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CROSS LISTING AND VALUE CREATION:

AN EMPIRICAL STUDY IN INDIAN CONTEXT

HARSHITA

2016 SMF 6507

DEPARTMENT OF MANAGEMENT STUDIES (D.M.S.)

INDIAN INSTITUTE OF TECHNOLOGY DELHI

MAY 2018

CROSS LISTING AND VALUE CREATION:

AN EMPIRICAL STUDY IN INDIAN CONTEXT

Submitted in partial fulfilment for the award of degree of

MASTER OF BUSINESS ADMINISTRATION

HARSHITA

(2016 SMF 6507)

Under the supervision of

PROF. P. K. JAIN

DR. SMITA KASHIRAMKA

DEPARTMENT OF MANAGEMENT STUDIES

INDIAN INSTITUTE OF TECHNOLOGY DELHI

MAY 2018

ACKNOWLEDGEMENT

I express my deep gratitude towards my supervisors and project guide, Prof. P. K.

Jain and Dr. Smita Kashiramka, for their continuous inputs throughout the project

work. The productive discussions with them gave me an insight into new concepts

and knowledge, which helped in the fruition and materialization of my thought

process into this project work.

I would also like to extend my thanks to the head of the department Prof. M. P.

Gupta for providing the requisite facilities in the department for the completion of

this project work. I am also indebted to the department‟s faculty members for their

invaluable contribution during the course of study of the programme. I am grateful to

the entire Department of Management Studies and its staff members, for their help

and inputs in the completion of the project work.

Finally I would like to thank all my family members for their continuous

encouragement and emotional support during the course of study of the programme.

HARSHITA

M.B.A. Candidate at D.M.S., I.I.T. Delhi

ABSTRACT

The study examines the impact of international cross listing on shareholders‟ wealth.

The dataset consists of 146 instances of first international cross listing by Indian

companies during the period 1997-2017. Using event study methodology, the study

finds negative abnormal returns around the date of announcement of cross listing. In

addition, the post-recession returns have been noted to be significantly positive, while

the pre-recession and during recession returns are significantly negative for

shareholders. The study also examines various determinants of value creation and

results show negative relation of financial leverage and business freedom with

abnormal returns. Evidence provides that abnormal returns vary across host markets.

Returns are negative for Luxembourg and London, insignificant for US and positive

only for Singapore. The study has also examined abnormal returns for firms

segregated on the basis of age, size of total assets and industry. No significant results

have been obtained for industry classification. On the basis of age, only growth

companies have shown positive returns, expansion and mature companies have

registered losses for shareholders. With respect to size of assets, large size companies

have witnessed greater losses than smaller ones. Overall, this provides evidence that

shareholders wealth does not increase when Indian companies tap international stock

exchanges for raising finance.

Keywords: Cross listing; Global depository receipts; American depository receipts;

Cumulative average abnormal returns

iii

CERTIFICATE

This is to certify that the project titled, “Cross Listing and Value Creation: An

Empirical Study in Indian Context”, submitted in partial fulfilment of the

requirements for the award of the degree of Master of Business Administration

from I.I.T. Delhi, by Harshita (2016 SMF 6507) is a bona fide and original record of

her work carried out by her under my supervision and guidance. The matter has not

been submitted anywhere for the award of any Degree or Diploma.

Prof. P.K. Jain Dr. Smita Kashiramka

Department of Management Studies Department of Management Studies

Indian Institute of Technology, Delhi Indian Institute of Technology, Delhi

CONTENTS

Contents Page No.

Acknowledgement .......................................................................................................... i

Abstract ........................................................................................................................ ii

Certificate .................................................................................................................. iii

List of Tables ................................................................................................................ v

List of Figures ............................................................................................................vii

Abbreviations ........................................................................................................... viii

Chapter 1: Introduction to the Study .....................................................................1

Chapter 2: Literature Survey .................................................................................3

Chapter 3: Research Methodology ........................................................................9

Chapter 4: Impact of Cross Listing on Shareholders’ Wealth ..........................13

Chapter 5: Effect of Cross Listing: Dis-aggregative Analysis ..........................25

Chapter 6: Concluding Observations ..................................................................34

References .................................................................................................................37

Annexure ....................................................................................................................40

LIST OF TABLES

Table No. Particulars Page No.

Table 3.1 List of independent variables used for regression ...................................12

Table 4.1 Description of dataset by number of stocks listed in different

host markets for the period 1997 till present ...........................................16

Table 4.2 Price reaction around cross listing announcement for the period

1997-2017 ................................................................................................17

Table 4.3 CAAR for pre-recession, during recession and post-recession

for multiple event windows .....................................................................18

Table 4.4 Results of regression for different event windows for 146 firms

for the period 1997-2017 .........................................................................20

Table 4.5 CAAR by host markets for different event windows for the

period 1997-2017 .....................................................................................21

Table 4.6 Regression results for different host markets for multiple event

windows for the period 1995-2017 ..........................................................22

Table 5.1 Age based segregation of 146 companies under study for the

period 1997-2017 .....................................................................................26

Table 5.2 Cumulative average abnormal returns for 146 Indian firms,

segregated on the basis of age, for the period 1997-2017 .......................26

Table 5.3 Regression results for Growth, Expansion and mature

companies for the period 1997-2017 .......................................................27

Table 5.4 Size based segregation of 146 companies under study for the

period 1997-2017 .....................................................................................29

Table 5.5 CAAR for small, medium and large companies for different

event windows for the period 1995-2017 ................................................29

Table 5.6 Regression results for small, medium and large size companies

for the period 1997-2017 .........................................................................30

Table No. Particulars Page No.

Table 5.7 Number of companies according to various industries ...........................31

Table 5.8 CAAR for Consumer goods, IT and Telecom and Industrial and

Manufacturing for the period 1997-2017 ................................................31

Table 5.9 Regression results according to different industries for the

period 1997-2017 .....................................................................................32

Table A.1 List of ADR/ GDR for the period 1992-2017 ........................................40

vii

LIST OF FIGURES

Figure No. Particulars Page No.

Figure 4.1 Number of first international cross listing by Indian

companies for the period 1992-2017 ....................................................14

Figure 4.2 Number of ADR/ GDR issues by Indian companies for the

period 1992-2017 ..................................................................................14

Figure 4.3 Number of international cross listing on various stock

exchanges for the period 1992-2017 .....................................................15

viii

ABBREVIATIONS

ADR - American Depository Receipt

BSE - Bombay Stock Exchange

CAAR - Cumulative Average Abnormal Returns

CAGR - Compounded Annual Growth Rate

CAR - Cumulative Abnormal Returns

DR - Depository Receipt

GDR - Global Depository Receipt

NSE - National Stock Exchange

SEBI - Securities and Exchange Board of India

SEC - Securities and Exchange Commission

CHAPTER 1

INTRODUCTION TO THE STUDY

1.1 INTRODUCTION

With globalisation, companies got an opportunity to expand their wings beyond their

local boundaries. The various functions in an organisation like marketing, operations,

research and development, all witnessed an international exposure. This global

presence also percolated to the function of finance, introducing the international

markets as a source of raising funds. One of the most popular ways to tap global

equity markets is a depository receipt. It is a financial instrument that represents a

foreign company‟s publicly traded securities.

Issue of Depository receipts (DRs) is highly beneficial for the company. DRs help

companies get access to foreign capital markets. This enhances the global presence of

the company and helps in getting international attention and coverage. DRs can

significantly increase the visibility and public profile of companies located in foreign

countries that do not ordinarily garner much attention from investors. International

exposure also helps firms in rapid growth and development. DRs also increase the

shareholder base of the company.

For the investors too, DRs offer several benefits. The use of DRs provide investors

with the ability to invest in a foreign company (with least concerns) about foreign

trading practices, differences in tax laws or transactions occurring across borders.

