantly auto correlated and the adjusted R2

value is 0.32 with 473 observations. It is important to note, that the standard errors in

this table are not robust for serial correlation.

Table 4: Results model 1, market risk

Coefficients Standard Error t Stat

Intercept 0.020 0.001 26.470

MR 0.010 0.001 9.920

SD GDP 0.000 0.000 0.527

PI 0.010 0.001 11.468

Table 4 shows that standard deviation of GDP between Israel to USA has an

insignificant effect on Israeli market risk. The effect of the Moody's rating is

significantly (at 5% level) positive. Therefore, when Moody upgrades Israeli Treasury

bond, the market risk increases. This result is in contrast with my expectation. I would

suggest, that when Moody upgrade the Israeli Treasury bond, more investors join the

stock market, and that can increase the trading activity (higher volume). Higher

volume comes with higher volatility, which is exactly what this regression shows. The

effect of the political instability periods has a significant (at 5% level) on the market

risk. Tension periods lead to higher volatility in the stock market.

Table 5 shows results from running a regression when the dependent variable is the

risk premium/default spread between yields to maturity of Israeli Treasury bond and

USA Treasury bond for 10 years. The independent variables are Moody's rating to

Israeli Treasury bond, the ratio in GDP standard deviation between Israel and USA

and the political instability periods as it was mentioned in section 2.2.




- 23 -

Table 5: Results model 1, Default Spread method


Intercept 1.823 0.275 6.635

MR -0.488 0.350 -1.396

SD GDP 0.104 0.055 1.900

PI 1.664 0.308 5.409

Table 5 shows that Moody's rating has an insignificant effect on Israel risk premium.

The effect of the ratio of the standard deviation of GDP between Israel to USA is

significantly (at 10% level) positive. Therefore, the volatility of the gross domestic

product in Israel has a significantly positive effect on the risk premium, for instance,

if the volatility of the GDP is high, it is indeed indicating a non-stable economical

environment in the country increasing the risk premium. The effect of the political

instability on the risk premium is 1.664%. This means that investors on average

require 1.664% more over the risk free return from investing in Israeli Treasury bond

in political instable periods comparing to political stable periods. This later effect is

statistically significant (at 5% level).


relative Israeli equity market standard deviation to USA equity market standard

deviation (standard deviation of both countries are estimated by the moving average

method). The independent variables are Moody's rating to Israeli Treasury bond, the

ratio in GDP standard deviation between Israel and USA and the political instability

periods as it was mentioned in section 2.2.




Table 6: Results model 1, Relative Equity Market Standard Deviation (moving

average) method. Coefficients Standard Error t Stat

Intercept 1.514 0.048 31.232

MR -0.481 0.061 -7.832

SD GDP -0.037 0.010 -3.869

PI -0.083 0.054 -1.536

Table 6 shows that Moody's rating have a significantly (at 5% level) negative effect

on the difference between the standard deviation of Israel equity market and USA

market. This result makes sense in a way when Moody upgrade Israeli Treasury bond

investors will believe more in the bond that leads to decreasing risk premium. The

effect of the ratio in standard deviation in GDP between Israel to USA is significantly

(at 5% level) negative. Therefore, the volatility of the gross domestic product in Israel

has a significantly negative effect on the risk premium. For instance, if the volatility

of the GDP is high, followed by non stable economical environment in the country,

the risk premium will decrease. This result is in contrast with our expectations. We

expect to see positive effect instead of negative. We have this unexplained result only

in the "Relative Equity Market Standard Deviation" method. The effect of the

political instability on the difference between the standard deviation of Israel and

USA equity markets is insignificantly negative -0.083%. Someone could claim now

- 24 -

that political events will increase the volatility of Israel equity market which leads to

an increase in the difference between the standard deviation of Israel equity market to

USA and not to a decrease. The answer for the skeptical reader is that there are a lot

of Israeli companies listed in USA equity market (the largest number of NASDAQ-

listed companies outside North America) and when investors want to stop investing in

Israel, usually they do it by ceasing investments in all companies related to Israel or to

the Jewish community. That is, when investors stop investing in Israeli companies in

USA equity market, the volatility also in the USA equity market increases.

