Thesis Announcement

UNIVERSITY OF MISKOLC FACULTY OF ECONOMICS

THESIS ANNOUNCEMENT

FULL NAME: Heena Kapoor

NEPTUN CODE: YL70T

TYPE OF PROGRAMME: MSc

NAME OF PROGRAMME: Master of Business Administration (English)

NAME OF SPECIALISATION: Economics

RESPONSIBLE DEPARTMENT OR INSTITUTE: Institute of Management Science

TITLE OF THESIS: Comparative Analysis On Budapest Stock Exchange And Bombay Stock Exchange

ASSIGNMENT: − Introducing the economy of India and Hungary − Introducing the Stock exchanges of both countries Analysis of the financial ratio of the company − Analyzing the Value at Risk model using company stock prices

BASE ORGANISATION : Richter Gedeon Nyrt, Sun Pharma, OTP Bank, SBI, MOL and ONGC

INTERNAL CONSULTANT : Dr Zsombori Zsolt, Lecturer

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UNIVERSITY OF MISKOLC FACULTY OF ECONOMICS

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FULL NAME: HEENA KAPOOR NEPTUN CODE: YL970T TITLE OF THESIS: Comparative Analysis On Budapest Stock Exchange And Bombay Stock Exchange BASE ORGANISATION : Richter Gedeon Nyrt, Sun Pharma, OTP Bank, SBI, MOL and ONGC INTERNAL CONSULTANT : Dr Zsombori Zsolt, Assistant Professor EXTERNAL CONSULTANT (name, position):

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FULL NAME: HEENA KAPOOR

NEPTUN CODE: YL970T

TITLE OF THESIS: Comparative Analysis On Budapest Stock Exchange And Bombay Stock Exchange

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Student’s name: HEENA KAPOOR

Neptun code: YL970T

Faculty and programme: Faculty of Economics, Master of business administration

Year of thesis submission: 2019 Title of the thesis: Comparative analysis of Budapest stock exchange and Bombay stock exchange I request that my thesis be treated confidentially (requires an application for confidential treatment). (Please underline as applicable.) Yes No I allow the university library to publish my thesis as full text on the Internet. (Please underline as applicable.) Yes No In full awareness of my liability I declare that the electronic version of my thesis is identical to the printed thesis I submitted.

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UNIVERSITY OF MISKOLC FACULTY OF ECONOMICS

Comparative Analysis of Budapest Stock Exchange and Bombay Stock Exchange

Heena Kapoor 2019

Abstract

Stock market is a vital part of every economy. Rise and fall in economy are reflected by the stock market. Bullish stock market is the sign of developing industrial sector and growing economy of the country. This thesis involves the analysis of Budapest stock exchange and Bombay stock exchange, and in order to further understand the associated risk, a comparison was made between them using two statistical techniques. The Oil, Banking and Pharmaceutical industries forms the backbone of nation’s economy. Thus, the analysis was conducted on the prominent companies in Oil, Banking and Pharmaceutical industries of both the stock exchanges. The VaR analysis was performed on the portfolio to analyse the risk associated with market. The evaluation of companies operating, and financial performance was conducted using ratio analysis technique.

Financial results have become an important indicator for business valuation. The Average Price Return have the significant influence on the Ratios represents the aggregate value of a company or stock. The purpose of this study is to analyse the relationship between the Financial Ratio and the Average Price Return of the chosen companies from the two Stock Exchanges. The price of company’s stock is a significant factor and should be kept in mind while making investment as it shows the value of a company. We took 3 companies from 3 important sector of economy- Banking, Pharmaceuticals and Oil.

Table of Contents

1. Introduction ...... 1 2. Objectives ...... 5 3. Limitations of the study ...... 6 4. Hypotheses ...... 7 5. Methodology ...... 8 1. Value at Risk ...... 8 2. Benchmark model ...... 8 3. Excel ...... 8 6. Literature Review ...... 9 7. Theoretical Background ...... 12 7.1 Hungarian Economy ...... 12 7.2 Indian Economy ...... 14 7.3 Stock Exchange ...... 16 7.3.1 Budapest Stock Exchange ...... 17 7.3.2 Bombay Stock Exchange ...... 20 7.3.3 Listed Domestic Companies ...... 22 7.4 MOL ...... 23 7.5 Oil and Natural Gas Corporation Ltd ...... 24 7.6 OTP BANK ...... 25 7.7 State Bank of India ...... 26 7.8 Richter Gedeon Nyrt ...... 27 7.9 Sun Pharmaceuticals ...... 28 7.10 Investment Risk Management ...... 29 7.11 VAR MODEL ...... 30 7.12 Ratio ...... 33 7.13 T-Test in Ms-Excel...... 36 8 Quantitative Analysis ...... 37 8.1.1 OTP ...... 37 Ratio Analysis ...... 37 T-TEST ...... 37 8.1.2 Richter Gedeon Nyrt ...... 39 RATIO ANALYSIS ...... 39 T-TEST ...... 39

8.1.3 MOL ...... 41 RATIO ANALYSIS ...... 41 T-TEST ...... 41 8.1.4 SBI ...... 43 RATIO ANALYSIS ...... 43 T-TEST ...... 43 8.1.5 Sun Pharma ...... 45 RATIO ANALYSIS ...... 45 T-TEST ...... 45 8.1.6 ONGC ...... 47 RATIO ANALYSIS ...... 47 T-TEST ...... 47 8.2.1 HUNGARIAN COMPANIES’ PORTFOLIO ...... 49 8.2.2 Indian Companies’ Portfolio ...... 51 8.2.3 BUX VAR ...... 53 8.2.4 SENSEX VAR ...... 55 9. Conclusion ...... 57 References ...... 59 Appendix ...... 62

List of Figures

Figure 1. Listed domestic companies in India ...... 22 Figure 2. Listed domestic companies in Hungary ...... 22 Figure 3. Probability density versus portfolio value with 90% confidence in portfolio ..... 30 Figure 4. Histogram Hungarians companies Portfolio ...... 50 Figure 5. Histogram of Indian Companies Portfolio ...... 52 Figure 6. Histogram of BUX ...... 54 Figure 7. Histogram of Sensex ...... 56

List of Tables

Table 1. Selected companies from each industry of Hungary and India ...... 3 Table 2. The list of requirements for Initial public Issue ...... 17 Table 3. Payment of listing fee ...... 21 Table 4. OTP Ratio analysis ...... 37 Table 5. OTP T-Test ...... 37 Table 6. Richter Gedeon Nyrt Ratio analysis ...... 39 Table 7. Richter Gedeon Nyrt T-Test ...... 39 Table 8. MOL Ratio analysis ...... 41 Table 9. MOL T-Test ...... 41 Table 10. SBI Ratio analysis ...... 43 Table 11. SBI T-Test ...... 43 Table 12. Sun Pharma Ratio analysis ...... 45 Table 13. Sun Pharma T-Test ...... 45 Table 14. ONGC Ratio analysis ...... 47 Table 15. ONGC T-Test ...... 47 Table 16. Frequency of Hungarians companies Portfolio ...... 49 Table 17. Frequency of Indian companies Portfolio ...... 51 Table 18. Frequency of BUX ...... 53 Table 19. Frequency of Sensex ...... 55

1. Introduction Stock Market is a key indicator of the financial strength of the country’s economy. It is a marketplace where different types of securities are being freely traded between the traders or investors. Stock Exchange provides a great platform for purchasing and selling securities, debt and derivatives with easy liquidity option. Nowadays, the stock market has become very intense and is increasingly gaining importance in the economic growth of a country.

It is not only important for the country’s economic growth but also the main sources of finance for all the companies and allows them to publicly trade their shares or raise capital or additional capital in case of expansion by selling shares of the company in an open market. For some companies (especially the large companies) it is a more flexible way to raise capital than borrowing from Banks. Stock Market is a reflector of the economic condition of a country’s economy, if an economy is growing then the production of outputs are increasing which increase the sale and profit of the companies which in turn increases the tax paid by them to the government and also shoots up the GDP percentage. Higher profit will also attract new investors in the market as investors are getting a high interest in the shares. But it can also work in reversing way also, loss or less profit may affect the share prices and can cause create disturbance in the stock market which can create disturbance in the economic condition of the company. It helps in mobilizing the resources in the economy.

Companies have to get listed on the stock market and sell their shares. This enables them to gain finance to invest. In a free-market economy, stock market plays an important role because it provides an easy access to the capital in exchange of giving up a certain percentage of ownership. It acts as a bridge between the person who needs money and have a new idea (Company) and those who have surplus money and want to invest and earn interest (investors). It provides a platform for investors to grow their small amount of money into large, without taking the risk of starting a business by themselves or leaving their career to earn some extra money. Stock market gives a good interest on investment if we compare with the returns given by the banks but the investment involves a certain level of risk associated with it. Most of the countries have more than one major stock exchanges. Example New York Stock Exchange (NYSE), National Association of Securities Dealers Automated Quotations NASDAQ of America. National Stock 1

Exchange of India and Bombay stock exchange of India. The stock market is an example of perfect competition market as it provides all the information is readily available to the investor and prospective investor as most countries promote transparency when it comes to the stock market as it is the one the main component for an economy the stock exchange of countries is free from control of the government. But have to work according to rules and regulations of that countries. Each country has its own set of laws that help in smooth functioning of the stock exchange and provide protection to the investors. Due to an increase e of a number of scams in the stock market, it is important to have some regulatory bodies in order to stabilize the confidence of the investors. In order to avoid scams and attract investors Government of each country came up with their rules and law which help in governing the stock market easily. These laws are made to have a more transparent view of stock exchange.

With the globalization, accessing the international market became easier. Now not only local investors have their investment in the market but also the international traders are involved. International traders are mostly interested in investing the developing Economy as it provides a great return on their investments. Globalization affected all spheres- stock market was also one among them. It gave rise to the integration of financial market.

Globalization had made foreign investment in stock market much easier. Because of transparency in this business, the investment in stocks are not limited to the local market, many investors are investing in different countries stock by Global depository receipt etc.

In the market there are numerous of company listed on exchanges. In order to determine the size of the company analysing the share prices are not enough, Market Capitalization is the one of the common techniques to determine the size. In recent years Market capitalization have become an important indicator in order to evaluate the companies in the stock market. Market capitalization is the total dollar value of all outstanding shares of a company. It is calculated by multiplying the current share price by the number of outstanding shares. Outstanding Shares are all the shares which are currently owned by stockholders, company officials, and investors in the public domain. Usually analyst use the figure to determine the size and the position of the company. Since it is calculated with the help of share price which is not stable so, the market capitalization can also fluctuate on daily basis.

In this thesis main the goal is to analyse and compare the Stock Exchanges. Being an Indian, pursuing MBA in Hungary have equipped me with deeper knowledge of financial market of both the countries. This had motivated me to study and compare the Stock Exchanges of both the countries, as the Stock Market is a reflector of the economic condition of a country’s economy. In this thesis, the Bombay Stock Exchange (India), which is Asia’s oldest stock exchange and the Budapest Stock Exchange (Hungary) were chosen. The objective of this analysis is to study the three main sectors of two different countries from two different continents i.e., India (Asia) and Hungary (Europe). On the first look of both the stock exchange, the hypothesis (H1) of Bombay Stock Exchange to be less risky in terms of investment than Budapest Stock Exchange (Hungary) can be formed, which is supported by high economic growth and large market size of the former. However, we need a deeper level investigation of the major industries of each country for testing our hypothesis. This was the motivation for conducting the present study.