DRs also help an investor diversify his portfolio and offers opportunities to benefit

from trends and developments outside the home country.

As a part of globalising strategy, Indian government had initiated 2 major steps –

allowed FII to invest in India and permitted Indian companies to float their stocks in

foreign markets.

However, despite the known benefits of cross listing, firms stay apprehensive of this

strategy; a select list of plausible reasons is as follows:

a. It is a costly affair to fulfil all disclosure requirements.

b. It becomes difficult to deal with volatility spill-overs that arise from international

trading

c. It is an imperative to ensure that foreigners do not get controlling interest in the

company

In view of the above, the study aims to find out if companies have any substantial

gains associated with cross listing and identify these gains.

1.2 OBJECTIVES OF THE STUDY

1.To assess the relationship between international cross listing and shareholders‟

wealth

2.To identify the plausible determinants of value creation at the time of cross

listing

3.To conduct dis-aggregative analysis based on industrial classification, size and

age of the firms

For better exposition, the rest of the report is segregated into chapters. Chapter 2 deals

with literature review and identification of research gaps. Chapter 3 details the

research methodology, the research design, scope, variables and tests employed.

Chapter 4 covers the results and findings of the impact of cross listing on value

creation. Chapter 5 gives a detailed analysis of value creation to shareholders after

segregating companies based on age, size and industry. Chapter 6 provides the

concluding observations.

CHAPTER 2

LITERATURE SURVEY

This chapter provides a brief summary of the important research papers and articles

related to ADR/ GDR analysed for conducting the present study. This analysis has

also helped identify several gaps in the research done so far on the subject.

2.1 LITERATURE REVIEW

Foerster and Karolyi (1999) studied how the stock price performed at the time of

cross listing on non-US stocks in the US markets. Their sample consisted of 153 firms

from countries of Europe, Canada and Asia Pacific region that were cross-listing for

the first time on US exchanges from 1976 to 1992. Cumulative abnormal returns

calculated for the event window (-100, +250) show that abnormal returns of 19% are

present during the year before the cross listing. During the week of cross listing

shareholders have earned additional return of 1.2%. But for the year following the

cross listing, shareholders‟ wealth has decreased by 14%. The study also highlights

the impact of cross listing on risk level of the firm. The home market risk declines

after the cross-listing event, as suggested by the decrease in the home market beta

from 1.03 to 0.74 on average, while the global level risk remains unchanged. They

also test the significance of traditional hypothesis in explaining the abnormal returns

generated to shareholders. The results support investor recognition and market

segmentation to be significant reasons for value creation. Empirical results also show

that the decline in abnormal returns in the year after the cross listing is mitigated for

companies that raise capital at the same time.

Miller (1999) analysed impact of international dual listing on the stock price. During

a 10-year study period, from 1985-1995, they studied the first depository receipt issue

by 181 firms from 35 countries. They used event study methodology to assess

changes in the value of the share at the time of announcement of the cross listing. It

was observed that the positive abnormal returns generated around the announcement

date were larger in magnitude as compared to results reported previously. Results also

suggested that US exchanges produced highest abnormal returns. This result

highlights while direct barriers may be weak in causing market segmentation, barriers

like low investor protection and recognition and illiquidity segment capital markets,

hence leading to significant differences in stock price reaction. The study also

provides for detailed analysis for public and private issue. There is positive effect on

shareholder wealth in a public offering by foreign companies in the US. Private

offering, however, has witnessed a negative impact of wealth of shareholders. The

results show that cross listing removes barriers to capital flow and helps increase

share value and reducing the cost of capital.

Bancel and Mittoo (2001) studied a sample of 305 firms from France, Italy,

Switzerland, Germany, Netherlands, UK that cross listed on foreign exchanges to

determine the net benefits from foreign listing. They noted that the perceived net

benefits of foreign listing will vary across firms. By collecting data from managers of

different companies using a questionnaire, they observed that 60% of managers

perceived benefits of cross listing outweigh the cost and 30% of the managers feel the

opposite. The managers cited the main benefits of foreign listing as increased

liquidity, increased trading volume and higher financial disclosure level of firms.

They also studied the perception of European and Canadian managers in depth and

found significant differences in the benefits and costs perceived by both groups,

which could be indicative of differences in corporate practices and culture.

According to the European managers, the major benefits were increased visibility and

an increased shareholder base. Canadian managers, however, perceived increased

liquidity to be the most important benefit from cross listing. Similarly, differences

were found in the perceived costs. For European managers, public relations costs were

most important, whereas for Canadian managers, it was Securities and Exchange

Commission (SEC) disclosure requirements. Majority of the managers in the sample

cited that cross listing was part of their globalisation strategy.

Sarkissian and Schill (2004) examined the destination preferences of firms at the time of

cross listing. Using a comprehensive database of 2251 listing across 25 host markets from

44 home markets, they studied the population of cross listing as of 1998. They analysed

both country specific and firm specific determinants that affect cross listing and concluded

that proximity in terms of geography, culture, economy and industry were significant

factors in deciding the destination market for cross listing. These proximity factors help

increase information for the investor and provide psychological tolerance even for the

foreign investors. Unfamiliarity of the host market leads to psychological intolerance as

well as produces unavailability of information. Hence, it is not preferred by firms. They

observed that considerations around investor diversification were not significantly

important in deciding the host market, but higher return correlation did influence the

decision of firms to choose the host market. Other important determinants include, market

capitalisation and a conducive tax environment. Proximity and cross-country familiarity

were significant variables.

Roosenboom and Dijk (2009) examined different destination markets response to cross

listing. They studied 526 cross listing instances from 44 countries during the period 1982-

2002. They employed the standard event study methodology to assess how stock prices

behave at the earliest public announcement of cross listing. They used an event window of

250 trading days around the event under consideration. Results have been calculated using

a two factor model for both the domestic and world markets. Focussing on 8 major stock

exchanges, they reported abnormal returns of 1.3% for US exchanges, 1.1% for London

stock exchange, 0.6% for exchanges in continental Europe and 0.5% for Tokyo exchange.

Thus they concluded that destination markets played an important role in valuation effects

at the time of cross listing with developed markets generating more returns for the

shareholders. The study also focussed on analysing how different value creation

explanations vary across destination markets. In US, legal protection and investor

recognition have proved to be significant whereas in London, market segmentation and

investor recognition have been identified as significant in explaining value creation. The

empirical results for Tokyo and continental Europe is mixed.

In an IMF Working Paper (2009) 48 companies in the sub-saharan African region

were studied that have cross listed in the period 1992-2008. Using an event study

methodology, the study observed that cross listing generated positive price reaction

around the date of regional cross listing. Contrary to the results obtained by other

studies, even the post-cross listing results were normal. The study concluded that

cross listing has a positive effect on firm value and this result should be considered by

authorities to boost stock market development. Numerous benefits associated with

cross listing can be obtained if right policies are designed both in the home and host

market for conducive mechanism for firms to cross list.

Abdallah and Ioannidis (2010) studied 1165 firms from 47 countries that cross listed

on US equity exchanges in the period 1976-2007. They noted that firms cross listed at a

time when they could take advantage of overvalued share prices in their domestic

market. While abnormal returns existed at the time of cross listing, they subsequently

declined. This decline in post-listing abnormal return was higher for firms with higher

pre-listing abnormal returns. This decline was also higher for companies that had higher

Tobin‟s-Q in the pre-listing period. Results also show that the risk level reduced as

depicted by the local home market beta. But, this decrease in the risk level also

diminished over time. The global beta remained unchanged for most of the period under

study, except for the period 2001-2007 when there was a decline in the global risk level

for the firms undertaking cross listing. Also, the regression test for investor protection

associated with abnormal returns shows no significant association between the

cumulative abnormal returns generated post cross listing and the measures of investor

protection – accounting standards index, anti-director rights index and rule of law index.