Table 7 shows results from running a regression while the dependent variable is the


deviation (standard deviation of both countries are estimated by GARCH model). The

independent variables are Moody's rating to Israeli Treasury bond, the ratio in GDP

standard deviation between Israel and USA and the political instability periods as it

was mentioned in section 2.2.




Table 7: Results model 1, Relative Equity Market Standard Deviation (GARCH

model) method.


Intercept 1.429 0.031 46.770

MR -0.337 0.039 -8.719

SD GDP -0.023 0.006 -3.713

PI -0.131 0.034 -3.877

Table 7 shows the same results concerning Moody's rating and the ratio in standard

deviation in GDP as in Table 6. The effect of the political instability on the difference

between the standard deviation of Israel and USA equity markets is statistically

significant negative -0.131%. Someone could claim now that political events will

increase the volatility of Israel equity market which can lead to an increase of the

difference between the standard deviation of Israel equity market to USA and not to a

decrease. The answer for the skeptical reader is that there are many Israeli companies

listed in USA equity market (the largest number of NASDAQ-listed companies

outside North America) and when investors want to stop investing in Israel, usually

they do it by ceasing investments in all companies related to Israel or to the Jewish

community. That is, when investors stop investing in Israeli companies in USA equity

market, the volatility also in USA equity market start to increase.

6.2 Results for Model 2: Table 8 shows results from running a regression, when the dependent variable is the

market risk in terms of returns’ standard deviation estimated by moving average


ratio in GDP standard deviation between Israel and USA, governments elections and

the political instability periods as given by:

σt/ RPt = α + β1 * MRt + β2 * (SD GDP)t + β3 * Elt + β4 * PI2t + εt.

- 25 -




Table 8: Results model 2, market risk. Coefficients Standard Error t Stat

Intercept 0.020 0.001 26.499

MR 0.010 0.001 10.075

SD GDP 0.000 0.000 0.413

El 0.005 0.002 2.866

PI2 0.009 0.001 10.959


deviation in GDP as in Table 4. The effect of the political instability periods and

election periods is significant (at 5% level) on the market risk. Tension periods lead to

higher volatility in the stock market.



USA Treasury bond for 10 years. The independent variables are Moody's rating of

Israeli Treasury bond, the ratio in GDP standard deviation between Israel and USA,

governments elections and the political instability periods as it was mentioned in

section 2.2.


value is 0.31 with 106 observations. Additionally, it is important to note, that the

standard errors in this table are not robust for serial correlation.

Table 9: Results model 2, Default Spread method. Coefficients Standard Error t Stat

Intercept 1.669 0.260 6.412

MR -0.375 0.336 -1.116

SD GDP 0.121 0.052 2.320

El 1.439 0.575 2.502

PI2 1.873 0.299 6.272


deviation in GDP as in Table 5. The effect of the government elections is 1.439%.

The effect of the political instability (without elections) on the risk premium is

1.873%, which indicates that investors on average require more 1.873% over the risk

free return from investing in Israeli Treasury bond. The government elections and the

political instability effect are statistically significant (at 5% level).


relative Israeli equity market standard deviation (standard deviation of both countries

are estimated by the moving average method) and USA equity market standard

deviation. The independent variables are Moody's rating of Israeli Treasury bond, the

ratio in GDP standard deviation between Israel and USA, governments' elections and

the political instability periods (without elections), as it was mentioned previously in

section 2.2.