Investment in stock market involves risk, lately lots of method have been developed to measure risk. Value at Risk is one of the effective and efficient method to risk measurement. In this thesis I will use VAR analysis to measure the risk involve in investing in both the stock exchanges.

In this thesis, while comparing the financial statement of the companies, the financial year for Hungarian companies would be 1 January -31 December and for Indian companies 1 April- 31 March as both the countries have different rules for a financial year.

Table 1. Selected companies from each industry of Hungary and India

Sectors Hungary India

Pharmaceuticals Richter Gedeon Nyrt Sun Pharmaceutical

Banking OTP State Bank of India

Oil MOL ONGC (Source: Self-constructed)

Pharmaceuticals, Banking and Oil Company are the main sectors of both the countries. The choose companies are one of the leading players in the economy and have a good financial position which is been proved by bench mark analysis.

In this thesis I will try to formulate the relationship between chosen firm’s financial performance, market price and risk involved in investing. Due to globalization accessing to worldwide market became easy, now investors have lots of option to invest not in local market but also in different countries. To make correct decision in-depth analysis is important. In this thesis I took two developing countries situated in different continents (Asia and Europe). I will analyse the historical price movement of the selected companies and stock exchange with their financial performance.

2. Objectives • To have a comparative analysis of both stock exchanges • To study the fluctuations in share prices of selected companies • Effect of the stock exchange on the economy of both Countries. • Analysis of financial position of the company using ratio analysis and the risk involves the stocks of taken companies with the help of a model. • To understand the correlation between the stock prices and financial performances. • To find out investing in which country is more risker and profitable by using historical data and analysing it.

3. Limitations of the study • The topic has a broad nature which is a limitation. • The study is based only on secondary data. • Time is a major constraint for a detailed study. • Two countries follow different financial years.

4. Hypotheses ➢ H1: There is significant relationship between taken companies financial ratios and their stock market price. ➢ H2: Risk involved investing by portfolio of taken Indian companies of Bombay Stock Exchange is higher than investing by portfolio of taken Hungarian companies of Budapest Stock Exchange. ➢ H3: Risk involved in investing in investing in SENSEX (Index of Bombay stock exchange) is higher than investing in BUX (Index of Budapest Stock Exchange).

5. Methodology

To have an in-depth study of both the countries, I have chosen 3 companies from each country. In this thesis two methods are being used:

1. Value at Risk - As share market is uncertain and VAR model is one of the models which help in calculating the risk. In this thesis, I have compared the risk involved in the shares of the chosen company. 2. Benchmark model - Financial position of the company has a strong influence on the stock prices of the company. In order to have some pictures of the company’s financial statements in this thesis I have done ratio analysis and compare the ratios with the benchmark ratios. 3. Excel - (Software) Data is analyse using statistical formulas and processed to get the results.

6. Literature Review The stock exchange has become a major source of earning and it is a market which is difficult to predict. Many studies are done on the stock market. With the globalization of capital markets, stock exchanges around the world have faced their most challenging era since 2005. While the traditional role of the stock exchange should evolve by enforcing competitive advantage, as the heart of modern capital markets, stock exchanges give rise to both capital demand outflows and capital supply inflows, and both must be taken into consideration. Since 2005, the competition among the world's stock exchanges has rapidly increased. To secure their competitive positions, the traditional role of the stock exchange needs to change quickly through the enforcement of competitive advantage. (Lo, 2013)

According to a researcher, there is a link between economic variables with growth are extremely significant. These indicators are either quantitative or qualitative. The active- features are stock market size in terms of market capitalisation ratio, having positive significance correlated with real per capita GDP, market liquidity and activity in terms of value traded, turnover, and further having a positive sign with growth, namely that market volatility has negatively and insignificantly correlated with real per capita GDP growth. (Masoud, 2003) Stock market volatility modelling and estimation have established certain issues of great interest not only for investors, financial practitioners and academics, especially in terms of modern finance perspectives. Moreover, one of the main aims of the investment process is to reduce the high exposure to risk considering the fact that international portfolio diversification provides superior risk-adjusted returns. (Ramona Birăua, 2015).

The study of (Prasad, 2015) focused on the effect of profitability and market value ratios on market. In this study 23 listed infrastructural companies of CNX infrastructure Index has been taken for analysis. The main finding is market capitalization and firm performance that the influence of various variables such as return on equity (ROE), P/E ratio, return on asset (ROA), profitability etc. over market capitalization has been undertaking independently.

This study of (Dr. Mohammad Abdelkarim Yousef Almumani, April 2018) aims to investigate the effect of profitability ratios and market value ratios on the market capitalization for Jordanian listed commercial banks. In this study data of 2010-2016 was used from the Amman stock exchange archives. Thus, the study draws out a relationship

9 of market capitalization with five other variables namely ROE, ROA, EPS, PER and DPR. The finding of study is that return on equity and dividend pay-out ratio are the major determinants of market capitalization of the listed commercial banks in Jordan.

The study of (MacKenzie, 2015)focus on the risk indices are used to communicate risks to the public, understand how risk is changing over time, compare among different risks, and support decision making. This paper focus on the importance of describing risk with a probability distribution, developing a numerical risk measure that summarizes the probability distribution, and finally translating the risk measure to an index.

The study of (Li*, 2015) focus on VaR model is mainly suitable for measuring market risk, and not a measure of credit risk. It is because of existing financial risk measure is not perfect, it is worth our financial institutions to learn it and study it. The study emphasis on studied theories, methods and technical standards of China's financial risk management, in order to enhance the competitiveness level of our financial institutions.

The study (Vinay Kaura) focused on historical prices to create future scenarios one can determine the “Value-At Risk” of a specified portfolio using back testing, this report demonstrates how the developed model would have, hypothetically, been able to make profits of up to 40% over the course of the past year while the FTSE 100 benchmark rose by only 27%.

According to Mussalam earnings yield ratio, and dividend yield ratio enhance market stock returns while other ratios do not effect on market stock returns in Qatar. (MUSALLAM, 2018)

In study market-to-book ratio, dividend yield and firm size have significant positive relationship with stock returns, while price-to-sales ratio and earnings per share are insignificant and negative relationship with the stock returns. (LAI Ping-fu (Brian), 2016)

According the study there are relationships between the financial ratios which is valuable information to the stock investors. (Meri, Kamışlı', & Temizel, November 2017)

The article emphasizes that the market fluctuations relations to the prices, due to price movements it is difficult to observe the pattern, it is observed that the financial position and performance of the firms are in correlation with present market prices. (GAUTAMI & KALYAN, 2018)

The researcher did an analysis on a sample of 46 firms to show the value relevance of the financial ratios and their usefulness in security valuation in Egypt. They used three models to test for linear and non-linear relationships and Concluded that ROE seems to play a significant role in investment decisions in the Egyptian market (Omran & Ragab, 2004)

7. Theoretical Background 7.1 Hungarian Economy Hungary is one of the Central and Eastern European countries. The total land area is 90,530 Km2 with approx. 10 million population. Despite being in European Union Hungarian government have retained its own Currency which Hungarian forint (HUF). Average market value of 1 Euro=310 ft Hungary became member of European Union in since 1 May 2004. Hungary is the democratic country. From 2016 Hungary becomes an attractive country for tourism and employment. Hungarian Government decided to adopt Privatization policy in 1990 because of Hungarian foreign debt got so much increased that the government decide to sell some part of state property instead of being in debt. During the early nineties, century lot of government decided to take this step. External Debt in Hungary increased to 105322.07 EUR Million in the second quarter of 2018 from 103657.39 EUR Million in the first quarter of 2018 (Economics .T, 2019) In 20th century The Hungarian economy have been open to the world for trade. Hungarian economy went through a deep transformational and structural crisis during the transition, and it resulted in a modern national economy, ready for the Integration into the European Union. This came together with mainly necessary sacrifices that the society, the majority of the people had to suffer, but in the same time these sacrifices created the long-run conditions for catching up. Among others the catching up. The volume of gross domestic product was 4.2% higher in Hungary in the 1st quarter of 2017 than in the corresponding period of the previous year. The primary contributors to the growth were market-based services and industry. (ksh, 2019) After privatization lot of new companies came into the market which gave a boost to the economy and increases competition. In 1994 government decided to enter join European Union. European Union main motto is to ensure free movement of people and trade. It helps the Hungarian market to import goods and technology from other EU member countries easily, moreover, the union also provide economic support to Hungarian In 2004 Hungary became the tenth country to join the union. Hungary was one of those countries which was affected by the 2008 global crises -6.4% was the recession which affected the economy and it took a lot of time to recover from this loss.

The monetary policy decision of the country is taken by Hungarian National Bank (Hungarian: Magyar Nemzeti Bank, MNB) which is the central bank in Hungary whose prime objective is price stability. “According to IMF Gross domestic product, current prices of Hungary in 2017 was USD 125.297 Billion And for 2018 USD130.376 Billions. According to recent data, Hungary’s real GDP growth in the first quarter was 4.2% higher than the previous year GDP. The main driver of this growth is due to service and industrial contribution to the economy. This year the economic performance was also improved by 3.8% if we compare data with the previous year. The value added of agriculture decreased by 6.3%.” (ksh, 2019)

7.2 Indian Economy

Indian economy is the developing mixed Economy. India is situated in Asia Continent. It is the world's sixth- largest economy by nominal GDP and the third-largest by purchasing power parity (PPP) Seven largest Country by area. The Indian currency is Indian Rupee (INR) ₹. 1 Euro is equal 80 INR. According to IMF India is one of the fastest growing countries in the world.

The main sectors of Indian economy are agriculture, handicrafts, industries, and services. With the technological and economic growth service sector became the important part of the economy especially the Information and technology. India is considered as the main service provider for information and technology many companies have outsourced their IT services from India and Banking and Financial services have 37% of GDP share. Services are the main source of economic growth in India today, though two-thirds of Indian people earn their living directly or indirectly through agriculture. Industry accounts for 26% of GDP and Agriculture accounted for 23% of GDP (BENCHMARKING, 2017)

India was always an agriculturally based country because of its climate and land fertility. India exported $256B, making it the 18th largest exporter in the world. Major exported good are Crude oil, Gold, Jute. India imported $344B, making it the 14th largest importer in the world which is increased by 33.9% since 2009. (OEC, 2017) In 1991 Indian government decided to adopt Liberalization and privatization policy. As India was dealing a huge financial crisis mainly due to Balance of payment deficit in order to cover deficit government applied for a loan from IMF who asked India to adopt liberalization policy. Before 1991 for most of the business acquired, the license was mandatory. But after 1991 licensing policy was removed from most of the business. This economic change proved beneficial for the economy as it helps in economic growth and technological growth of the country.

India is a democratic country where the government have very less influence on the market. Reserve Bank of India (RBI) is the central bank who is responsible for making monetary policy. RBI is free from any governmental interference. According to UNCTAD’s World Investment Report 2015, India ranks third among most prospective host economy for 2015- 17 (after China and the US) in the world. Foreign direct investment (FDI) is one of the major sources of non-debt financial resource for the Indian economy. Foreign companies are attracted to invest because of relatively lower wages and availability of human resources (both skilled and unskilled), tax exemptions, for the new companies and investment etc. FDI 14 not only increases capital flow in the country but also help in technological growth and give rise to the level of employment in the country. In 2017 India has 7.2% GDP rate According to IMF the GDP will rise further to 7.8% in 2019.