The study also involved robustness check for the results and are unaffected by outliers.

Dodd and Louca (2012) employed the event study methodology to evaluate the

relationship between cross listing at an international location and shareholders‟ wealth.

With a sample size of 254 cross listing instances over the period 1982-2007, the study

concentrated on cross listing by European companies on US, UK and other European

exchanges. The abnormal returns calculated in the event window of 10 days around the

announcement date suggest that cross listing yields positive price reaction. However, in

their research, this result holds true only for US and UK exchanges. For the other

European exchanges, no such empirical affirmation has been obtained. The study also

investigated the effect on shareholders‟ wealth due to certain specific events. It was

found that the introduction of Sarbanes Oxley Act decreased the valuation gain of US

cross listing. No empirical evidence could be obtained to show the reduced benefits of

cross listing with the introduction of Euro. The study also evaluated the significance of

various traditional theories that seek to explain wealth effects of value creation. They test

the theories of market segmentation, legal bonding, investor recognition, liquidity,

proximity preference, business strategy and market timing after incorporating the impact

of introduction of Euro and Sarbanes Oxley Act and find that these theories are

significant in explaining wealth creation for the shareholders.

Ghadhab and Hellara (2016) used the event study methodology to find the impact first

cross listing and subsequent cross listings have on firm value. Covering 303 firms from 33

countries, they studied an extensive sample of 499 foreign listings spread across 1980-

2013. They focussed on cross listings on exchanges of US, UK, other major European

markets, Tokyo and Australia. Using an event window of 60 months around the date of

cross listing, they measured cumulative abnormal returns. Their findings suggest that only

the first three listings helps to enhance firm value. Additional cross listing decreased the

shareholders‟ wealth. They also conducted a deeper analysis for the US and UK exchanges

and noted that UK exchanges proved to be most conducive for highest gain in

shareholders‟ wealth for the pre-listing period, while valuation gain in post-listing period

was maximum in US exchanges. They also conducted regression analysis to test

traditional explanations of value creation. Their results show that standard concerns around

legal environment and proximity preference (culture and geography) failed to explain the

valuation gain to shareholders‟ at the time of cross listing. However, they show that

information efficiency associated with cross listing improves stock price informativeness,

which is a significant variable for valuation gain.

2.2 RESEARCH GAPS

On the basis of the review of literature, the following gaps have been identified:

1. Till date, very few studies have been conducted for Indian companies issuing

depository receipts in America and the other parts of the world.

2. Only the traditional explanations for value creation to shareholders have been

studied in the literature. Various other firm specific and country specific variables

can also be plausible determinants for explaining wealth creation for shareholders

that have not been considered.

3. In the sample, all the firms are treated as a group, irrespective of their differences

in industry, scale of operation, number of years of operation etc. Segmentation has

not been done to see differences in groups.

CHAPTER 3

RESEARCH METHODOLOGY

The objective of this chapter is to describe the scope, research design and variables

employed in the study. It also describes the methodology used to estimate the

abnormal returns due to cross listing. It then covers the regression model used to

assess the determinants of value creation to shareholders.

3.1 DATASET

The total population of first instances of international cross listing consists of 146

companies. However, due to unavailability of data, the study involves 146 Indian

companies, that have undertaken ADR/ GDR/ ADS/ GDS from April 1, 1992 to 31 st

December 2017. Only the first international cross listing has been considered; in other

words, subsequent cross listings have been excluded.

Data Source and Software

The list of Depository Receipt issues has been taken from PRIME Database. Event

study metrics has been used to calculate the abnormal returns.

3.2 RESEARCH DESIGN

3.2.1 Event Study

An event study measures the impact of a specific event on the value of a firm using

financial market data. Using this method, it can be assessed whether there is an

abnormal stock price effect related to an unanticipated event. From this, the

importance of the event can be assessed.

To assess the impact of cross-listing on value creation for shareholders, cumulative

abnormal returns over multiple event windows around the date of announcement of

cross listing have been calculated using the Market Model. In this study, semi-strong

form of Efficient Market Hypothesis (EMH) is employed which states that any new

information that is communicated to the public about the firms is immediately

reflected in the stock prices. Hence the stock price will adjust quickly to indicate the

change in the future expected discounted cash flow of the firm

Hypothesis Development

Null Hypothesis: Announcement of cross listing does not lead to abnormal returns;

CAAR is statistically zero.

H0 = CAAR = 0

Alternate Hypothesis: Announcement of cross listing does produce abnormal returns;

CAAR is statistically different from zero.

H1 = CAAR ≠ 0

Estimation Window

An estimation window of 180 days has been considered to estimate the coefficients.

Event Window

Multiple event windows have been considered including (-5, +5), (-3, +3), (-1, +1),

(0, 0), (-5, -1), (-3, -1), (1, 3) and (1, 5).

Abnormal returns are defined as per equation 3.1 using the Market Model:

ARit = Rit – E( Rit) (3.1)

Where

ARit = Abnormal returns of company i at time t

E(Rit )= Expected return on firm i at time t

E(Rit ) = αi + βi (Rmt) + εit (3.2)

With E (εit = 0) and var (εit ) = σ 2

Where

E(Rit )= Expected return on firm i at time t

αi = Ordinary Least Square (OLS) estimate of the Intercept of straight line or alpha

coefficient of security „i‟

βi = Ordinary Least Square (OLS) estimate of the coefficient of BSE 200

Rmt= Actual return on the market index, BSE 200

εit = Error term with mean zero and constant variance at time t

Cumulative abnormal returns (CARs) are the summation of the abnormal returns

generated by the stock over the event window and are determined as per equation 3.2

CARi = ∑ARit (3.3)

Where CARi is the cumulative abnormal return for firm i over the event window.

The returns are then averaged to obtain the Cumulative average abnormal returns

(CAAR).

3.2.2 Regression Model

The regression model tests the various explanatory variables to explain significant

influencers of wealth creation for shareholders at the time of value creation.

Null Hypothesis: There is no statistically significant influence of the independent

variables on the CAAR

Alternate Hypothesis: There is a statistically significant influence of the independent

variables on the CAAR

Table 3.1 provides a list of independent variables used in the study

Table 3.1: List of independent variables used for regression

Variable Description Source

Firm specific factors

Sales growth Three year growth rate of total sales of the

company ACE Equity

Market related factors

Market capitalisation to

GDP

Log of the absolute difference between home

and host country ratios

Global Financial

Development, World

Bank

Macro-economic factors

Political risk rating Measuring perceptions of likelihood of political

instability or politically motivated violence

World Governance

Indicators

Financial Freedom

Measures banking efficiency and independence

from government control and interference in the

financial sector

Heritage Foundation

Business Freedom

Measures extent to which regulatory and

infrastructure environments constrain the

efficient operation of business

Heritage Foundation

Market timing

Recession December 2007 – June 2009; dummy variable

NBER's Business

Cycle Dating

Procedure

Proximity factors

Cultural distance Country scores for dimensions of culture Hofstede‟s cultural

dimensions

Geographical distance Log of geographical distance between the home

and host countries CEPII database

Regression Equation

CARi = α + β1 (CAGR) + β2 (Financial Leverage) + β3 (Market cap to GDP) + β4

(Political risk rating) + β5 (Financial freedom) + β6 (Business freedom) + β7

(Recession) + β8 (Culture) + β9 (Geography) + εi (3.4)

The regression equation used in the study is defined as per equation 3.4

CHAPTER 4

RESULTS AND FINDINGS: IMPACT OF CROSS LISTING

ON SHAREHOLDERS’ WEALTH

This objective of this chapter is to provide a detailed description of the dataset used in

the study. For better exposition, the subject matter of the chapter is divided into two

sections. Section one deals with description of the dataset used in the study. Section

two describes the results and findings for the abnormal returns generated around the

date of announcement of cross listing and the various determinants that explain the

abnormal returns.