- 26 -






Intercept 1.524 0.048 31.475

MR -0.491 0.062 -7.891

SD GDP -0.038 0.010 -3.977

El -0.016 0.109 -0.149

PI2 -0.103 0.055 -1.871


deviation in GDP as in Table 6. The effect of the government elections is

insignificant; they have no effect on the risk premium. The effect of the political

instability on the difference between the standard deviation of Israel equity market

and USA is significantly (at 10% level) negative -0.103%. Someone could claim now

that political events will increase the volatility of Israel equity market which leads to

increasing difference between the standard deviation of Israel equity market compared

to USA market and not to decrease. The answer for the skeptical reader is that there

are many Israeli companies listed in USA equity market (the largest number of

NASDAQ-listed companies outside North America) and when investors want to stop

investing in Israel, usually they do it by stop investing in all companies related to

Israel or to the Jewish community. In other words, when investors stop investing in

Israeli companies in USA equity market, the volatility also in USA equity market

increases.



deviation (standard deviation of both countries are estimated by GARCH model) and

the independent variables are Moody's rating to Israeli Treasury bond, the ratio in

GDP standard deviation between Israel and USA, governments' elections and the

political instability periods (without elections) as it was mentioned in section 2.2.





model) method.

Coefficients Standard Error t Stat Intercept 1.435 0.030 47.144

Moody's rating -0.342 0.039 -8.739

ratio GDP IL/USA -0.023 0.006 -3.835

election -0.133 0.069 -1.930

political instability -0.135 0.035 -3.907


deviation in GDP as in Table 6. The effect of the government elections is negative

- 27 -

statistically significant (at 10% level). Therefore, in the election periods the risk

premium in Israel decreases. The effect of the political instability on the difference

between the standard deviation of Israel equity market and USA is significant, at 5%

level, negative -0.135%. Someone could claim now that political events will increase

the volatility of Israel equity market which leads to increasing difference between the

standard deviation of Israel equity market compared to USA market and not to

decrease. The answer for the skeptical reader is that there are many of Israeli

companies listed in USA equity market (the largest number of NASDAQ-listed

companies outside North America) and when investors want to stop investing in

Israel, usually they do it by stop investing in all companies related to Israel or to the

Jewish community. In other words, when investors stop investing in Israeli companies

in USA equity market, the volatility also in USA equity market increases.

6.3 Results for model 3


market risk in terms of returns standard deviation estimated by moving average


ratio in GDP standard deviation between Israel and USA and the eight political

instability periods as given by:

σt/ RPt = α + ∑ + β9 * MRt + β10 * (SD GDP)t + εt.




Table 12: Results model 3, market risk.

Coefficients Standard Error t Stat Intercept 0.020 0.001 29.357 PI1 0.009 0.001 11.048 PI2 0.001 0.003 0.394 PI3 0.021 0.002 10.140 PI4 0.028 0.002 11.330 PI5 0.014 0.002 5.548 PI6 -0.002 0.004 -0.534 PI7 -0.010 0.004 -2.890 PI8 -0.011 0.004 -2.925 Moody's rating 0.010 0.001 9.700 ratio GDP IL/USA 0.000 0.000 0.764


deviation in GDP as in Table 4. The 17th

Knesset election and the UN special report

have an insignificant effect on the Israel market risk. Second Intifada, 2006 Lebanon

War, Gaza War and the 18th

Knesset election are significantly (at 5% level) positive.

Therefore, in these periods the market risk increased. The tension with Turkey and

Al-Mabhouh controversy are significantly (at 5% level) negative, which means in this

period the market risk decreased. Please, consult section 2.2 to link between the PIi to

the specific event (i=1…8), for instance, PI1 related to the Second Intifada as it is

described on page 5 section 2.2.

- 28 -



USA Treasury bond for 10 years. The independent variables are Moody's rating of

Israeli Treasury bond, the ratio in GDP standard deviation between Israel and USA,

and the eight political instability periods as it was mentioned in section 2.2.




Table 13: Results model 3, Default Spread method.