In 2016, the Indian government decided to demonetize its 500- and 1000- rupee notes, which is the two biggest currency notes in India. The government replaced the 500rupee notes with a new note and removed 1000 rupee note from the economy and issued a new 2000rupee note. This change was made in overnight and time period of exchanging the currency was very short. The government took this step-in order to remove fake currency and black money (untaxed amount) in circulation. This was an unexpected move by the government which impacted the stock market as a number of investors left the market and some left due to lack of funds and other withdraw as they were expecting fall in the market. It took some time for the exchange to come back to normal place. The government tax collection was also increased to the demonetization.

In 2017 Indian economy faced another major change in the form of new tax reform the government introduces new indirect tax i.e., Goods and service tax and replaced some of its old indirect tax which also created some disturbance in the economic system of the country. This increases the government revenue from taxation. The major reform done by the new government had increased the personal tax collection to 2.3% of GDP

7.3 Stock Exchange

Stock exchanges are indispensable for the smooth and orderly functioning of the corporate sector in a free market economy. The main function of the stock market is to provide a ready market for sale and purchase of securities. The presence of stock exchange market gives assurance to investors that their investment can be converted into cash whenever they want. The investors can invest in long-term investment projects without any hesitation, as because of stock exchange they can convert a long-term investment into short term and medium term. The stock market offers attractive opportunities for investment in various securities. These attractive opportunities encourage people to save more and invest in securities of the corporate sector rather than investing in unproductive assets such as gold, silver

Stock Exchange requires companies to follow some minimum standards operational or capital structure for listing. It helps to maintain the quality of market and efficiency of the market. Listing means an admission of securities to dealings on a recognized stock exchange.

7.3.1 Budapest Stock Exchange

Budapest stock exchange is the successor of Hungarian stock exchange which was founded in Pest in 1864.The Hungarian stock exchange was one of the leading exchanges in Europe, but it was disbanded in 1948. 1990 Budapest stock exchange was created by the government is the 2nd largest stock exchange in Central and Eastern Europe by market capitalization and liquidity. BUX, BUMIX, CETOP are the indices of Budapest stock exchange. In 2015 National Bank of Hungary (MNB) bought shares of the stock exchange and become a major qualified shareholder in exchange.

The exchange formulates a policy in order to compete with other exchange the new stock exchange development strategy is made the special focus of this strategy is small and medium enterprises (SMEs). This strategy will provide a trading platform to SMEs. A foreign investor has 70-80% of the BSE’s equity capitalization and its turnover.

BUX is the major index in the stock exchange. It is comprising of 25 major trading companies. Prices are taken from the electronic Xetra trading system. BSE was one of the first in the world who started to use free-float capitalization weightings instead of the traditional market capitalization weightings in October 1999 (BET, 2019)

Table 2. The list of requirements for Initial public Issue

Equities Prime Equities Standard Equities T Market Market Market

Series of At least 5 billion No requirements No requirements shares to be forints at market listed value

Free float - at least 25 percent of No requirements No requirements the series to be listed is free float; or at market prices, shares to the value of at least two billion forints are free float; or

the series of shares is, at the time of listing, in the possession of at least 500 owners.

Only common shares Equity class may be admitted No requirements No requirements No obligation to No obligation to Corporate Mandatory to disclose at listing disclose at listing Governance disclose at listing (only after listing (only after listing Report (also afterwards with each annual with each annual annually – together with report) report) the annual report)

Business years Three full, completed, No requirements No requirements audited years

The method of Public transaction Public No public listing transaction transaction (one-year grace requirement period) (technical listing) Sources: (BET, 2019)

The listing fee payable Issuers are not obliged to pay a fee for listing Equities and Other Securities Issued. The Amount of the annual listing maintenance fee is based on https://www.bse.hu/Issuers/Listing-on-the-BSE/Terms-of-Listing capitalization.

The Budapest Stock Exchange's Market Capitalization is $23.2 Billion, Market Capitalization to GDP ratio, which when compared to the historic ratio is an indicator that a market is over or undervalued, is 17.77% (BET, 2019)

7.3.2 Bombay Stock Exchange

Bombay stock exchange and National stock exchange are two main stock exchanges of India where the main trading takes place. National stock exchange was coming into existence in 1994 whereas Bombay stock exchange was established in 1875 (the oldest stock exchange in Asia). At that time 22 stockbrokers were there who use to gather under banyan trees in front of Mumbai's Town Hall to do trading. The Indian stock exchange is the world 3rd largest stock exchange on investor basis having approx. 20million investors. In 1986, the S&P BSE SENSEX index was introduced which helped the Exchange to measure its performance. The exchange decides to opt electronic trade system in 1995 to increase the efficiency and transparency in the trading. At the beginning of 20th century, this index was opened to its derivatives market, trading S&P BSE SENSEX futures contracts and developed S&P BSE SENSEX options and equity derivatives which helps the exchange to expand its trading platform. (Bombay Stock Exchange, 2019). Currently, S&P BSE SENSEX index is widely traded in the market and is traded on EUREX (European derivative market)

BSE SENSEX is the main index of the exchange consist of 30 companies. The Bombay Stock Exchange's Market Capitalization is $1.66 Trillion. Market Capitalization to GDP ratio, which when compared to the historic ratio is an indicator that a market is over or undervalued, is 99.62% (Bombay Stock Exchange, 2019).

➢ The minimum post-issue paid-up capital of the applicant company be shall be Rs. 10 crores for IPOs & Rs.3 crore for FPOs; and ➢ The minimum market capitalization of the Company shall be Rs. 25 crores (market capitalization shall be calculated by multiplying the post-issue paid-up number of equity shares with the issue price). ➢ Allotment of Securities -As per the Listing Agreement, a company is required to complete the allotment of securities offered to the public within 30 days of the date of closure of the subscription list and approach the Designated Stock Exchange for approval of the basis of allotment. ➢ Operating requirement-3 years ➢ Minimum deposit

➢ Companies making public/rights issues are required to deposit 1% of the issue amount with the Designated Stock Exchange before the issue opens

Table 3. Payment of listing fee Initial listing fees Rs. 20,000/-

Annual listing fees

(i) Upto Rs. 5 Crs. Rs. 15,000/-

Rs.5 Crs. To (ii) Rs. 25,000/- Rs.10 Crs. Rs.10 Crs. To (iii) Rs. 40,000/- Rs.20 Crs. Rs.20 Crs. To (iv) Rs. 60,000/- Rs.30 Crs. Rs.30 Crs. To Rs. 70,000/- plus Rs. 2,500/- for every increase (v) of Rs. 5 crs Rs.100 Crs. Or part thereof above Rs. 30 crs. Rs.100 Crs. to Rs. 125,000/- plus Rs. 2,500/- for every (vi) increase of Rs. 5 crs Rs.500 Crs. Or part thereof above Rs. 100 crs. Rs.500 Crs. to Rs. 375,000/- plus Rs. 2,500/- for every (vii) increase of Rs. 5 crs Rs.1000 Crs. Or part thereof above Rs. 500 crs. Above Rs. Rs. 625,000/- plus Rs. 2,750/- for every (vi) 1000 increase of Rs. 5 crs or part thereof above Rs. Crs. 1000 crs.

Sources: (Bombay Stock Exchange, 2019)

7.3.3 Listed Domestic Companies

Listed domestic companies in India

Figure 1. Listed domestic companies in India

Listed domestic companies in India 7000

6000

5000

4000

3000

2000

1000

Source: (worldbank, 2019)

Listed domestic companies in Hungary

Figure 2. Listed domestic companies in Hungary

Listed domestic companies in Hungary 70 58 60 55 50 52 51 50 48 47 48 48 50 45 44 42 43 41 39 40 41 40

Source: (worldbank, 2019)

7.4 MOL

MOL group was founded in 1991 as MOL Plc. In 1995 they opened first Romanian MOL filling Nagyszalonta. Since its foundation MOL group has acquired 100% stakes in BaiTex, Surgut-7 exploration blocks in Russia, Margala and Margala-North exploration blocks in Pakistan, Akri-Bijeel exploration block in the Kurdistan Region of Iraq, Tifon in Croatia, Matjushkinskaya Vertikal LLC in Russia, IES oil company in Italy, TUS Oil Holding in Slovenia, Pap Oil and Bohemia Realty Companies in the Czech Republic, TVK Plc. (subsequently renamed to "MOL Petrochemicals")

MOL is a Hungarian multinational oil and gas company headquartered in Budapest, Hungary. MOL is the second most valuable company in Central and Eastern Europe. MOL placed 402 on the Fortune Global 500 list of the world's largest companies in 2013. MOL's revenue was equal to one-fifth of Hungary's GDP at the time. As of November 2015, the largest shareholder is Hungarian state with 24.74% ahead of ČEZ Group with 7.35%, Oman Oil Budapest with 7.00% and ahead of OTP Bank with 5.84%. More than 50% of shares are free floated.

MOL is vertically integrated and is active in every area of the oil and gas industry, including exploration and production, refining, distribution and marketing, petrochemicals, power generation and trading. It has minor renewable energy activities in the form of biofuels. It has operations in over 40 countries worldwide, it has nearly 2,000 service stations in 11 countries (mainly in Central and Eastern Europe) under seven brands, and it is a market leader in Hungary, Slovakia, and Croatia. MOL's downstream operations manufacture and sell products such as fuels, lubricants, additives and petrochemicals. The company's most significant areas of operations are Central and Eastern Europe, Southern Europe, North Sea, Middle East and Russia. It has 4 Refineries with 417,000 Refineries throughput per day, 2 Petrochemical Facilities with Petrochemical production of 2080 KTPA and 459M BARRELS OF OIL EQUIVALENT of SPE 2P. The market capitalization is $7.3 Billion in May 2017 (molgroup, 2019).

7.5 Oil and Natural Gas Corporation Ltd

Oil and Natural Gas Corporation Ltd. (ONGC) is an India oil company a Navaratna public sector enterprise engaged in the exploration of hydrocarbons is one of the leading companies with significant contribution in its industrial and economic growth over the years ONGC has been fairly successful in building up a vibrant oil industry in the country. The Oil and Natural directorate were formed in the year 1952 as part of Department of Geological Survey of India (GSI) to undertake the task of exploration of crude oil in the country. The directorate was transformed into commission in the year 1956 thenceforth it was known as Oil and Natural Gas Commission till recently in the year 1993 when it converted into a public limited company and is known as Oil and Natural Gas Corporation Limited. The various products of ONGC are Crude Oil, NGL (Natural Gasoline), LPG (Liquefied Petroleum Gas), Ethane- Propane, Natural Gas.

Maharatna ONGC is the largest producer of crude oil and natural gas in India, contributing around 70 percent of Indian domestic production.

It is one of the most valued public enterprises in India, and one of the highest profit-making and dividend-paying. ONGC has a unique distinction of being a company with in-house service capabilities in all areas of Exploration and Production of oil & gas and related oilfield services. Winner of the Best Employer award, a dedicated team of over 33,927 professionals’ toils round the clock in challenging locations.

Its wholly-owned subsidiary ONGC Videsh Limited (OVL) is the biggest Indian multinational in the energy space, participating in 36 oil and gas properties in 17 countries. ONGC subsidiary Mangalore Refinery and Petrochemicals Limited.