4.1 DESCRIPTION OF DATASET

From the period of January 1, 1992 till December 31, 2017, there have been 336

instances of international cross listing by Indian companies. Out of these 262 relate to

the first international cross listing and the remaining 74 are cases of subsequent cross

listings in other international markets.

The scope of the present study is limited to all instances of first international cross

listings by Indian companies.

The graph (depicted in Figure 4.1) shows the number of first cross listings till date.

The trend shows that there was a sharp increase in the number of cross listings in the

year 1994, followed by a sudden dip for the next decade. However, in the years

preceding the recession, the cross listings again took a sharp increase. This decreased

in the years after the recession.

Figure 4.1: Number of first international cross listing by Indian companies for the

period 1992-2017

Figure 4.2 highlights the split between the Global Depository Receipts and the

American Depository receipts in the first cross listing. The preference for GDRs as

the first international destination for the Indian stocks far exceeds the preference for

ADRs. The year-wise split is exhibited in Figure 4.2.

Figure 4.2: Number of ADR/ GDR issues by Indian companies for the period 1992-2017

1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

N u

m b

e r

o f

co m

p a

n ie

Years

1 9 9

2 0 0

2 0 1

N u

m b

e r o

f c o

m p

a n

ie s

Years

GDR ADR

The graph depicted in Figure 4.3 shows the trend of cross listing across different stock

exchanges. Luxembourg stock exchange has consistently been the preferred stock

exchange for cross listing by Indian companies. This is followed by London stock

exchange and finally by Singapore.

F ig

u r e 4

.3 :

N u

m b

e r o

f in

te r n

a ti

o n

a l

c r o ss

l is

ti n

g o

n v

a r io

u s

st o c k

e x c h

a n

g e s

fo r t

h e p

e r io

d 1

9 9

2 -2

0 1

The study aims to analyse the returns generated by international cross listing based on

the entire population of 262 companies. However, constrained by the availability of

data, this study analyses 146 companies.

Table 4.1 highlights the year-wise distribution for the companies under study.

Table 4.1: Description of dataset by number of stocks listed in different host markets for

the period 1997 till present

Year Luxembourg London NYSE NASDAQ Singapore Dubai Total

1997 0 2 0 0 0 0 2

1998 0 0 0 0 0 0 0

1999 0 1 1 1 0 0 3

2000 1 1 3 0 0 0 5

2001 1 0 1 0 0 0 2

2002 1 0 0 0 0 0 1

2003 4 0 0 0 0 0 4

2004 5 2 0 0 0 0 7

2005 20 4 0 0 0 0 24

2006 19 3 0 0 0 2 24

2007 9 1 1 0 5 0 16

2008 8 0 0 0 2 0 10

2009 10 2 0 0 1 0 13

2010 19 0 0 0 1 0 20

2011 11 0 0 0 0 0 11

2012 2 0 0 0 0 0 2

2013 2 0 0 0 0 0 2

Total 112 16 6 1 9 2 146

4.2 EMPIRICAL EVIDENCE

4.2.1 The effects of cross listing on shareholders’ wealth

The study estimates the effects of cross listing on shareholder‟s wealth using

Cumulative average abnormal returns (CAAR) around the date of announcement of

cross listing in the international market.

Table 4.2 details the cumulative abnormal returns around the date of announcement of

cross listing for 146 cross listing announcement events during the period 1997-2017.

Table 4.2: Price reaction around cross listing announcement for the period 1997-2017

Event

Window CAAR

Parametric tests Non-Parametric tests

T test Patell Test Corrado

Rank Test Sign Test

(-5, +5) 0.0074 0.4645 -0.9193 0.2113 -0.4840

(-3, +3) -0.0118 -0.9296 -2.1397* -1.0976 -1.6721**

(-1, +1) -0.0067 -0.8076 -1.2883 0.6318 -0.4840

(0, 0) 0.0032 0.6751 0.5758 0.4902 -0.6537

(-5, -1) 0.0267 2.4872* 2.4998* 1.5756 1.3831

(-3, -1) 0.0002 0.0290 -1.1220 -0.2917 -0.4840

(1, 3) -0.0153 -1.8388** -2.4789* -1.6680** -1.1629

(1, 5) -0.0226 -2.1002* -4.1209* -1.4814 -1.8418**

* indicates significance at 5%

**indicates significance at 10%

The results in Table 4.2 show that market performance is not favourable around the

date of announcement of cross listing. Relevant data shows that shareholders are

likely to have significant negative abnormal returns of -1.18% in the event window of

(-3, +3) (Significant at 5%). The negative returns around the date of announcement

might be the result of a pessimistic market perception regarding added risks

associated with DRs like currency risk, impact of economic and political problems of

host country and asymmetric information.

In the pre-announcement period (-5, -1), it appears that shareholders witness

significant positive abnormal returns of 2.67% (Significant at 5%) but the post-

announcement period is likely to result in significant losses to the extent of 1.53% and

2.26% in the event windows of (1,3) and (1,5) respectively. The possible reason for

the positive pre-announcement returns turning negative after the announcement of

cross listing could be that investors tend to be over-pessimistic regarding the risks and

probable problems associated with the company going international.

Cumulative average abnormal returns pre and post-recession

The period under study, 1997-2017, witnessed the Global Recession, which shook the

capital markets around the world. For better understanding of the wealth effects of

cross listing, the period under study has been segregated into pre-recession, during

recession and post-recession. The recession phase has been identified by National

Bureau of Economic Research‟s Cycle Dating Procedure as the time period from

December 2007 to June 2009.

Table 4.3: CAAR for pre-recession, during recession and post-recession for multiple

event windows

Event Window CAAR

Pre-recession During recession Post-recession

(-5, +5) -0.0269* 0.0131 0.0618*

(-3, +3) -0.0405* -0.0048 0.0329

(-1, +1) -0.0230* 0.0087 0.0150

(0, 0) -0.0011 -0.0008 0.0117*

(-5, -1) 0.0210 0.0605* 0.0255**

(-3, -1) -0.0114 0.0320 0.0092**

(1, 3) -0.0280* -0.0360** 0.0121

(1, 5) -0.0468* -0.0466* 0.0247

* indicates significance at 5%

**indicates significance at 10%

It follows from Table 4.3 that cumulative average abnormal returns in the pre-

recession period (Up to November 2007) were significantly negative. Similar trend

has been observed in the period during recession (December 2007 – June 2009). Data

shows returns to shareholders were negative and as high as 4.6% in the period

following the cross listing.

However, from July 2009 (Post-recession period), wealth effects for shareholders

have been observed to be positive, generating returns as high as 6% in the (-5,+5)

event window. The recession created an apprehensive atmosphere in the financial

markets. A cross listing event in such gloomy times might have generated favourable

sentiments among investors regarding expected performance and growth of the

company. This can be a possible explanation of the positive abnormal returns

generated in the post-recession period.

The data, thus, supports that effects of cross listing for shareholders vary over time.

4.2.2 Determinants of wealth effects of cross listing

This section analyses the possible determinants of value creation for shareholders due

to cross listing. Table 4.4 reports regression results on the effect that the independent

variables have on the CAAR.