Coefficients Standard Error t Stat Intercept 1.612 0.266 6.068 PI1 2.467 0.330 7.464 PI2 -0.008 0.956 -0.008 PI3 -0.068 0.798 -0.086 PI4 0.797 0.979 0.814 PI5 -0.009 0.979 -0.009 PI6 -0.201 1.348 -0.149 PI7 -0.467 1.348 -0.347 PI8 -0.577 1.348 -0.428 Moody's rating 0.183 0.392 0.466 ratio GDP IL/USA 0.116 0.051 2.274


deviation in GDP as in Table 5. All the tension periods except of the Second Intifada

are statistically insignificant, at 5% level, which means that all other tension periods

have no effect on the risk premium of Israel. The Second Intifada event is

significantly (at 5% level) positive. Therefore, in this specific political instability the

risk premium in Israel increased.


relative Israeli equity market standard deviation (standard deviation of both countries

are estimated by the moving average method) and USA equity market standard

deviation. The independent variables are Moody's rating of Israeli Treasury bond, the

ratio in GDP standard deviation between Israel and USA, and the eight political

instability periods as it was mentioned in section 2.2.




- 29 -


average) method.

Coefficients Standard Error t Stat Intercept 1.493 0.048 30.997 PI1 -0.185 0.059 -3.145 PI2 0.284 0.181 1.575 PI3 0.956 0.145 6.582 PI4 -0.186 0.175 -1.063 PI5 -0.137 0.175 -0.785 PI6 0.043 0.254 0.169 PI7 -0.036 0.255 -0.142 PI8 0.012 0.255 0.047 Moody's rating -0.461 0.070 -6.556 ratio GDP IL/USA -0.032 0.009 -3.460


deviation in GDP as in Table 6. The Second Intifada event is negative statistically

significant (at 5% level). Therefore, in this specific political instability the risk

premium in Israel decreased. The event of 2006 Lebanon War is positive statistically

significant (at 5% level). Therefore, in this specific period the risk premium in Israel

increased. All other tension periods are not statistically significant, which means no

effect on the risk premium.



deviation (standard deviation of both countries are estimated by GARCH model) and

the independent variables are Moody's rating to Israeli Treasury bond, the ratio in

GDP standard deviation between Israel and USA, and the eight political instability

periods as it was mentioned in section 2.2.





model) method.


Intercept 1.417 0.030 47.050

PI1 -0.201 0.037 -5.463

PI2 0.209 0.113 1.851

PI3 0.477 0.091 5.261

PI4 -0.183 0.109 -1.673

PI5 -0.327 0.109 -2.996

PI6 0.132 0.159 0.829

PI7 0.132 0.159 0.831

PI8 -0.085 0.159 -0.534

Moody's rating -0.329 0.044 -7.477

ratio GDP IL/USA -0.019 0.006 -3.344


deviation in GDP as in Table 6. The Second Intifada event is negative statistically

significant (at 5% level). Therefore, in this specific political instability the risk

- 30 -

premium in Israel decreased. The 17th

Knesset election is positively significant (at

10% level) which means in this period the risk premium increased. The event of 2006

Lebanon War is positive statistically significant (at 5% level). Therefore, in this

specific period the risk premium in Israel increased. The Gaza war event is negatively

significant (at 10% level). Therefore, in this period the risk premium decreased. The

18th

Knesset election is significantly negative (at 5% level). Therefore, in this period

the risk premium decreased. All other tension periods are not statically significant,

which means no effect on the risk premium.

There might be other explanations for these results derived especially from "Relative

Equity Market Standard Deviation" method in the three models. One of these

explanations is if the political instability increases, then the uncertainty among the

investors increases as well. Consequently, it leads to lower trading activity or lower

volume in the stock market, meaning that fewer investors want to buy and fewer

investors want to sell in discount. Lower volume in its turn leads to less trading which

comes with lower volatility in the stock market. This explanation could be reasonable

if the investors believe that this is a temporary tension and the panic, due to new

political information, will pass among investors. This later explanation could be

reasonable for domestic investors who are less sensitive to political news or events

rather than foreign investors.

It is important to note that the risk premium’s results from the three models used in

this study are different in some parts. From the default spread method the risk

premium - of the country hidden in the yields to maturity from the Treasury bonds – is

significantly (at 5% level) positive affected by the political instability in general.