ONGC is one of the most valuable corporations trading on Indian stock exchanges. With a current approximate share price of around INR 250 per share and 8555.60 million equity share base, the market valuation of ONGC is INR 2,138,900 million. Its market capitalization is 231,960.73 (Oil and Natural Gas Corporation Limited, 2019).

7.6 OTP BANK

OTP Bank Group is one of the largest independent financial services providers in Central and Eastern Europe with a full range of banking services for private individuals and corporate clients. OTP Group comprises large subsidiaries, granting services in the field of insurance, real estate, factoring, leasing and asset management, investment and pension funds. The bank is serving clients in 9 countries, namely Hungary, Slovakia, Bulgaria, Serbia, Romania, Croatia, Ukraine, Montenegro and Russia.

OTP Group provides its universal financial services through several subsidiaries. In Hungary, traditional banking operations are performed by the Bank while specialized services, including car leasing, investment funds are developed and offered by the Bank's subsidiaries. Insurance claims of OTP Group clients are supplied by sales of insurance products with strategic collaboration with French insurance company, Groupama, after its OTP Garancia aqutision. The predecessor of OTP Bank called the National Savings Bank (OTP Bank) was established in 1949 as a nationwide, state-owned, banking entity providing retail deposits and loans. In the ensuing years, its activities and the scope of its authority gradually widened.

Nowadays OTP Groups' more than 38,000 employees are serving 13 million clients in over 1,500 branches and through electronic channels on all the markets of the bank. OTP is still the largest commercial bank in Hungary with over 25% market share. OTP Group started its activity in 1949 when OTP Bank was founded as state savings and commercial bank. OTP stands for Országos Takarék Pénztár (National Savings Bank) which indicates the original purpose of establishment of the bank. The bank went public in 1995, and the share of the state in the bank capital decreased to one preferential gold share, which also eliminated shortly thereafter. Currently, most of the banks' shares are owned by private and institutional investors.OTP has a high free float shareholder structure; the free float ratio reaches the 68.61%. The rest is held by one of the Forbes billionaire Megdet Rahimkulov in 8.88%, Hungarian MOL Group in 8.57%, French Groupama in 8.30% and American Lazard in 5.64%. The market cap of otp as on May 2017 was $7.9 Billion (OTP, 2019).

7.7 State Bank of India

State Bank of India (SBI) is an Indian multinational, public sector banking and financial services company. It is a government-owned corporation with its headquarters in Mumbai, Maharashtra. State Bank of India (SBI), with a 200-year history, is the largest commercial bank in India in terms of assets, deposits, profits, branches, customers and employees. The Government of India is the single largest shareholder of this Fortune 500 entity with 61.58% ownership. SBI is ranked 60th in the list of Top 1000 Banks in the world by "The Banker" in July 2012.

The SBI group consists of SBI and five associate banks. The group has an extensive network, with over 20000 plus branches in India and another 173 offices in 34 countries across the world.

As of 31st March 2012, the group had assets worth USD 359 billion, deposits of USD 278 billion and capital & reserves in excess of USD 20.88 billion. The group commands over 22% share of the domestic Indian banking market. SBI’s non- banking subsidiaries/joint ventures are market leaders in their respective areas and provide wide-ranging services, which include life insurance, merchant banking, mutual funds, credit cards, factoring services, security trading and primary dealership, making the SBI Group a truly large financial supermarket and India’s financial icon. SBI has arrangements with over 1500 various international/local banks to exchange financial messages through SWIFT in all business centres of the world to facilitate trade related banking business, reinforced by dedicated and highly skilled teams of professionals. (Linda, 2019)

In April market cap of SBI Rs 2,35,307.51 crore. On April 1, 2017, the State Bank of India, India's largest bank, merged with five of its associate banks (State Bank of Bikaner & Jaipur, State Bank of Hyderabad, State Bank of Mysore, State Bank of Patiala and State Bank of Travancore), and with the Bhartiya Mahila Bank. This merger was the first largest consolidation in the Indian banking industry.

7.8 Richter Gedeon Nyrt

Richter Group is active in two major business segments, primarily Pharmaceuticals comprising the research and development, manufacturing, sales and marketing of pharmaceutical products, and it is also engaged in the Wholesale and Retail of these products. In addition, there is a third group (’Other’) of companies comprising those members of the Group that provide auxiliary services to the former segments. Research, development, manufacturing and marketing of pharmaceutical products are the core activities of Richter and in this endeavour, the Group is supported by a number of subsidiaries, joint ventures and associated companies. Manufacturing subsidiaries of the Group which operate in traditional markets together with a broad network of trading affiliates that ensure a strong market presence have together created the foundation for regional leadership and a global presence in the area of Women’s Healthcare (Richter, 2019).

Richter Gedeon Nyrt is a Hungarian company registered under Budapest stock exchange. The total number of shares in issue at 186,374,860 as of 31 December 2016 which is as same as in last year. The Company is following corporate governance Corporate Governance according to guidelines set by the Budapest Stock Exchange and the directives of the capital market.

Gedeon Richter’s key principles of Corporate Governance are to create and maintain satisfactory shareholders so as to enhance shareholder value, to differentiate the roles and responsibilities of the Board of Directors, the Executive Board and the Supervisory Board, and to operate the Group’s business in compliance with legal and regulatory requirements and to maintain the highest ethical standards (Richter, 2019).

7.9 Sun Pharmaceuticals

Sun Pharmaceuticals was established by Mr Dilip Shanghvi in 1983 in Vapi, India with five products to treat psychiatry ailments. Today, it is the largest chronic prescription company in India and a market leader in psychiatry, neurology, cardiology, orthopedics, ophthalmology, gastroenterology and nephrology. Sun Pharma was listed on the stock exchange in 1994 in an issue oversubscribed 55 times. The founding family continues to hold a majority stake in the company. Today Sun Pharma is the second largest and the most profitable pharmaceutical company in India, as well as the largest pharmaceutical company by market capitalization on the Indian exchanges. They have over 40 (API & finished dose) state-of-the-art manufacturing sites spanning 6 continents. These manufacturing units are located in India, the US, Brazil, Canada, Egypt, Hungary, Israel, Bangladesh, Mexico, Romania, Ireland, Morocco, Nigeria, South Africa and Malaysia. These units provide best- in-class products to patients across 150 countries worldwide.

In Hungary, they engaged in manufacturing and sale of APIs, intermediates and finished products which are supplied in the domestic and foreign markets.Some of their key APIs include Codeine Phosphate Hemihydrate, Dihydrocodeine Bitartrate, and Pholcodine, Ethylmorphine HCl, Oxycodone HCl, Morphine Sulfate, Phenobarbital Acid and Sodium. Their diverse product portfolio covers cardiology, substances for the central nervous system, antidepressants, antispasmodics and other products for coughing.

Their operations in Hungary are supported by global R&D and manufacturing with an unwavering commitment to quality. Their medicines are trusted by healthcare professionals and patients in over 150 countries of the world. Their global presence is supported by over 41 manufacturing facilities across 5 continents. They have a multi-cultural workforce comprising more than 30,000 employees of over 50 nationalities.

In 2007, Sun Pharma demerged its innovative R&D arm and listed it separately on the stock market as the Sun Pharma Advanced Research Company Ltd. (NSE: SPARC, BSE: 532872). In 2013, SPARC declared revenue of Rs. 873 million. SPARC focuses on new chemical entities (NCE) research. Market Cap in May 2017 was $24.9 Billion (sunpharma, 2019)

7.10 Investment Risk Management

Risk means uncertainty in the investment. In the stock market, there is a risk that the investor will not get the same amount which he had expected. Generally, return on investment is related to the risk. High returns mean high risk associated with that investment. High return is the reward for the risk taken for an investment. It can be caused by a various event like fluctuation in prices, changes in governmental policy, some disturbance in the world market, Risk can’t be removed from an investment but can be minimized with the risk management. Risk management is the process of identifying, analysing the uncertain event that will affect the investment. In order to make investment less risky, there is some model. With help of models and analysis, the investor can have a rough idea about the risk involves in the investments. Risk management is not only beneficial for the investor but also to the organization. It is the ongoing process it needs to be applied and make changes with the time. The risk can be reduced either by transferring the risk or sharing the risk. Transferring risk is diversifying the investment or making a diversified portfolio with this the risk got transferred to financial investments or hedging.

Financial risk modelling is done determine the risk it includes lots of model Value at Risk is the most common and efficient model to identify the risk. Basel II also proposed the risk modelling.

7.11 VAR MODEL

It measures the risk involves in the investments. It helps in estimating the loss of investment in a period. It is a statistical measurement of the riskiness of financial entities or portfolios of assets. This model gives the probability of loss of the given asset. The concept of Value at Risk was developed by J.P. Morgan as a concept to simplify the risk measurement and management processes. This measure may be obtained in a number of ways, using a statistical model or by computer simulation.

It is the maximum loss on the given asset which can occur at the certain percentage of confidence over a holding period of n days. if the VaR on an asset is $ 100 million at a one- week, 95% confidence level, there is an only a 5% chance that the value of the asset will drop more than $ 100 million over any given week. It is an important tool for risk management because this technique is able to summarize the risks across different positions and business segments in a single asset or portfolio. It can also help in estimating other types of risks such as credit risk, cash flow risk as well as the value at risk.

VaR measures, though, came from the crises that beset financial service firms over time and the regulatory responses to these crises

Value at Risk can be used be by any entity to measure its risk exposure, it is used most often by commercial and investment banks to capture the potential loss in value of their traded portfolios from adverse market movements over a specified period. This can then be compared to their available capital and cash reserves to ensure that the losses can be covered without putting the firms at risk.

Figure 3. Probability density versus portfolio value with 90% confidence in portfolio

Sources: (glynholton., 2017)

The Fig.3 shows that in case 90% VaR i.e., 90% confidence in the portfolio.

VAR have two main parameters

1. Horizon 2. Confidence Level

There are three main approaches of calculating VaR

• Variance-Covariance approach, • Historical simulation • Monte Carlo simulation

Variance approach- In this method, it is assumed that the returns on risk factors are normally distributed, the correlations between risk factors are constant. The daily Value at Risk is a function of the standard deviation and the desired confidence level. To measure the standard deviation of each risk factor is the historical data is used.

Historical Stimulation- This model calculates potential losses using actual returns in the risk factors from historical data. The rare events and crashes can be included

In the results. As the risk factor returns used for revaluing the portfolio are actual past movements, the correlations in the calculation are also actual past correlations. They capture the dynamic nature of correlation as well as scenarios when the usual correlation relationships break down.

Monte Carlo simulation method- It is similar to historical stimulation but instead of using historical changes, a distribution that adequately describes price changes are used. After simulating price changes or changes in risk factors, hypothetical profits and losses are calculated. Finally, VaR is calculated as a percentile corresponding to the chosen confidence level. This method is capable of finding the behaviour in the complex products.

Limitation

• VaR is dependent on the underlying assumptions used by the model, such as normality and liquid markets. • Using historical data sometime doesn’t help in predicting future risk.

7.12 Ratio

Financial ratios are the comparison of the financial statement of the company. It is easier to understand and give a brief idea about company’s performance. It can be also used to compare the two companies as it is a simple mathematical formula. It doesn’t take in consideration of the size of the firm. Ratio analysis allows us to compare the two companies which are in different counties doing business in different currencies. It is just computing data from the financial statement of the company and having a deep analysis of the results. The financial ratio is divided into several categories: liquidity, solvency, efficiency, profitability, market prospect, investment leverage. The ratio analysis will help in analysing the financial performance of the company with market capitalization.