Table 4.4: Results of regression for different event windows for 146 firms for the period

1997-2017

Independent

variable

Event Window

(-5,+5) (-3,+3) (-1,+1) (0,0)

Coef. T statistic Coef. T statistic Coef. T statistic Coef. T statistic

CAGR 0.000119 0.005894 0.011515 0.569819 0.008743 0.477789 0.001717 0.335262

Financial

Leverage -0.00127 -0.15447 -0.01778 -2.16386* -0.01088 -1.46188 0.000663 0.318158

Market cap

to GDP -0.04855 -0.38827 0.185621 1.480929 0.116183 1.023606 -0.0029 -0.0912

Political risk

rating 0.003778 1.073253 -0.0047 -1.33087 -0.00449 -1.40577 0.000336 0.375555

Financial

freedom -0.0009 -0.43268 0.000494 0.238178 0.000862 0.458803 -0.00044 -0.84276

Business

freedom 0.000112 0.063763 -0.00291

1.65543** -0.00257 -1.61258 0.003 0.069236

Recession -0.00092 -0.01463 0.01536 0.242931 0.034094 0.595464 -0.01421 -0.8868

Culture 0.196704 1.041336 -0.16736 -0.88386 -0.17884 -1.04303 -0.0265 -0.00054

Geography -0.34472 -1.2547 0.138645 0.503423 0.224252 0.899181 0.0296 0.42399

R 2 0.027035482 0.064588 0.036758 0.026912

* indicates significance at 5%, **indicates significance at 10%

The Table reports coefficients of the regression model, run for 146 instances of

international cross listing undertaken by Indian companies during the period 1997-

2017. The explanatory power of the model (as shown by R 2 ) is poor for all event

windows. Findings indicate that financial leverage and business freedom have a

negatively significant relation with abnormal returns.

Leverage has a negative effect on abnormal returns generated around cross listing.

The various risks associated with higher leverage may be the reason investors prefer

low-levered firms.

A surprising observation is that higher business freedom in home and host country

produces lower wealth benefits for shareholders. Regulatory freedom is believed to be

an important aspect of financial market return, but the results produce a negative

coefficient of business freedom which shows that market performance improves with

higher government regulations. Regulations in the form of higher transparency and

disclosures might build confidence among investors, thus generating positive returns.

4.2.3 Cumulative average abnormal returns by host market

The determinants of wealth creation due to cross listing may vary across the different

host markets. Hence, combining all the cross-listing instances in one model might

weaken the regression model and create spurious relations. The following tables

(Table 4.5 and 4.6) highlight the results according to various host markets. Table 4.5

reports cumulative abnormal returns by the 4 major host markets – Luxembourg,

London, United States and Singapore.

Table 4.5: CAAR by host markets for different event windows for the period 1997-2017

Event Window

CAAR

Luxembourg London United States Singapore

(-5, +5) 0.0101 -0.0260* 0.0277 0.0146

(-3, +3) -0.0118* -0.0290* 0.0011 0.0084

(-1, +1) -0.0083 -0.0193* 0.0360 0.0017

(0, 0) 0.0038 -0.0087** 0.0215 0.0024

(-5, -1) 0.0262* -0.0034 0.0678 0.0542*

(-3, -1) -0.0011 -0.0111 0.0145 0.0277**

(1, 3) -0.0144* -0.0091 -0.0350 -0.0218

(1, 5) -0.0199* -0.0139 -0.0616 -0.0421**

* indicates significance at 5%; **indicates significance at 10%

Table 4.6: Regression results for different host markets for multiple event windows for

the period 1997-2017 E

V E

N T

W IN

D O

(- 1 , +

1 )

S in

g a p

o r e

0 .0

6 9 * *

0 .3

0 5 * *

0 .0

0 0 4

-0 .0

9 2 8

0 .0

1 5 * *

-0 .0

1 1 9

0 .5

8 5 * *

0 .0

0 0 4

0 .0

0 1 5

U n

it e d

S ta

te s

0 .0

4 6 5

-0 .0

0 2 9

0 .0

0 4 8

0 .1

5 8 9

0 .0

9 7 7

1 .1

1 7 1

0 .0

0 7 8

0 .0

0 0 3

0 .0

0 3 5

L o n

d o n

-0 .0

0 2 4

-0 .0

0 1 9

-1 .0

6 8 9

0 .0

0 9 5

0 .0

4 4 1

-0 .1

6 8 0

-0 .1

5 9 7

6 .2

4 6 4

0 .0

0 7 1

L u

-0 .0

3 0 1

-0 .0

1 2 2

0 .2

9 9 4

-0 .0

1 * *

0 .0

0 5 3

-0 .0

4 * *

0 .1

0 0 6

0 .0

0 2 3

0 .0

0 0 9

(- 3 , +

3 )

S in

g a p

o r e

0 .0

6 1 2

0 .6

3 4 8

0 .0

0 5 9

-0 .0

9 8 0

0 .0

1 7 0

-0 .0

3 8 3

1 .2

1 4 * *

0 .0

0 0 9

0 .0

0 5 8

U n

it e d

S ta

te s

-0 .4

2 3

-0 .0

1 4

0 .0

0 0 8

0 .0

0 9 8

0 .0

0 4 6

0 .0

8 6 5

0 .0

6 0 5

0 .0

2 5 9

0 .0

0 4 8

L o n

d o n

0 .4

0 7 9

-0 .0

0 2 1

-0 .9

0 3 9

0 .0

0 9 3

0 .0

0 8 8

-0 .0

4 8 4

-0 .4

8 * *

2 .3

7 3 2

0 .0

5 0 7

L u

-0 .0

3 2

-0 .0

2 2 *

0 .3

7 9 * *

-0 .0

1 1 5

0 .0

0 4 5

-0 .0

4 * *

0 .0

6 9 6

0 .0

0 6 5

0 .0

0 0 1

(- 5 , +

5 )

S in

g a p

o r e

0 .1

1 8 8

1 .0

6 2 * *

0 .0

1 0 0

-0 .1

8 9 6

0 .0

2 5 5

-0 .0

5 7 * *

1 .8

8 6 * *

0 .0

0 8 7

0 .0

1 1 4

U n

it e d

S ta

te s

-0 .2

8 1 2

-0 .0

2 2

0 .0

5 8 7

-0 .0

5 7

-0 .0

4 1 6

-0 .3

0 3 9

0 .0

3 9 8

0 .0

1 4

0 .0

3 0 5

L o n

d o n

0 .4

7 4 8

0 .0

0 7 6

-1 .7

2 7 7

0 .0

1 8 2

0 .0

4 2 2

-0 .2

0 6 6

-0 .5

1 2 3

8 .8

6 6 8

0 .0

0 2 0 9

L u

-0 .0

2 6 0

0 .0

0 2 4

-0 .0

2 1 0

0 .0

1 2 2

0 .0

0 1 8

0 .0

0 1 0

-0 .0

2 4 0

0 .0

9 1 3

0 .0

0 1 7

IN D

E P

E N

V A

R IA

B L

C A

G R

F in

a n

c ia

L e v e r a g e

M a r k

e t

c a p

to G

D P

P o li ti

c a l r is

ta k

in g

F in

a n

c ia

fr e e d

o m

B u

si n

e ss

fr e e d

o m

R e c e ss

io n

C u

lt u

r e

G e o g r a p

h y

* indicates significance at 5%; **indicates significance at 10%

Luxembourg

The analysis indicates that on an average, cross listing event by Indian companies on

the Luxembourg stock exchange results in significant negative market reaction of

1.18% in the event window of (-3, +3). The positive abnormal returns in the pre-

announcement period (2.62%, significant at 5%), turn into losses in the post-

announcement period (1.44% in the event window (1,3) and 1.99% in the event window

(1,5), significant at 5%).

The explanatory power of the regression model has increased for all event windows,

specially (-3, +3), an increase from 2.7% to 24%. Results show that financial

leverage, political risk taking, business freedom have a significant but a negative

impact on shareholders‟ wealth due to cross-listing. Findings also provide evidence

that Market capitalisation to GDP is a positively significant determinant of wealth

creation (Significant at 10%).

London

Relevant data shows that cross listing produces significantly negative abnormal

returns on London stock exchange. The losses are as high as 2.60% in the (5,5) event

window, but gradually lower to 1.93% in the (1,1) event window.

In the context of cross listing on London stock exchange, it has been observed that

recession has a negative relation with the effects of cross listing on shareholders‟

wealth (significant at 10%). During the period of recession (December 2007 – June

2009), abnormal returns have been negative due to apprehensive market sentiments.