From relative equity market standard deviation (estimated either by moving average

method or GARCH model) method the risk premium – of the country hidden in the

volatility of the equity market – is negatively affected by the political instability.

It is worth mentioning that in this thesis I did not separate the investors into domestic

and foreign investors, except of the fact that risk market can be implied more for

domestic investors. Usually foreign investors are more skeptical compared to

domestic investors. In the paper "Do domestic investors have more valuable

information about individual stocks than foreign investors? By Hyuk Choe, Bong-

Chan Kho, and René M. Stulz, Current draft, December 2000 – pages 1 and 22" it is

mentioned that "domestic individual investors have a short-lived private information

advantage for individual stocks over foreign investors". Thus, foreign investors can

see the risk premium slightly different from domestic investors, but that does not

change the results we achieved in this thesis.

Despite of the good financial results that Israel shows, it can be noticed from the data,

as well as from the diagram, that there is still a difference between the yields to

maturity from USA Treasury bonds to Israeli Treasury bonds and higher volatility in

Israeli equity market. The fact that risk premium is not zero can be explained by the

ongoing difficult security environment, which continues to constrain Israel's credit

ratings. Further, it led to higher required rate of return on investing in Israeli bonds.

- 31 -

6.4 Robustness test

Due to the auto correlation, some of the previous results can be questioned. Thus, to

test the robustness of these results, models including lags of the dependent variable

are included to account for the auto correlation. In this section, the regressions are

repeated for the regression where we had auto correlation in section 6.1, 6.2 and 6.4.

For market risk and the method “Default Spread” the models include two lags of the

endogenous variable in the three models and for the method “Relative Equity Market

Standard Deviation” one lag of the endogenous variable is included in the three

models. The choice of lags was determined to render regressions with auto

correlation. The results are presented in Appendix in page number 37.

Model 1: Table 16 shows results from running the following regression:

σt = α + β

1 * σ

t-1+ β

2 * σ

t-2+ β

3 * MR

t + β

4 * (SD GDP)

t + β

5 * PI

t + ε

t

where the dependent variable is the market risk. For this regression there is no auto

correlation left and the adjusted R2 value is 0.921 with 471 observations. Table 16

shows that the main variable of interest PI is significantly positive (at 5% level),

different from zero. This result is in the same line with our previous results. Political

instability affects the market risk in Israel.

Table 17 shows results from running the following regression:

RPt = α + β

1 * RP

t-1 + β

2 * RP

t-2 + β

3 * MR

t + β

4 * (SD GDP)

t + β

5 * PI

t + ε

t

where the dependent variable is the spread between the yields to maturity of Israeli

Treasury bond and USA Treasury bond. For this regression there is no auto


shows that the main variable of interest PI is not significantly different from zero.

Table 18 shows results from running the following regression;

RP

t = α + β

1 * RP

t-1 + β

2 * MR

t + β

3 * (SD GDP)

t + β

4 * PI

t + ε

t.

where the dependent variable is the relative equity market standard deviation (estimated by

moving average method) for Israel. For this regression there is no auto correlation left

and the adjusted R2 value is 0.87 with 471 observations. Table 18 shows that the main

variable in interest PI is not significant different from zero.


RP

t = α + β

1 * RP

t-1 + β

2 * MR

t + β

3 * (SD GDP)

t + β

4 * PI

t + ε

t.


GARCH model) for Israel. For this regression there is no auto correlation left and the

- 32 -

adjusted R2 value is 0.78 with 471 observations. Table 19 shows that the main

variable in interest PI is not significantly different from zero.


σt = α + β

1 * σ

t-1+ β

2 * σ

t-2+ β

3 * MR

t + β

4 * (SD GDP)

t + + β

5 * El

t + β

6 * PI2

t + ε

t



shows that the main variable of interest PI is significantly positive (at 5% level),

different from zero. This result is in the same line with our previous results. Political



RP

t = α + β

1 * RP

t-1 + β

2 * RP

t-2 + β

3 * MR

t + β

4 * (SD GDP)

t + β

5 * El

t + β

6 * PI2

t + ε

t.