I) Liquidity ratio: It analyses the company’s ability to pay it debt. It shows that if in any unseen event the company have to its debt how much it can pay off its liabilities and other a) Quick Ratio/ Acid test Ratio: shows how easily a company can convert its asset into cash in order to pay off its current liabilities.

Formula:

Total Current Assets − Inventory − Prepaid Expenses (1) Quick Ratio = Current Liabilities

II) Financial leverage ratio/ equity debt ratio: it measures the overall debt of the company in comparison of the assets or equity. It indicates the assets of the company which actually belongs to the shareholder and the capital structure of the company. If the leverage is high it means the creditors have major share in the asset. In case of solvency, the shareholder will be in loss. a) Debt to equity ratio: It shows the percentage of finance come from creditors and shareholders. This ratio helps the investor or stakeholders to know the overall burden in future indicates how much debt a company is using to finance its assets relative to the value of shareholders’ equity

Formula:

Total Liabilities (2) Debt − Equity Ratio = Shareholder′s Equity

Lower ratio is better for the company. Lower debt to equity implies the company is more financially stable.

III) Profitability Ratio:

Profitable ratio shows the profit generated by the company from its core business. It helps the investor to have an idea of the return on investment a) Profit margin/ Return on sale/ Gross profit:

It measures the amount of net income earned with each dollar of sales generated by comparing the net income and net sales of a company It shows the stakeholders to about the efficiency of company. Low margin shows that company’s expenses are high which is not good for the company. It shows how much profit is been generated in relation with the sales.

Formula:

Net Income (3) Profit margin = Net Sales

b) Return on equity Ratio

It shows the profit generated from the investment done by the shareholders. This ratio is beneficial for potential investor as it indicates how their money will be utilized by the company. Higher Ratio is better. A return on € 1 means that every euro of common stockholders' equity generates 1 euro of net income

Formula:

Net Income (4) Return on equity Ratio = Shareholder’s equity

34 b) Return on Assets

It shows the profitability of a company in relative to its total assets. It gives analyst an idea about the efficiency of company's management is at using the assets to generate earnings.

Formula:

Net Income (5) Return on Assets = Net Asset

The higher the ROA is better as the company is using less asset or investment and earning more money.

7.13 T-Test in Ms-Excel

It is a standardized value which is calculated from sample data during a hypothesis test. T- tests are the test results are all based on t-values. It is a procedure which helps in calculating the statistical test that compares data to what is expected under the null hypothesis, Null hypothesis is a hypothesis of no difference.

If data set have multiple random samples of the same size from the same population and performed the same t-test, we will have number of t-values. A specific t-distribution is known by its degrees of freedom (DF), a value closely related to sample size. Therefore, different t-distributions exist for every sample size. For t-tests, if we take a t-value and place it in the context of the correct t-distribution, we can calculate the probabilities associated with that t-value.A probability allows us to find how common or rare our t-value is under the assumption that the null hypothesis is true. If the probability is low enough, we can conclude that the effect observed in our sample is inconsistent with the null hypothesis. The evidence in the sample data is strong enough to reject the null hypothesis for the entire population. (Minitab Blog Editor, 2016)

8 Quantitative Analysis 8.1.1 OTP Ratio Analysis Table 4. OTP Ratio analysis

Average Price Return Net Profit Margin ROA ROE Liquidity Ratio Debt equity

2013 12.130% 14.95 9.99 16.8 0.81 0.06

2014 86.543% 15.23 9.17 16.3 0.68 0.18

2015 88.452% 11.45 5.53 10.4 0.76 0.26

2016 45.182% 10.83 4.07 7.73 0.7 0.25

2017 22.075% 14.46 5.64 10.1 0.8 0.21

(Source: Own construction) T-TEST Table 5. OTP T-Test

Net Profit Liquidit Debt ROA ROE Margin y Ratio equity

Mean 0.5087645 0.50876 0.508764 0.50876 0.50876 Variance 0.1261812 0.12618 0.126181 0.12618 0.12618 Observations 5 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 0 df 4 4 4 4 4

t Stat -5.516570 -6.4727 -13.6531 - 1.4984 1.94475

P(T<=t) one-tail 0.002635 0.00146 0.000083 0.10418 0.06185 t Critical one- tail 2.13184676 2.13184 2.131846 2.13184 2.13184

(Source: Own construction)

The above results are derived from Excel using Data analysis, Since the p value is set at 0.05, we can see that the P(T<=t) one-tail value is for the ROE (0.002), ROA (0.0014), Net Profit Margin ratio (0.000083) is smaller than the p-value(0.05) to reject the null hypothesis, Moreover, the t-value is smaller than the t-critical value, for ROE , ROA, Net Profit Margin ratio reject the null hypothesis

8.1.2 Richter Gedeon Nyrt

RATIO ANALYSIS Table 6. Richter Gedeon Nyrt Ratio analysis

Average Price Return Net ROA ROE Liquidity Ratio Debt Profit equity Margin 2013 -0.047% 12.17 6.16 8.03 2.9 0.1

2014 0.103% 7.05 3.47 4.51 2.37 0.08

2015 -0.168% 14.86 7.39 9.23 3.26 0.06

2016 -0.041% 16.99 8.47 10.2 2.45 0.04

2017 -0.015% 2 1.13 1.33 2.54 0

(Source: Own construction) T-TEST Table 7. Richter Gedeon Nyrt T-Test

Net Profit Debt Liquidity Margin equity Ratio ROA ROE - - Mean -0.00033777 -0.00033 0.000337779 -0.000337 0.0003377

Variance 9.31827 9.31827 9.31827 9.31827 9.31827

Observations 5 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 0

df 4 4 4 4 4

t Stat -3.90182744 -3.273535 -16.3000115 -3.974658 -4.048802 P(T<=t) one- tail 0.008757189 0.015343 0.00004145 0.008171 0.007571 t Critical one- tail 2.131846786 2.131846 2.131846786 2.131786 2.131786

(Source: Own construction)

The above results are derived from Excel using Data analysis, Since the p value is set at 0.05, we can see that the P(T<=t) one-tail value is for all the ratio is smaller than the p-value to reject the null hypothesis, ROE (0.0075), Net profit (0.008), ROA (0.0081), Liquidity (0.00004), Debt Equity (0.01) Moreover, the t-value is smaller than the t-critical value, for all the ratio reject the null hypothesis

8.1.3 MOL

RATIO ANALYSIS Table 8. MOL Ratio analysis

YEAR Average Price Return Liquidity Debt ROA ROE Net Ratio equity Profit Margin 2013 0.017% 0.85 0.4 0.46 1.27 0.4

2014 0.035% 0.58 0.26 0.09 0.24 0.08

2015 -0.118% 0.52 0.32 - -16 -6.25 5.98

2016 -0.353% 0.55 0.29 6.56 17.87 7.42

2017 0.372% 0.66 0.28 7.36 18.99 7.43

(Source: Own construction)

T-TEST Table 9. MOL T-Test

Net Profit Liquidity Debt ROA ROE Margin Ratio equity Mean -9.4E-05 -9.4E-05 -9.4E-05 -9.4E-05 -9.4E-05 Variance 6.95E-06 6.95E-06 6.95E-06 6.95E-06 6.95E-06 Observations 5 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 0 df 4 4 4 4 4 t Stat -0.69683 -0.69138 -0.70425 -10.6609 -12.6449 P(T<=t) one-tail 0.262141 0.26368 0.260059 0.000219 0.000113 t Critical one-tail 2.131847 2.131847 2.131847 2.131847 2.131847

(Source: Own construction)

The above results are derived from Excel using Data analysis, Since the p value is set at 0.05, we can see that the P(T<=t) one-tail value is for Liquidity Ratio (0.00021) and Debt Equity

Ratio (0.00011) is smaller than the p-value to reject the null hypothesis for them, Moreover, the t-value is smaller than the t-critical value, for Liquidity Ratio and Debt Equity Ratio reject the null hypothesis

8.1.4 SBI

RATIO ANALYSIS Table 10. SBI Ratio analysis

Average Price Return Debt ROA ROE Net Profit equity Margin

2013 -0.046% 1.69 0.90 15.49 18.98

2014 -0.060% 1.56 0.63 10.41 13.60

2015 -0.146% 1.63 0.67 11.01 13.67

2016 0.160% 1.54 0.79 13.03 17.33

2017 -0.151% 1.67 0.01 0.12 0.17

(Source: Own construction)

T-TEST Table 11. SBI T-Test

Net Profit SBI ROA Margin ROE Debt equity Mean -0.0004859257 -0.0004859257 -0.00048592570 -0.00048592570 Variance 0.00000158788 0.00000158788 0.00000158788 0.00000158788 Observations 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 df 4 4 4 4 t Stat 3.87609433832 3.84778788961 3.80999226379 -54.73615955184 P(T<=t) one- tail 0.00895026971 0.00916858878 0.00947013343 0.00000033347 t Critical one- tail 2.13184678633 2.13184678633 2.13184678633 2.13184678633

(Source: Own construction) 43

ROA (0.0089), Net profit (0.009), ROE (0.0094) Liquidity (0.00004), Debt Equity (0.0000003334)

Moreover, the t-value is smaller than the t-critical value, for all the ratio reject the null hypothesis.

8.1.5 Sun Pharma

RATIO ANALYSIS Table 12. Sun Pharma Ratio analysis

Year Average Price Return Liquidity Debt ROA ROE Net Ratio equity Profit Margin 2013 -0.1431% 2.69 0.01 16.06 21.97 26.40

2014 -0.1234% 2.06 0.01 12.50 18.75 19.54

2015 -0.2256% 1.21 0.05 11.58 20.56 16.55

2016 0.1374% 1.72 0.10 9.14 16.53 16.68

2017 0.0819% 1.34 0.04 12.05 20.47 22.24

(Source: Own construction)

T-TEST Table 13. Sun Pharma T-Test

Net Profit Liquidity Debt Margin Ratio equity ROA ROE - Mean 0.000545807 -0.00055 -0.00055 -0.00055 - 0.000545807 Variance 2.43275E-06 2.43E-06 2.43E-06 2.43E-06 0.000002433 Observations 5 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 0 df 4 4 4 4 4 t Stat -10.9422587 -6.75872 -2.56801 -11.0294 - 21.057619236 P(T<=t) one- tail 0.000198103 0.00125 0.031055 0.000192 0.000015031 t Critical one- tail 2.131846786 2.131847 2.131847 2.131847 2.131846786

(Source: Own construction)

The above results are derived from Excel using Data analysis, Since the p value is set at 0.05, we can see that the P(T<=t) one-tail value is for all the ratio for Sun Pharma is smaller than the p-value to reject the null hypothesis,

ROA (0.000192), Net profit (0.000198103), ROE (0.000015031) Liquidity (0.00125), Debt Equity (0.031055)

Moreover, the t-value is smaller than the t-critical value, for all the ratio reject the null hypothesis.