United States

On the stock exchanges in the Unites States (both NYSE and NASDAQ) the results

show insignificant market reaction to the event of cross listing.

The analysis is revealing in that it indicates that no variable has a significant impact

on the abnormal returns.

Singapore

The results indicate that for cross listing done on Singapore stock exchange, the

significant positive returns in the pre-announcement period (up to 5%) become losses

for shareholders in the post-announcement period (4%).

Relevant data shows that for the event window (-1,1), CAGR, financial leverage,

financial freedom and recession play a positive and significant role. With higher

Compounded annual growth rate, growth opportunity is higher, thus resulting in

enhanced wealth benefits for shareholders. The positive impact of financial freedom

on abnormal returns is also consistent with theoretical background that independence

from government control leads to better market performance. However, according to

results, recession is also a positive and significant influencer of abnormal returns,

which implies higher returns during the period of recession. This finding is

contradictory to popular belief.

Summary

In sum, wealth effects of cross listing vary across host markets and over time.

Evidence provides that different explanatory variables explain the value creation to

shareholders; these reasons vary across different host markets.

CHAPTER 5

EFFECT OF CROSS LISTING:

DIS-AGGREGATIVE ANALYSIS

This chapter covers the abnormal returns and their possible determinants according to

specific groups created on the basis on age, size of total assets and industry

classification.

5.1 DIS-AGGREGATION OF DATA

The dataset covers 146 instances of international cross listing by Indian companies for

the period 1992-2017. But these companies vary across industries, with different scale

and scope of operations. Therefore, by analysing them as one group, the specific

features about their group may not be captured. Thus, for better assessment, a dis-

aggregative analysis has been undertaken by forming clusters based on three

parameters, age, size of total assets and industry classification.

5.2 AGE

Companies pass through various stages in their business lifecycle. One way to

identify the current stage of a company is based on its age. Consequently, the quartile

function has been used to segregate the companies under study into 4 quartiles, Q1,

Q2, Q3 and Q4.

The age profile of the companies under study ranges from 1 year to 102 years.

According quartiles created are presented in Table 5.1.

Table 5.1 Age based segregation of 146 companies under study for the period 1997-2017

Classification Age range (in years) Quartiles Number of companies

Growth 1-13 Q1 42

Expansion 14-23 Q2, Q3 68

Mature 24 and above Q4 36

Quartile 1 consists of companies with an age range of 1-13 years. These are growth

companies that are focussing on rapidly scaling up operations. Expansion companies

have been identified as part of Quartile 2 (14-18 years) and Quartile 3 (19-23 years).

These are companies that have set up a foundation for their businesses and are now

looking at expansion activities. The age range for expansion companies is 14-23

years. Lastly, companies with age 24 years or more, falling under Quartile 4, are

identified as Mature companies.

Table 5.2: Cumulative abnormal returns for 146 Indian firms, segregated on the basis

of age, for the period 1997-2017

Event Window

CAAR

Growth Expansion Mature

(-5, +5) 0.0100 0.0181 -0.0160*

(-3, +3) -0.0007 -0.0204* -0.0085**

(-1, +1) 0.0148** -0.0200* -0.0066

(0, 0) 0.0076 0.0072 -0.0096*

* indicates significance at 5%; **indicates significance at 10%

Table 5.3: Regression results for Growth, Expansion and mature companies for

the period 1997-2017

E V

E N

T W

I N

D O

(- 1

, +

1 )

M a

tu r e

-0 .0

2 8

5 1

-0 .0

0 7

1 4

-0 .1

1 8

3 3

0 .0

0 1

6 5

-0 .0

0 0

3 3

0 .0

3 9

0 .0

1 9

2 4

-0 .0

1 6

3 4

0 .0

7 1

6 6

E x

p a

n s io

0 .0

2 3

4 3

-0 .0

1 6

2 2

0 .2

8 7

7 1

-0 .0

1 8

3 *

0 .0

0 5

6 3

-0 .0

0 8

3 *

0 .1

5 0

9 0

-0 .8

2 4

0 .6

1 9

0 3

G r o

w th

-0 .0

7 5

8 8

0 .0

0 5

7 4

-0 .0

6 2

1 7

0 .0

0 5

5 8

* *

-0 .0

0 1

8 3

0 .0

0 2

9 *

0 .0

0 8

9 4

0 .1

8 2

3 4

-0 .1

1 2

3 9

(- 3

, +

3 )

M a

tu r e

-0 .0

7 8

8 5

-0 .0

2 3

1 6

0 .1

7 0

1 6

0 .0

0 0

0 .0

0 3

0 5

0 .0

0 2

0 .2

0 3

5 7

-0 .1

6 4

4 4

0 .7

4 7

4 9

E x

p a

n s io

0 .0

3 1

6 3

-0 .0

2 0

8 4

0 .3

9 1

6 2

-0 .0

1 8

9 2

0 .0

0 5

1 5

-0 .0

0 9

0 4

0 .1

2 4

8 6

-0 .7

3 2

0 3

* *

0 .4

8 4

9 4

G r o

w th

-0 .0

3 3

5 1

0 .0

0 1

3 5

-0 .0

4 8

2 3

0 .0

0 5

6 5

-0 .0

0 2

4 3

0 .0

0 2

4 9

0 .0

2 5

0 .1

3 2

3 8

-0 .4

2 4

8 8

(- 5

, +

5 )

M a

tu r e

-0 .1

1 4

0 3

-0 .0

3 5

5 2

0 .0

1 8

8 2

0 .0

0 3

7 8

0 .0

0 4

6 4

-0 .0

0 0

0 .3

9 7

5 6

* *

-0 .1

5 1

1 7

1 .0

7 1

8 4

E x

p a

n s io

0 .0

1 1

5 6

0 .0

0 2

9 0

0 .0

3 2

8 5

-0 .0

0 0

9 6

-0 .0

0 0

1 9

-0 .0

0 1

7 1

-0 .0

1 7

-0 .0

1 0

4 7

-0 .0

0 7

6 3

G r o

w th

0 .1

0 6

0 2

0 .0

1 5

6 0

-0 .2

4 4

3 9

0 .0

0 5

7 0

-0 .0

1 3

7 8

0 .0

0 2

1 9

0 .4

0 2

4 9

-1 .8

5 7

8 6

* *

I N

D E

P E

N D

E N

V A

R I A

B L

C A

G R

F in

a n

c ia

L e v

e r a

g e

M a

r k

e t

c a

p t

G D

P o

li ti

c a

l r is

r a

ti n

F in

a n

c ia

fr e e d

o m

B u

s in

e s s

fr e e d

o m

R e c e s s io

C u

lt u

r e

G e o

g r a

p h

* indicates significance at 5%; **indicates significance at 10%

From the results, it can be observed that Growth firms have a significant positive

abnormal return of 1.48% around the date of announcement of cross listing, whereas

Expansion and Mature companies have witnessed negative returns of 2% and 1.6%

respectively.

For growth companies, geographical proximity has a negative relation, whereas

political risk rating and business freedom have a positive relation with abnormal

returns. Abnormal returns of expansion companies is negatively impacted by political

risk rating, business freedom and cultural proximity. A notable observation is that

mature companies registered gains when cross listing was done during recession.

The significant finding is that only growth firms have abnormal gains; shareholders of

expansion and mature companies have registered losses around the date of

announcement of cross listing. A possible reason for this could be shareholders

optimism about the long-run opportunities for growth companies. Expansion and

mature companies, on the other hand, have already established a ground for

themselves, thus long-run growth opportunities are not as many as for growth

companies. Growth companies also do not suffer from organisational rigidities and

inertia, thus making their future prospects bright.

In brief, findings suggest that wealth creation will vary depending upon the age of the

company at the time of making the international cross listing issue.