Treasury bond and USA Treasury bond. For this regression there is no auto


shows that the main variable in interest PI is significant, at 5% level, positive, which

repeats the same results that we had in Table 4 before correcting auto correlation.


RP

t = α + β

1 * RP

t-1 + β

2 * MR

t + β

3 * (SD GDP)

t + β

4 * El

t + β

5 * PI2

t + ε

t.


moving average method) for Israel. For this regression there is no auto correlation left


variable in interest PI is insignificant.


RP

t = α + β

1 * RP

t-1 + β

2 * MR

t + β

3 * (SD GDP)

t + β

4 * El

t + β

5 * PI2

t + ε

t.


GARCH model) for Israel. For this regression there is no auto correlation left and the


variable in interest PI is insignificant.


σt = α + ∑

+β

9 * σ

t-1+ β

10 * σ

t-2+ β

11 * MR

t + β

12 * (SD GDP)

t + ε

t

- 33 -



shows that the main variable of interest PIi is significant, at 5% level, positive

different from zero when i=1, 3 and 4. All other PIi i≠1, 3 and 4 are not statistically

significant. This result is in the same line with our previous results. Political



RP

t = α + ∑

+ β

9 * RP

t-1 + β

10 * RP

t-2 + β

11 * MR

t + β

12 * (SD GDP)

t + ε

t.


Treasury bond and USA Treasury bond. For this regression, there is no auto


shows that the main variable in interest PIi is significantly positive (at 5% level) only

when i=1 (related to the first event or the Second Intifada), which repeats the same

results that we had in the section 6.1 before correcting auto correlation.


RPt = α + ∑

+ β

9 * RP

t-1 + β

10 * MR

t + β

11 * (SD GDP)

t + ε

t.


moving average method) for Israel. For this regression, there is no auto correlation left


variable in interest PI is significant only when i=2 or 3 (related to the events election

and the 2006 Lebanon war). Other i≠2 or 3 are not statistically significant.


RPt = α + ∑

+ β

9 * RP

t-1 + β

10 * MR

t + β

11 * (SD GDP)

t + ε

t.


GARCH model) for Israel. For this regression, there is no auto correlation left and the


variable in interest PI is significantly positive, at 5% level, when i=3 (related to the

event the 2006 Lebanon war), and it is significantly negative, at 10% level, when i=5

(related to the event 18th

Knesset election. Other i≠2 are not statistically significant.

- 34 -

7. Conclusions

The purpose of this master thesis was to observe how political instability affects the

market risk and the risk premium on the financial markets in Israel by three models.

The returns standard deviation from the Israeli stock market was used as a proxy for

the market risk. Measuring risk premium was done by using the methods "Country

Default Spread" and the approach "Relative Equity Market Standard Deviation",

where the standard deviation was estimated by the moving average method and by the

GARCH model. These models are the most widely used to measure the market risk

and the risk premium. In the "Country Default Spread" method I looked at the yields

on bonds issued by the Israeli government where there is a "default free" bond (in this

case I used USA Treasury bond) yields to which I can compare. In the "Relative

Equity Market Standard Deviation" method I looked at the relative volatility of Israel

equity market compared to the volatility of USA equity market. The standard

deviation of the stock market used in the "Relative Equity Market Standard

Deviation" method was estimated by the methods moving average and GARCH

models.

From part of the results we can see that there is an effect of the tension periods

(political instability) on the market risk and on the risk premium in Israel.

Results from Model 1 show that political instability positively affects the market risk

in Israel, and show that political instability positively affects the risk premium only

when we imply the "Country Default Spread" method. "Relative Equity Market

Standard Deviation" method shows that political instability negatively affects the risk

premium when the standard deviation is estimated by GARCH model. When the

standard deviation was estimated by moving average method, no effect of the political

instability was found on the risk premium.