8.1.6 ONGC

RATIO ANALYSIS Table 14. ONGC Ratio analysis

Average Price Return Net Profit ROA ROE Liquidity Ratio Debt Margin equity

2013 12.130% 14.95 9.99 16.8 0.81 0.06

2014 86.543% 15.23 9.17 16.3 0.68 0.18

2015 88.452% 11.45 5.53 10.4 0.76 0.26

2016 45.182% 10.83 4.07 7.73 0.7 0.25

2017 22.075% 14.46 5.64 10.1 0.8 0.21

(Source: Own construction) T-TEST Table 15. ONGC T-Test

Net Profit Liquidity Debt ROA ROE Margin Ratio equity 0.5087647 0.5087647 Mean 0.508764765 0.508764765 0.508764765 65 65 0.1261815 0.1261815 Variance 0.126181522 0.126181522 0.126181522 22 22 Observations 5 5 5 5 5 Hypothesized Mean Difference 0 0 0 0 0 df 4 4 4 4 4 t Stat -5.51656979 -6.472728814 -13.65315138 -1.4984912 1.9447588 P(T<=t) one-tail 0.002635293 0.001467717 8.33326E-05 0.1041855 0.0518496 t Critical one-tail 2.131846786 2.131846786 2.131846786 2.1318467 2.1318467

(Source: Own construction) The above results are derived from Excel using Data analysis, Since the p value is set at 0.05, we can see that the P(T<=t) one-tail value is for ROE, ROA and Debt Equity is smaller than

47 the p-value to reject the null hypothesis, Moreover, the t-value is smaller than the t-critical value, for ROE, ROA and Debt Equity reject the null hypothesis,

From analyses of taken company we accept our Hypothesis H1: There is significant relationship between taken companies financial ratios and their stock market price.

VAR ANALYSIS 8.2.1 HUNGARIAN COMPANIES’ PORTFOLIO

Var analysis measure of the risk of loss for investments. In this analysis portfolio of the stock prices of Hungarian company (MOL, OTP Bank, Richter Gedeon Nyrt) are analysed.

1january 2018-31march 2018 stock prices is used.

Here it is assumed investor decided to invest 900 euro (300euro in each company) or

281,250.00 Hungarian forints.

Data analysis is done on excel. Using data of 3months. 1 huf= 0.0032 euro

Table 16. Frequency of Hungarians companies Portfolio

Cumulative Bin Frequency % -29.12 1 1.67% -20.75 5 10.00% -12.39 3 15.00% -4.03 15 40.00% 4.33 17 68.33% 12.69 15 93.33% 21.06 1 95.00% More 3 100.00%

(Source: Own construction)

Figure 4. Histogram Hungarians companies Portfolio Fig.4 . Histogram to show the frequency

Histogra 18 m 120.00 % 16 100.00 14 % 12 80.00 % 10 60.00 % Frequency 40.00 Cumulative %

20.00 % 0.00 -29.12 -20.75 -12.39 -4.03 4.3 12.69 21.06 % 3 Mo Bin

(Source: Own construction)

Var 95%= -22.63 euro

Interpretation: histogram is calculated using a series of period of return i.e.,

푉퐴푅 = LN(P0 − P1) ∗ portfolio investment (9)

In worst scenario loss will incur on the portfolio based on the model at 95% of confidence is -22.63Euro. (In the extreme left corner on the bottom of the histogram highlighted by dotted line).1

Total portfolio=sum of three investments each day period of return

95% var= =PERCENTILE.EXC (array of total portfolio return,5%).

1 As the stock market price of Hungarian company is in ft in order to analyses the data the Total portfolio is converted into euro. 50

8.2.2 Indian Companies’ Portfolio

Var analysis measure of the risk of loss for investments. In this analysis portfolio of the stock prices of Indian company (ONGC, SBI, Sun Pharma) are analysed. 1january 2018-31march 2018 stock prices are used.

Here it is assumed investor decided to invest 900 euro (300euro in each company) or

Rs. 75000

Data analysis is done on excel. Using data of 3months. Rs. 1= 0.012euro

Table 17. Frequency of Indian companies Portfolio

Cumulative Bin Frequency % -31.62 1 1.67% -23.5 1 3.33% -15.38 6 13.33% -7.27 11 31.67% 0.85 16 58.33% 8.97 15 83.33% 17.08 4 90.00% More 6 100.00% (Source: Own Construction)

Figure 5. Histogram of Indian Companies Portfolio

Histogram 18 120.00 % 16 100.00 14 % 80.00 % 10 60.00 % Frequency 40.00 Cumulative % %

20.00 % 0.00 -31.62-23.50-15.38 -7.27 0.85 8.97 17.08 % More

(Source: Own construction) Var 95%= -22.4768 euro

Interpretation: histogram is calculated using a series of period of return i.e.,

=LN(P0-P1) *portfolio investment

In worst scenario loss will incur on the portfolio based on the model at 95% of confidence is - 22.4768 Euro. (In the extreme left corner on the bottom of the histogram highlighted by dotted line).

Total portfolio=sum of three investments each day period of return. 95% var =PERCENTILE.EXC (array of total portfolio return,5%).

As the stock market price of Indian company is in India rupee in order to analyse the data the Total portfolio is converted into euro. It is concluded that both the portfolio has in significant difference in their risk, hence we reject our Hypothesis. (H2: Risk involved investing by portfolio of taken Indian companies of Bombay Stock Exchange is higher than investing by portfolio of taken Hungarian companies of Budapest Stock Exchange.)

8.2.3 BUX VAR

In order to have analysis of stock exchange I have done VAR analyses (Historical Stimulation) on index of both stock exchange i.e., BUX (for Budapest stock exchange)

Prices of indices were taken i.e., 1 January 2017-31 December 2017.

VAR =PERCENTILE (array,5%)

Var 95%=0.0218

Table 18. Frequency of BUX

Bin Frequency Cumulative % -0.025 1 0.40% -0.021 2 1.20% -0.017 4 2.80% -0.012 8 6.00% -0.008 13 11.20% -0.004 38 26.40% 0.000 44 44.00% 0.005 60 68.00% 0.009 50 88.00% 0.013 19 95.60% 0.018 8 98.80% 0.022 2 99.60% 0.026 0 99.60% 0.031 0 99.60% 0.035 0 99.60% More 1 100.00% (Source: Own construction)

Figure 6. Histogram of BUX

BUX 70 120.00% 60 100.00% 50 80.00% 40 60.00% 30 40.00% Frequency 20 10 20.00% Frequency

0 0.00% Cumulative %

0.021975017 0.000445211 0.004751172 0.009057133 0.013363094 0.017669056 0.026280978 0.030586939 0.034892901

-0.025390557 -0.021084596 -0.016778635 -0.012472673 -0.008166712 -0.003860751 Bin

(Source: Own construction)

In worst scenario loss will incur on the portfolio based on the model at 95% of confidence is Var 95%=0.0218. (In the extreme left corner on the bottom of the histogram highlighted by dotted line).

8.2.4 SENSEX VAR

In order to have analysis of stock exchange I have done VAR analyses (Historical Stimulation) on index of both stock exchange i.e., SENSEX (for Bombay stock exchange) Prices of indices were taken i.e., 1 January 2017-31 December 2017.

VAR =PERCENTILE (array,5%)

Var 95%=0.085

Table 19. Frequency of Sensex

Bin Frequency Cumulative % -0.01402 1 0.40% -0.01193 2 1.21% -0.00983 6 3.64% -0.00773 8 6.88% -0.00564 14 12.55% -0.00354 15 18.62% -0.00145 29 30.36% 0.000647 42 47.37% 0.002742 45 65.59% 0.004837 25 75.71% 0.006933 22 84.62% 0.009028 19 92.31% 0.011123 12 97.17% 0.013218 3 98.38% 0.015314 2 99.19% More 2 100.00% (Source: Own construction)

Figure 7. Histogram of Sensex

SENSEX 50 120.00% 45 40 100.00% 35 80.00% 30 25 60.00% 20 Frequency 40.00% 15 Frequency 10 20.00% 5 Cumulative %

0 0.00%

0.00274199 0.01321847

0.000646694 0.004837286 0.006932582 0.009027878 0.011123174 0.015313766

-0.014020377 -0.011925081 -0.009829785 -0.007734489 -0.005639193 -0.003543897 -0.001448602 Bin

(Source: Own construction)

The above analysis indicates that Sensex is riskier than BUX. As the greater VaR 95% confidence is riskier. In worst scenario loss will incur on the portfolio based on the model at 95% of confidence is Var 95%=0.085. (In the extreme left corner on the bottom of the histogram highlighted by dotted line).

It is concluded that both the portfolio has in significant difference in their risk, hence we accept our Hypothesis. (H3: Risk involved in investing in investing in SENSEX (Index of Bombay stock exchange) is higher than investing in BUX (Index of Budapest Stock Exchange)

9. Conclusion Both India and Hungary are developing countries. By surface comparison of the market capitalization and the market size of Bombay stock exchange with Budapest stock exchange, it might seem that the former is stronger as it is more liquid and is the world’s 3rd largest stock exchange on investor’s basis. Due to high economic growth and large market size, Bombay stock exchange have large volume of trade, traded on the exchange.

Unfortunately, Budapest stock exchange have not fully recovered yet from the global crises which is also one of the main reasons that its economic growth is slower than the Bombay stock exchange. However, this is compensated by the fact that Hungary is a member of European Union and this provides the companies listed in Budapest stock exchange, highly competitive advantages to have easy trade with other countries. The VaR analysis at 95% confidence for Hungarian company portfolio was -22.63 Euro and for Indian company portfolio was -22.4768 Euro. Thus, it can be concluded that the risk associated on investment in Oil, Banking and Pharmaceutical industries of India and Hungary do not have significant difference. This value also shows that presently both the markets are financially stable. Despite of large market size and high economic growth, the hypothesis of Bombay stock exchange being less risky than Budapest stock exchange in Oil, Banking and Pharmaceutical industries is not true.

Financial results have become an important indicator for business valuation. The Average Price Return have the significant influence on the Ratios represents the aggregate value of a company or stock. The purpose of this study is to analyse the relationship between the Financial Ratio and the Average Price Return of the chosen companies from the two Stock Exchanges. From T-test we have proved that all the Hypothesis of this study is correct there is significant relationship between the Ratio and Prices, Analysis of Ratio and Prices is beneficial for the investor to take decision of investment for both the market

The analysis of each company provided further insight. Richter Gedeon Nyrt have sufficient current assets to cover its liabilities and its debt ratio shows that presently the company is always below the threshold which is good for the company.However, the profit margin ROA, ROE has decreased from previous years. The return on equity has increased which indicates that the money of shareholders is efficiently used by the Richter Gedeon Nyrt.

The current ratio and quick ratio of Sun Pharma is more than ideal ratio which indicates that the company have ability to pay-off its current debt with its current asset without selling its 57 long-term asset in order to have smooth functioning of daily operations of business. The Debt-equity ratio show that the sun pharma is lower which is beneficial for the company as it is important for a company to receive payment from its debtor in order to have smooth functioning of business. Therefore, from the Ratio analysis of Sun Pharma, it can be concluded that the company is in good financial position.

Mol, it has improving from previous years its Liquidity ratio But still less than the ideal ratio. However, the overall liquidity ratio of company is less than the ideal ratio. This shows company does have sufficient current asset to pay off its debts. Though the efficiency ratio and financial ratio have reached to its ideal ratio but still has not reached to the same level as in 2015. The current ratio of is Mol lower than ONGC, still it is aligned with the ideal ratio but the quick ratio is less than 1 which is not beneficial for the company. The financial ratio is according to the ideal ratio which reflects that the company is less risky. ONGC is using its funds wisely which was concluded by calculating its profit ratios.