5.3 SIZE OF TOTAL ASSETS

The firms under study have been clustered based on the size of total assets. The

classification is based on the definition followed by NSE for Indian firms that groups

NIFTY500 firms into large, mid and small-cap firms (as no global standard of value

based classification is available). The top 20% of the firms by total assets are identified as

large size firms, next 30% are categorised as Medium size firms, and the bottom 50% are

designated as Small size firms. This categorisation is shown in Table 5.4

Table 5.4: Size based segregation of 146 companies under study for the period 1997-2017

Classification Basis of classification Asset size range (Crores) Number of

companies

Small size

Bottom 50% of the firms

under study by size of

assets

Asset size less than INR

523 crores 72

Medium size

Next 30% of the firms

under study by size of

assets

Asset size greater than

INR 523 crores and less

than 1835 crores

Large size

Top 20% of the firms

under study by size of

assets

Asset size greater than

1835 crores 25

Table 5.5 shows the CAAR for small, medium and large companies.

Table 5.5: CAAR for small, medium and large companies for different event windows

for the period 1995-2017

Event Window

CAAR

Small Medium Large

(-5, +5) 0.0114 0.0257 -0.0366*

(-3, +3) -0.0004 -0.0228** -0.0264*

(-1, +1) 0.0098 -0.0261* -0.0215*

(0, 0) 0.0034 0.0035 0.0023

* indicates significance at 5%; **indicates significance at 10%

Table 5.6: Regression results for small, medium and large size companies for the period

1997-2017

E V

E N

T W

IN D

O W

(- 1 ,

+ 1 )

L a

r g e

0 .0

3 7

6 1

-0 .0

0 0 3

-0 .2

7 3 7

0 .0

0 4

9 2

-0 .0

0 1 3

-0 .0

0 3 7

-0 .0

7 3 0

0 .0

7 4

1 3

-0 .1

2 5 2

M e d

iu m

0 .3

7 1

7 4

-0 .0

2 4 8

0 .4

1 5

5 0

-0 .0

1 8 5

6 *

0 .0

0 3

4 4

-0 .0

1 0 4

5 *

-0 .8

7 8 5

1 .1

2 2

6 9

S m

a ll

-0 .0

0 8 8

-0 .0

1 2 6

-0 .1

0 4 8

0 .0

0 6

5 3

-0 .0

0 1 5

0 .0

0 2

0 5

-0 .0

4 6 3

0 .1

9 8

5 6

-0 .4

0 0 6

(- 3 ,

+ 3 )

L a

r g e

-0 .0

0 6 4

-0 .0

0 0 9

-0 .2

7 0 6

0 .0

0 4

5 0

0 .0

0 0

1 9

-0 .0

0 2 7

-0 .2

4 5 7

0 .0

6 9

5 3

-0 .1

9 5 7

M e d

iu m

0 .3

9 6

7 0

-0 .0

3 9 1

0 .4

7 0

5 5

-0 .0

1 3 2

0 .0

0 3

0 4

-0 .0

1 1 0

9 *

0 .0

0 1

6 7

-0 .4

9 5 1

0 .6

8 2

9 9

S m

a ll

-0 .0

1 1 9

-0 .0

2 7 6

-0 .0

2 1 3

0 .0

0 5

1 7

-0 .0

0 2 3

0 .0

0 2

6 8

-0 .0

6 1 0

0 .2

0 3

5 9

-0 .5

0 6 7

(- 5 ,

+ 5 )

L a

r g e

0 .0

3 9

7 6

-0 .0

0 2 0

-0 .5

4 4 3

0 .0

0 9

1 7

-0 .0

0 5 1

-0 .0

0 9 1

-0 .3

1 0 4

0 .4

0 4

2 9

-0 .8

9 8 3

M e d

iu m

0 .1

2 4

7 4

0 .0

1 1

6 1

0 .1

3 9

8 5

0 .0

0 7

4 4

0 .0

0 0

2 3

-0 .0

0 3 8

0 .5

9 7

3 3

-0 .4

7 0 8

S m

a ll

-0 .0

1 5 1

-0 .0

2 2 9

-0 .1

3 3 0

0 .0

0 3

7 7

-0 .0

0 3 7

0 .0

0 2

3 0

-0 .0

2 3 8

0 .1

2 3

5 1

-0 .1

6 1 0

IN D

E P

E N

D E

N T

V A

R IA

B L

C A

G R

F in

a n

c ia

l L

e v

e r a g e

M a

r k

e t

c a p

t o

G D

P o

li ti

c a

l r is

k t

a k

in g

F in

a n

c ia

l fr

e e d

o m

B u

si n

e ss

f r e e d

o m

R e c e ss

io n

C u

lt u

r e

G e o g

r a

p h

* indicates significance at 5%; **indicates significance at 10%

Results show that while small size companies do not have any significant abnormal returns,

medium size companies and large size companies have negative returns. Large size

companies have losses as high as 3.66%, but no explanatory variable has been found that

significantly impacts the abnormal returns. Medium size firms are negatively related with

political risk rating and business freedom, generating negative returns as high as 2.61%.

This result is in conformity with the theoretical size effect, a smaller firm outperforms a

larger one. Relevant data shows that losses for any event window are higher for large

size companies than for medium size companies.

5.3 INDUSTRY

The firms under study belong to different industries. Segregating them on the basis of

their sector will enable better exposition of the abnormal returns generated. Table 5.7

shows the classification of industries under study

Table 5.7: Number of companies according to various industries

Classification Number of companies

Consumer goods 34

IT and Telecom 36

Industrial and Manufacturing 47

Others 29

The present section focusses on the abnormal returns generated in 3 sectors -

Consumer goods, IT and Telecom and Industrial and Manufacturing

Table 5.8: CAAR for Consumer goods, IT and Telecom and Industrial and

Manufacturing for the period 1997-2017

Event Window

CAAR

Consumer Goods IT and Telecom Industrial and

Manufacturing

(-5, +5) 0.0115 0.0253 0.0247

(-3, +3) 0.0044 0.0198 0.0017

(-1, +1) 0.0185 0.0138 0.0063

(0, 0) 0.0065 0.0132 0.0019

* indicates significance at 5%; **indicates significance at 10%

Table 5.9: Regression results according to different industries for the period 1997-2017

E V

E N

T W

IN D

O W

(- 1

, +

1 )

In d

u st

r ia

l a

n d

M fg

0 .0

4 7 3

2 4

-0 .0

0 3

4 4

0 .0

0 5 1

4 6

0 .0

0 2 9

3 1

-0 .0

0 2

3 1

0 .0

0 0 7

7 4

0 .0

0 5 4

5 5

0 .1

2 6 8

0 2

0 .2

6 3 0

8 1

IT a

n d

T e le

c o

0 .0

0 1 3

5 8

0 .0

3 9 8

4 8

0 .0

4 7 9

9 9

0 .0

0 4 3

6 4

0 .0

0 1 4

7 5

0 .0

0 5 3

4 *

0 .0

1 9 1

2 9

0 .0

7 2 6

8 9

0 .1

2 4 9

3 7

C o

n su

m e r

g o

o d

0 .0

4 5 4

3 7

-0 .0

0 5

5 5

0 .1

7 9 7

8 6

0 .0

0 6 4

5 6

0 .0

1 0 6

2 7 *

0 .0

0 2 9

8 4

-0 .0

1 6

3 6

0 .5

2 6 1

2 5

-2 .3

4 6

3 *

(- 3

, +

3 )