Results from Model 2 show that political instability, both in election terms or other

political tension periods, positively affects the market risk in Israel, and shows that

political instability, either in elections terms or other tension periods, positively

affects the risk premium only when we imply the "Country Default Spread" method.

"Relative Equity Market Standard Deviation" method shows that political instability,

both in election terms or other political tension periods, negatively affects the risk

premium when the standard deviation is estimated by GARCH model. When the

standard deviation is estimated by moving average method, the result shows effect of

the political instability (without elections) at low confidence level.

Results from Model 3 show that most of the political instability periods affect the

market risk in Israel, and shows that the Second Intifada is the only event that

positively affects the risk premium when we imply the “Country Default Spread”

method. "Relative Equity Market Standard Deviation" method (when the standard

deviation is estimated by moving average method) shows that the Second Intifada

event negatively affects the risk premium and the event of Lebanon War positively

affects the risk premium in Israel. While the standard deviation is estimated by

GARCH model, the Second Intifada and the Knesset 18th

elections events negatively

affect the risk premium. On the other hand, Lebanon War and the Knesset 17th

elections positively affect the risk premium in Israel.

- 35 -

The analyses of the data by three models show significant effect (either positively or

negatively) of the political instability periods on the market risk and risk premium.

Even though, not all the estimated coefficients were significant but in most of the

results there is a link between the market risk, risk premium, and political instability

periods. In section 6.4, I checked the robustness of the results; the repeated results are

less significant (lower confidence level). Therefore, in my point of view, the "Country

Default Spread" method and the “Relative Equity Market Standard Deviation" method

should be questioned again. GARCH model is one of the recent developments in the

literature and it is widely used in prediction’s models. I am more inclined to trust the

results from GARCH model, which shows that the political instability periods does

not affect (in most of the periods) the risk premium in Israel as it can be seen from

section 6.4 (Table 19, 23, and 27), because of the statistically weakness of the

coefficients (not significant). The data consists of weekly rate of returns; therefore,

there is no effect of the political instability periods on weekly returns. My own

interpretation is that the political events affect the risk premium in daily effect only

because of the first shock, and after some time the stock market reforms or corrects

itself and go back to normal state. In my point of view, the Israeli market is strong and

resistant against political news or political shocks. I believe that the ongoing political

instability in Israel made the stock market less sensitive and automatically slowed

down external effects such as political events.

The market risk and risk premium in Israel seem to occur for two main reasons. One

of the reasons is the ongoing intension in the political environment and the second

reason is the fact that the Israeli market is classified as an emerging market, by

Morgan Stanley Capital International (MSCI), regarding this study. If these two

reasons are eliminated, it seems to be that Israel will have no risk country or

additional risk premium.

Finally, it is important to note that the results vary among the methods used in this

paper and it depends on which method we use. The results vary mainly when it comes

to risk premium.