Financial ratio of the OTP improved in 2016 but the in 2017 it decreased again which created a negative impact on the good will of the company. On the other hand, State Bank of India debt equity ratio is high shows that it doesn’t have sufficient current asset to pay off its debts.in 2017 has been improved from previous year. Net profit margin for SBI have good but in 2017 OTP was better. The ROE, ROA of OTP is better than SBI.

From the analysis we accept

➢ H1: There is significant relationship between taken companies financial ratios and their stock market price. ➢ H3: Risk involved in investing in investing in SENSEX (Index of Bombay stock exchange) is higher than investing in BUX (Index of Budapest Stock Exchange).

And we reject

➢ H2: Risk involved investing by portfolio of taken Indian companies of Bombay Stock Exchange is higher than investing by portfolio of taken Hungarian companies of Budapest Stock Exchange.

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Appendix

Hungarian VaR model working

Date Prices Period retu eriod retu eriod retu eriod retu eriod retu Period return PORTFOLIO (yyymmdd) otp mol Richter otp mol Richter otp mol Richter Total portfolio total % of euro return Mar 29, 11,420.00 2,772.00 5,305.00 1.41% 1.09% 0.76% 1322.77 1020.14 709.56 3052.47 9.77 3.26% 20 Mar 28, 11,260.00 2,742.00 5,265.00 -0.62% -2.95% -1.69% -581.01 -2762.51 -1589.02 -4932.54 -15.78 -5.26% 20 Mar 27, 11,330.00 2,824.00 5,355.00 -0.18% 0.07% 2.94% -165.34 66.42 2753.63 2654.71 8.50 2.83% 20 Mar 26, 11,350.00 2,822.00 5,200.00 0.44% 0.07% 0.77% 413.91 66.47 723.94 1204.32 3.85 1.28% 20 Mar 23, 11,300.00 2,820.00 5,160.00 -0.88% -0.57% -2.68% -826.00 -530.41 -2509.71 -3866.12 -12.37 -4.12% 20 Mar 22, 11,400.00 2,836.00 5,300.00 -1.65% -3.87% -2.33% -1549.62 -3631.16 -2185.41 -7366.19 -23.57 -7.86% 20 Mar 21, 11,590.00 2,948.00 5,425.00 1.22% 1.92% -1.55% 1139.34 1798.00 -1457.51 1479.83 4.74 1.58% 20 Mar 20, 11,450.00 2,892.00 5,510.00 1.23% -0.28% 1.19% 1153.35 -258.98 1112.52 2006.89 6.42 2.14% 20 Mar 19, 11,310.00 2,900.00 5,445.00 -3.65% -3.79% -2.27% -3418.35 -3552.52 -2127.87 -9098.74 -29.12 -9.71% 20 Mar 14, 11,730.00 3,012.00 5,570.00 2.07% 0.27% -1.51% 1938.05 249.34 -1419.85 767.54 2.46 0.82% 20 Mar 13, 11,490.00 3,004.00 5,655.00 -0.26% -0.33% -0.18% -244.46 -311.57 -165.64 -721.66 -2.31 -0.77% 20 Mar 12, 11,520.00 3,014.00 5,665.00 1.49% 1.20% 0.09% 1393.77 1126.52 82.78 2603.07 8.33 2.78% 20 Mar 09, 11,350.00 2,978.00 5,660.00 -0.70% -0.87% -1.14% -658.48 -814.95 -1070.50 -2543.92 -8.14 -2.71% 20 Mar 08, 11,430.00 3,004.00 5,725.00 0.79% 2.15% 0.44% 741.11 2018.92 410.29 3170.32 10.15 3.38% 20 Mar 07, 11,340.00 2,940.00 5,700.00 1.06% 2.20% -3.02% 997.35 2063.36 -2834.99 225.72 0.72 0.24% 20 Mar 06, 11,220.00 2,876.00 5,875.00 1.35% 3.76% 4.70% 1261.80 3520.60 4410.66 9193.06 29.42 9.81% 20 Mar 05, 11,070.00 2,770.00 5,605.00 -0.18% 1.90% 1.80% -169.22 1776.66 1687.71 3295.15 10.54 3.51% 20 Mar 02, 11,090.00 2,718.00 5,505.00 -1.96% -3.26% -2.33% -1841.58 -3054.02 -2188.16 -7083.75 -22.67 -7.56% 20 Mar 01, 11,310.00 2,808.00 5,635.00 -1.67% -0.28% -0.80% -1561.85 -266.71 -745.70 -2574.26 -8.24 -2.75% 20 Feb 28, 11,500.00 2,816.00 5,680.00 -0.35% -0.57% -2.09% -325.52 -531.16 -1960.00 -2816.69 -9.01 -3.00% 20 Feb 27, 11,540.00 2,832.00 5,800.00 0.35% 1.14% -4.71% 325.52 1065.35 -4420.01 -3029.14 -9.69 -3.23% 20 Feb 26, 11,500.00 2,800.00 6,080.00 1.58% 1.08% 0.83% 1479.00 1009.88 774.16 3263.04 10.44 3.48% 20 Feb 23, 11,320.00 2,770.00 6,030.00 -1.49% -1.29% -0.25% -1397.44 -1210.56 -232.92 -2840.92 -9.09 -3.03% 20 Feb 22, 11,490.00 2,806.00 6,045.00 -0.87% -1.35% -0.58% -812.40 -1261.08 -541.24 -2614.72 -8.37 -2.79% 20 Feb 21, 11,590.00 2,844.00 6,080.00 1.57% -1.19% 3.01% 1467.42 -1114.13 2817.41 3170.69 10.15 3.38% 20 Feb 20, 11,410.00 2,878.00 5,900.00 -1.65% -0.62% 0.00% -1548.28 -584.52 0.00 -2132.79 -6.82 -2.27% 20 Feb 19, 11,600.00 2,896.00 5,900.00 -1.28% 0.97% -0.76% -1204.51 910.83 -712.33 -1006.01 -3.22 -1.07% 20 Feb 16, 11,750.00 2,868.00 5,945.00 2.59% 0.00% 2.99% 2424.70 0.00 2801.10 5225.81 16.72 5.57% 20 Feb 15, 11,450.00 2,868.00 5,770.00 -1.13% -1.04% 4.43% -1058.41 -975.56 4152.58 2118.61 6.78 2.26% 20 Feb 14, 11,580.00 2,898.00 5,520.00 -0.17% 0.07% 0.36% -161.78 64.72 340.29 243.24 0.78 0.26% 20 Feb 13, 11,600.00 2,896.00 5,500.00 1.74% -0.28% -1.80% 1630.48 -258.62 -1689.23 -317.38 -1.02 -0.34% 20 Feb 12, 11,400.00 2,904.00 5,600.00 1.77% 1.60% -6.65% 1659.34 1496.91 -6233.41 -3077.17 -9.85 -3.28% 20 Feb 09, 11,200.00 2,858.00 5,985.00 0.72% -1.11% -6.78% 672.05 -1043.85 -6358.37 -6730.17 -21.54 -7.18% 20 Feb 08, 11,120.00 2,890.00 6,405.00 -2.31% -3.13% -1.86% -2166.76 -2937.91 -1740.19 -6844.86 -21.90 -7.30% 20 Feb 07, 11,380.00 2,982.00 6,525.00 3.40% 1.08% 3.19% 3183.95 1011.47 2992.66 7188.09 23.00 7.67% 20 Feb 06, 11,000.00 2,950.00 6,320.00 -3.40% -2.68% -1.26% -3183.95 -2508.51 -1179.26 -6871.72 -21.99 -7.33% 20 Feb 05, 11,380.00 3,030.00 6,400.00 -0.70% -0.33% -0.08% -656.75 -308.90 -73.21 -1038.86 -3.32 -1.11% 20 Feb 02, 11,460.00 3,040.00 6,405.00 -0.87% -1.31% -0.23% -814.51 -1225.51 -219.30 -2259.32 -7.23 -2.41% 20 Feb 01, 11,560.00 3,080.00 6,420.00 -0.26% 0.85% -0.08% -242.98 794.76 -72.99 478.79 1.53 0.51% 20 Jan 31, 11,590.00 3,054.00 6,425.00 1.65% 0.59% -0.39% 1549.62 554.19 -364.08 1739.73 5.57 1.86% 20 62

Jan 30, 11,400.00 3,036.00 6,450.00 -1.39% -2.09% -0.70% -1306.64 -1955.74 -651.80 -3914.18 -12.53 -4.18% 20 Jan 29, 11,560.00 3,100.00 6,495.00 0.35% -1.22% -2.36% 324.96 -1142.21 -2211.02 -3028.27 -9.69 -3.23% 20 Jan 26, 11,520.00 3,138.00 6,650.00 1.66% 0.83% 0.08% 1559.12 780.00 70.52 2409.64 7.71 2.57% 20 Jan 25, 11,330.00 3,112.00 6,645.00 -1.75% -1.85% -0.38% -1640.46 -1731.19 -352.05 -3723.69 -11.92 -3.97% 20 Jan 24, 11,530.00 3,170.00 6,670.00 -1.72% -0.94% -1.56% -1612.25 -883.05 -1464.33 -3959.63 -12.67 -4.22% 20 Jan 23, 11,730.00 3,200.00 6,775.00 3.29% 0.13% -0.07% 3087.37 117.26 -69.16 3135.47 10.03 3.34% 20 Jan 22, 11,350.00 3,196.00 6,780.00 3.41% 3.11% 1.19% 3192.51 2919.68 1112.77 7224.97 23.12 7.71% 20 Jan 19, 10,970.00 3,098.00 6,700.00 0.55% 2.09% 0.15% 514.17 1957.02 140.03 2611.22 8.36 2.79% 20 Jan 18, 10,910.00 3,034.00 6,690.00 -0.27% 0.60% 0.22% -257.44 557.85 210.44 510.85 1.63 0.54% 20 Jan 17, 10,940.00 3,016.00 6,675.00 -0.36% 0.20% -0.37% -342.15 186.69 -350.47 -505.93 -1.62 -0.54% 20 Jan 16, 10,980.00 3,010.00 6,700.00 1.10% -0.20% -0.52% 1030.23 -186.69 -488.46 355.08 1.14 0.38% 20 Jan 15, 10,860.00 3,016.00 6,735.00 -0.64% -0.92% -0.59% -602.34 -866.34 -555.15 -2023.83 -6.48 -2.16% 20 Jan 12, 10,930.00 3,044.00 6,775.00 -0.09% 0.66% 0.67% -85.73 618.00 624.77 1157.04 3.70 1.23% 20 Jan 11, 10,940.00 3,024.00 6,730.00 1.38% -0.20% -0.44% 1294.31 -185.83 -416.98 691.51 2.21 0.74% 20 Jan 10, 10,790.00 3,030.00 6,760.00 -0.55% -1.70% 0.89% -519.87 -1595.26 835.82 -1279.32 -4.09 -1.36% 20 Jan 09, 10,850.00 3,082.00 6,700.00 -1.10% -0.26% -0.74% -1031.17 -243.03 -697.03 -1971.24 -6.31 -2.10% 20 Jan 08, 10,970.00 3,090.00 6,750.00 0.27% 0.32% 0.22% 256.73 303.89 208.57 769.19 2.46 0.82% 20 Jan 05, 10,940.00 3,080.00 6,735.00 -0.18% 0.59% 0.97% -171.23 549.50 909.18 1287.45 4.12 1.37% 20 Jan 04, 10,960.00 3,062.00 6,670.00 1.10% 0.52% -0.52% 1032.12 491.16 -490.66 1032.63 3.30 1.10% 20 Jan 03, 10,840.00 3,046.00 6,705.00 0.37% 0.59% 0.52% 346.58 555.65 490.66 1392.88 4.46 1.49% 20