- 36 -

Appendix



Intercept 0.001 0.000 3.157

Ơt-1

1.132 0.045 24.928

Ơt-2

-0.204 0.046 -4.466

MR 0.001 0.000 1.706

SD GDP 0.000 0.000 0.803

PI 0.001 0.000 2.316

Table 17: Results model 1, Default Spread method


Intercept 0.121 0.094 1.291

RPt-1

1.351 0.092 14.725

RPt-2

-0.426 0.089 -4.760

MR -0.058 0.099 -0.587

SD GDP 0.015 0.016 0.972

PI 0.139 0.098 1.415



Intercept 0.090 0.032 2.803

RPt-1

0.931 0.017 53.614

MR -0.023 0.025 -0.937

SD GDP -0.001 0.004 -0.198

PI 0.017 0.020 0.853


model) method. Coefficients Standard Error t Stat

Intercept 0.195 0.037 5.270

RPt-1

0.863 0.024 36.685

MR -0.046 0.021 -2.151

SD GDP -0.003 0.003 -0.884

PI -0.016 0.018 -0.885

- 37 -



Intercept 0.001 0.000 3.112

Ơt-1

1.129 0.046 24.770

Ơt-2

-0.199 0.046 -4.362

MR 0.001 0.000 1.809

SD GDP 0.000 0.000 0.784

El 0.000 0.001 -0.124

PI 0.001 0.000 2.413


Intercept 0.120 0.092 1.298

RPt-1

1.334 0.092 14.457

RPt-2

-0.425 0.090 -4.743

MR -0.051 0.099 -0.516

SD GDP 0.020 0.016 1.283

El 0.218 0.173 1.260

PI2 0.204 0.103 1.987



Intercept 0.094 0.032 2.908

RPt-1

0.930 0.017 53.535

MR -0.025 0.025 -1.002

SD GDP -0.001 0.004 -0.293

El 0.021 0.041 0.512

PI2 0.011 0.021 0.511



Intercept 0.198 0.037 5.313

RPt-1

0.861 0.024 36.569

MR -0.045 0.021 -2.112

SD GDP -0.003 0.003 -0.926

El -0.035 0.035 -1.004

PI2 -0.014 0.018 -0.775

- 38 -



Intercept 0.002 0.000 3.952 PI1 0.001 0.000 2.837 PI2 0.000 0.001 0.324 PI3 0.003 0.001 3.674 PI4 0.003 0.001 2.499 PI5 0.001 0.001 0.575 PI6 -0.001 0.001 -0.751 PI7 -0.001 0.001 -0.864 PI8 -0.001 0.001 -0.513 Ơ

t-1 1.103 0.046 23.980

Ơt-2

-0.206 0.046 -4.452

MR 0.001 0.000 2.629

SD GDP 0.000 0.000 1.070


Intercept 0.127 0.099 1.289 PI1 0.322 0.128 2.505 PI2 -0.099 0.294 -0.335 PI3 0.103 0.246 0.420 PI4 -0.171 0.303 -0.565 PI5 -0.101 0.304 -0.330 PI6 -0.046 0.414 -0.112 PI7 -0.188 0.414 -0.453 PI8 -0.106 0.415 -0.255

RPt-1

1.307 0.096 13.587

RPt-2

-0.410 0.092 -4.457

MR 0.062 0.121 0.511

SD GDP 0.022 0.016 1.337



Intercept 0.112 0.034 3.329 PI1 0.002 0.024 0.103 PI2 0.154 0.071 2.164 PI3 0.183 0.059 3.079 PI4 0.016 0.069 0.236 PI5 -0.044 0.069 -0.633 PI6 -0.026 0.100 -0.260 PI7 0.000 0.100 -0.001 PI8 -0.002 0.100 -0.022

RPt-1

0.912 0.018 50.035

MR -0.018 0.029 -0.627

SD GDP 0.000 0.004 -0.042

- 39 -



Intercept 0.224 0.039 5.691 PI1 -0.025 0.021 -1.225 PI2 0.056 0.061 0.910 PI3 0.114 0.050 2.270 PI4 -0.012 0.059 -0.200 PI5 -0.099 0.060 -1.659 PI6 -0.028 0.086 -0.324 PI7 -0.052 0.086 -0.607 PI8 -0.015 0.086 -0.177

RPt-1

0.838 0.025 33.368

MR -0.041 0.025 -1.602

SD GDP -0.002 0.003 -0.713

- 40 -

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http://www.globes.co.il/news/article.aspx?did=1000546140


ANIMA Investment Network, invest in Israel, investment promotion centre of Israel’s

Ministry of Industry, Trade and Labor, Foreign Trade Administration

http://www.animaweb.org/en/pays_israel_agencepromotion_en.php

USA Central Bank, for yields to maturity of treasury bonds

http://www.federalreserve.gov/releases/h15/data/Monthly/H15_TCMNOM_Y10.txt

Israel Central Bank, for yields to maturity of treasury bonds

http://www.bankisrael.gov.il/firsteng.htm

TASE website, the website of Tel Aviv Stock Exchange in Israel

http://www.tase.co.il/TASEEng/Homepage.htm