India var model working

Date Prices Period return Period return Period return Period return eriod retu Period return PORTFOLIO (yyymmdd) SBI ONGC SUN SBI ONGC SUN SBI ONGC SUN Total portfolio euro total % PHARMA PHARMA PHARMA of 4/2/2018 246.3 180 507.799988 -1.53% 1.23% 2.47% -382.7636142 307.4378 618.0535174 542.7276766 6.5127321 2.17% 3/28/2018 250.1 177.8 495.399994 -1.49% -1.01% -1.97% -372.0675789 -251.821 -492.1962835 -1116.085095 - -4.46% 13.393021 3/27/2018 253.85 179.6 505.25 3.00% 0.53% 0.35% 749.7562921 132.591 86.74110313 969.088355 11.62906 3.88% 3/26/2018 246.35 178.65 503.5 4.89% 0.79% 0.34% 1221.783789 196.6846 84.55255351 1503.020979 18.036252 6.01% 3/23/2018 234.6 177.25 501.799988 -2.94% -0.81% -1.22% -735.0382275 -203.681 -304.5357786 -1243.255005 -14.91906 -4.97% 3/22/2018 241.6 178.7 507.950012 -2.49% 1.84% 0.64% -623.3708372 458.858 160.470601 -4.042225061 - -0.02% 0.0485067 3/21/2018 247.7 175.45 504.700012 -0.62% 0.77% -0.82% -155.9521115 193.1051 -204.7268077 -167.5738268 - -0.67% 2.0108859 3/20/2018 249.25 174.1 508.850006 0.46% -1.43% 2.18% 115.612349 -356.436 543.8511958 303.0275221 3.6363303 1.21% 3/19/2018 248.1 176.6 497.899994 -1.80% -0.45% -1.08% -449.3829697 -112.993 -269.6787086 -832.054526 - -3.33% 9.9846543 3/16/2018 252.6 177.4 503.299988 -0.59% -2.28% -2.67% -148.0170067 -571.215 -666.5772173 -1385.809665 - -5.54% 16.629716 3/15/2018 254.1 181.5 516.900024 -1.13% 0.50% -0.78% -283.7042739 124.2745 -195.1153065 -354.5450929 - -1.42% 4.2545411 3/14/2018 257 180.6 520.950012 0.82% -1.54% -0.37% 205.1199263 -384.621 -93.40490497 -272.9063012 - -1.09% 3.2748756 3/13/2018 254.9 183.4 522.900024 0.81% -0.14% 2.02% 201.8709147 -34.0553 504.6779599 672.4935624 8.0699227 2.69% 3/12/2018 252.85 183.65 512.450012 -0.12% 2.20% 1.11% -29.64308648 550.5315 277.1685981 798.0569975 9.576684 3.19% 3/9/2018 253.15 179.65 506.799988 -1.41% -0.28% -1.68% -353.0168524 -69.4831 -420.6730004 -843.1729459 - -3.37% 10.118075 3/8/2018 256.75 180.15 515.400024 4.01% -0.44% -1.86% 1003.313636 -110.773 -466.1332539 426.407144 5.1168857 1.71% 3/7/2018 246.65 180.95 525.099976 -3.92% -2.35% -1.25% -978.9590314 -587.138 -312.2692035 -1878.366504 - -7.51% 22.540398 3/6/2018 256.5 185.25 531.700012 -2.81% -0.13% -2.99% -701.5632546 -33.7154 -748.0509991 -1483.3297 - -5.93% 17.799956 3/5/2018 263.8 185.5 547.849976 0.47% -2.16% 2.47% 118.7425104 -539.949 616.7438145 195.5369313 2.3464432 0.78% 3/1/2018 262.55 189.55 534.5 -2.33% 0.56% -0.16% -583.5021266 138.8713 -39.72408272 -484.3549368 - -1.94% 5.8122592 2/28/2018 268.75 188.5 535.349976 0.35% 0.05% -1.77% 88.52977486 13.26691 -442.0410465 -340.2443568 - -1.36% 4.0829323 2/27/2018 267.8 188.4 544.900024 -2.56% -1.24% -2.04% -640.5301209 -309.908 -510.893739 -1461.332357 - -5.85% 17.535988 2/26/2018 274.75 190.75 556.150024 -0.49% 0.39% -2.49% -122.5386846 98.48995 -623.7278083 -647.7765428 - -2.59% 7.7733185 2/23/2018 276.1 190 570.200012 1.28% 2.02% 5.04% 318.9399849 505.0681 1261.110933 2085.119004 25.021428 8.34% 2/22/2018 272.6 186.2 542.150024 -0.18% -2.07% 3.26% -45.81272942 -518.223 815.5200371 251.4839996 3.017808 1.01% 2/21/2018 273.1 190.1 524.75 1.27% 1.64% -6.39% 317.8312729 411.0416 -1598.571624 -869.6987463 - -3.48% 10.436385 2/20/2018 269.65 187 559.400024 0.74% 1.10% -0.61% 186.1166278 275.5779 -153.7074122 307.9870854 3.695845 1.23% 2/19/2018 267.65 184.95 562.849976 -1.52% -0.89% -2.17% -380.0597895 -222.045 -542.6176777 -1144.72293 - -4.58% 13.736675 2/16/2018 271.75 186.6 575.200012 -2.58% -0.96% -0.36% -644.7874588 -240 -88.94052414 -973.7282261 - -3.89% 11.684739 2/15/2018 278.85 188.4 577.25 0.74% 1.36% 0.49% 184.471099 340.685 121.5591511 646.7152819 7.7605834 2.59% 2/14/2018 276.8 185.85 574.450012 -4.14% -2.65% -2.56% -1034.997639 -663.697 -640.177794 -2338.872473 -28.06647 -9.36% 2/12/2018 288.5 190.85 589.349976 -2.70% 1.64% 1.14% -675.3696808 409.413 285.8372435 19.88056235 0.2385667 0.08% 2/9/2018 296.4 187.75 582.650024 -1.69% -0.43% -0.13% -422.3582891 -106.299 -32.15985903 -560.8168724 - -2.24% 6.7298025 2/8/2018 301.45 188.55 583.400024 2.93% -0.66% 6.13% 732.1300566 -165.192 1533.030816 2099.969313 25.199632 8.40% 2/7/2018 292.75 189.8 548.700012 0.43% 2.21% -0.58% 106.9749172 552.6938 -145.3761999 514.2925592 6.1715107 2.06% 2/6/2018 291.5 185.65 551.900024 -2.10% -1.71% -0.94% -526.1575635 -427.248 -234.4450004 -1187.85088 - -4.75% 14.254211 2/5/2018 297.7 188.85 557.099976 0.27% -1.89% 1.07% 67.27366925 -472.082 268.4416498 -136.3667612 - -0.55% 1.6364011 2/2/2018 296.9 192.45 551.150024 -2.87% -1.37% -0.92% -717.9507627 -341.898 -230.2696381 -1290.118257 - -5.16% 15.481419 2/1/2018 305.55 195.1 556.25 -2.33% -4.14% -4.07% -582.268932 -1035.41 -1017.222763 -2634.901282 - -10.54% 31.618815 1/31/2018 312.75 203.35 579.349976 -0.03% -0.22% -2.04% -7.992806897 -55.2618 -510.4184629 -573.673111 - -2.29% 6.8840773 1/30/2018 312.85 203.8 591.299988 0.56% -0.56% 0.72% 140.2359608 -140.672 180.3376974 179.9012382 2.1588149 0.72% 1/29/2018 311.1 204.95 587.049988 -0.66% -1.60% 1.09% -164.1966655 -399.331 271.8920398 -291.6358441 - -1.17% 3.4996301 1/25/2018 313.15 208.25 580.700012 -5.09% -1.07% -0.93% -1272.351603 -268.659 -231.4022373 -1772.413142 - -7.09% 21.268958 1/24/2018 329.5 210.5 586.099976 3.55% 1.60% 1.37% 888.1242791 401.0628 343.588999 1632.776117 19.593313 6.53% 1/23/2018 318 207.15 578.099976 3.76% 3.54% 0.31% 941.240523 884.3955 77.96212382 1903.598129 22.843178 7.61% 1/22/2018 306.25 199.95 576.299988 -0.91% 3.23% 0.75% -227.5318854 806.8279 187.233656 766.5296319 9.1983556 3.07% 1/19/2018 309.05 193.6 572 2.06% -0.23% -0.74% 514.8913711 -58.0417 -185.0650733 271.7846118 3.2614153 1.09% 1/18/2018 302.75 194.05 576.25 -1.18% -0.82% -1.22% -295.5219081 -205.286 -306.1428454 -806.9508714 - -3.23% 9.6834105 1/17/2018 306.35 195.65 583.349976 3.39% -0.74% 0.90% 846.5549074 -184.598 226.0121389 887.968881 10.655627 3.55% 1/16/2018 296.15 197.1 578.099976 -2.04% 0.28% 0.29% -509.7106758 69.85944 73.62292025 -366.2283188 - -1.46% 4.3947398 1/15/2018 302.25 196.55 576.400024 0.15% -1.86% -1.35% 37.24957306 -466.243 -338.1766914 -767.1700888 - -3.07% 64

9.2060411 1/12/2018 301.8 200.25 584.25 -0.07% 1.26% -0.71% -16.56277006 314.0745 -176.9514024 120.56031 1.4467237 0.48% 1/11/2018 302 197.75 588.400024 0.32% 0.20% 0.47% 78.76733312 50.61935 117.1161755 246.502862 2.9580343 0.99% 1/10/2018 301.05 197.35 585.650024 -1.06% 0.23% -0.20% -264.3351954 57.07193 -51.17067885 -258.4339408 - -1.03% 3.1012073 1/9/2018 304.25 196.9 586.849976 -0.46% -0.13% -0.87% -114.7726244 -31.7219 -216.324562 -362.8190543 - -1.45% 4.3538287 1/8/2018 305.65 197.15 591.950012 -0.18% -0.28% 2.26% -44.94713923 -69.6471 563.7896682 449.1954012 5.3903448 1.80% 1/5/2018 306.2 197.7 578.75 -0.60% -0.83% -0.39% -150.5886523 -207.785 -97.00378629 -455.3771617 - -1.82% 5.4645259 1/4/2018 308.05 199.35 581 1.70% 2.88% 2.04% 425.6103817 718.7887 510.7762977 1655.175404 19.862105 6.62% 1/3/2018 302.85 193.7 569.25 -0.02% -1.66% -0.39% -4.126124648 -415.983 -98.61945728 -518.7285634 - -2.07% 6.2247428 1/2/2018 302.9 196.95 571.5 -1.36% 2.34% -0.37% -340.1965867 584.3342 -91.69410524 152.4434865 1.8293218 0.61% 1/1/2018 307.05 192.4 573.599976 #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0! #DIV/0!