In d

u st

r ia

a n

d M

0 .0

7 1 5

9 7

-0 .0

2 1

0 .1

8 9 8

8 2

0 .0

0 0 2

3 6

-0 .0

0 3

6 8

-0 .0

0 1

2 2

0 .0

4 6 1

9 3

0 .0

2 4 6

6 4

0 .4

2 2 0

IT a

n d

T e le

c o

0 .0

0 2 6

4 4

-0 .0

3 2

0 .3

2 5 6

* *

-0 .0

0 3

8 8

0 .0

0 6 9

0 .0

0 7 1

5 7

0 .0

5 5 3

0 8

-0 .2

0 9

2 2

0 .2

3 2 7

6 3

C o

n su

m e r

g o

o d

0 .0

6 8 1

6 2

-0 .0

1 9

0 1

0 .2

0 8 9

3 6

0 .0

1 1 6

3 5

0 .0

1 1 9

5 1

0 .0

0 2 6

9 9

-0 .1

0 2

9 4

0 .8

6 5 3

6 8

-3 .0

2 9

5 * *

(- 5

, +

5 )

In d

u st

r ia

a n

d M

0 .1

2 0 5

9 2

0 .0

0 9 0

1 9

-0 .0

6 9

0 8

0 .0

0 8 2

9 8

-0 .0

0 8

7 1

0 .0

0 0 8

4 9

0 .0

7 8 7

6 9

0 .3

1 6 3

1 7

0 .4

8 3 1

6 6

IT a

n d

T e le

c o

0 .0

1 7 6

9 7

-0 .0

2 5

5 6

0 .5

1 7 4 7 * *

-0 .0

1 0 0 1

0 .0

1 0 9 9 * *

0 .0

0 5 9 0 * *

0 .0

6 6 2

0 4

-0 .3

0 2

3 6

0 .1

6 1 0

7 3

C o

n su

m e r

g o

o d

0 .1

3 9 4

9 7

0 .0

0 7 0

4 9

0 .1

1 4 5

0 8

0 .0

0 9 6

4 8

0 .0

1 0 8

8 1

0 .0

0 2 4

1 7

-0 .0

9 1

9 2

0 .8

4 2 8

0 9

-2 .6

8 3

8 8

IN D

E P

E N

D E

N T

V A

R IA

B L

C A

G R

F in

a n

c ia

L e v

e r a

g e

M a

r k

e t

c a

p t

G D

P o

li ti

c a

l r is

r a

ti n

F in

a n

c ia

fr e e d

o m

B u

si n

e ss

f r e e d

o m

R e c e ss

io n

C u

lt u

r e

G e o

g r a

p h

* indicates significance at 5%; **indicates significance at 10%

The study observes that for the three sectors considered, the returns are positive but

not significant for any event window.

Summary

The dis-aggregative analysis has provided a better understanding of the abnormal

returns generated by companies of different age, size and industry. No significant

results have been obtained for industry-wise analysis. But segregation on the basis of

age shows abnormal returns are positive for growth companies and negative for

expansion and mature companies. Further, it is noted from size based segregation that

larger companies generate higher abnormal losses.

CHAPTER 6

CONCLUDING OBSERVATIONS

The study has examined the wealth effects of cross listing for shareholders. The study

has dwelt on measuring the abnormal returns generated around the date of

announcement of cross listing for various event windows and to identify the plausible

determinants of the abnormal returns.

The study is based on secondary data of 146 instances of first international cross

listing by Indian companies for the period 1997-2015. There are some select

observations.

First, in the context of cross listing by Indian companies, shareholders have witnessed

losses around the date of announcement of cross listing. This is contrary to existing

literature which provides evidence that shareholders‟ wealth increases around cross

listing. Negative returns in Indian context could be due to the pessimism of the

investors regarding additional risks that the company will face after an international

listing. There is also a transition observed from positive pre-announcement returns to

negative post-announcement returns.

Second, wealth effects of cross listing vary over time. Returns generated are negative

for the pre-recession and during recession period. However, the post-recession period

has witnessed significant gains to shareholders around the date of announcement of

cross listing.

Third, the study also examines the determinants of value creation to shareholders due

to cross listing. Only two significant variables could be observed when regression was

run on all 146 instances of cross listing. Both financial leverage and business freedom

affect cumulative average abnormal returns in a negative way. While it is appropriate

to note that returns are lower for high-levered firms, it is a puzzle to note that higher

business freedom to operate negatively influences abnormal returns. This shows that

regulations in the form of disclosures and greater transparency boost the confidence of

investors when stocks are listed in a foreign exchange.

Fourth, cumulative average abnormal returns vary according to different host markets.

Indian companies have majorly picked 4 destinations to list their stocks. Luxembourg,

London, United States and Singapore. Cross listing at Luxembourg and London has

produced unfavourable returns for shareholders. Returns are not significant when

cross listing is done in United States. Singapore is the only host market that has

produced gains for shareholders. The significant variables that explain the positive

return in the case of Singapore stock exchange include a higher CAGR, financial

leverage and financial freedom.

Fifth, for better exposition, the firms under study have been categorised based on age,

size of total assets and industry. A surprising observation was that there are gains for

cross listing by growth companies, but there are losses for cross listing by expansion

and mature companies. Investors see mettle in growth companies as they are

perceived to be having tremendous scope for growth and development. In terms of

size of assets, the results are in conformity with the theoretical size effect. Large size

companies have abnormal losses higher than the medium size companies. The results

generated by small size companies are not significant. Three industries have been

studied in detail – consumer goods, IT and Telecom and Industrial and

Manufacturing. The results for no sector were noted to be significant. Category-wise

analysis of the firms has helped in better understanding of the abnormal returns

generated and the explanatory variables for the same.

In sum, it is reasonable to conclude that market performance does not improve after

cross listing. Only growth firms, that have promising development opportunities, are

likely to generate gains for shareholders when they list themselves overseas. Despite

negative returns, firms continue to list their shares abroad. The possible explanation of

this could be that in order to achieve long run targets, cross listed firms are ready to

accept the short-term losses.

Overall, results show that wealth effects of raising capital in international markets in

the context of Indian companies is generally negative and it varies across host

markets, over time and according to company specific factors.

REFERENCES

[1] Abdallah, A. A. N., & Ioannidis, C. (2010). Why do firms cross-list? International

evidence from the US market. The Quarterly Review of Economics and

Finance, 50(2), 202-213.

[2] Adelegan, O. J. (2009). The impact of the regional cross-listing of stocks on firm

value in sub-Saharan Africa (No. 9-99). International Monetary Fund.

[3] Anderson, C. W., Fedenia, M., Hirschey, M., & Skiba, H. (2011). Cultural

influences on home bias and international diversification by institutional

investors. Journal of Banking & Finance, 35(4), 916-934.

[4] Bancel, F., & Mittoo, C. (2001). European managerial perceptions of the net benefits

of foreign stock listings. European financial management, 7(2), 213-236.

[5] Bianconi, M., & Tan, L. (2010). Cross-listing premium in the US and the UK

destination. International Review of Economics & Finance, 19(2), 244-259.

[6] Bris, A., Cantale, S., & Nishiotis, G. P. (2007). A breakdown of the valuation effects

of international cross‐listing. European Financial Management, 13(3), 498-530.

[7] Brown, S. J., & Warner, J. B. (1985). Using daily stock returns: The case of event

studies. Journal of financial economics, 14(1), 3-31.

[8] Dodd, O. (2013). Why do firms cross-list their shares on foreign exchanges? A

review of cross-listing theories and empirical evidence. Review of Behavioural

Finance, 5(1), 77-99.

[9] Doidge, C., Karolyi, G. A., & Stulz, R. M. (2004). Why are foreign firms listed in

the US worth more?. Journal of financial economics, 71(2), 205-238.

[10] Foerster, S. R., & Karolyi, G. A. (1999). The effects of market segmentation and

investor recognition on asset prices: Evidence from foreign stocks listing in the

United States. The Journal of Finance, 54(3), 981-1013.

[11] Ghadhab, I., & Hellara, S. (2016). Cross-listing and value creation. Journal of

Multinational Financial Management, 37, 1-11.

[12] Grinblatt, M., & Keloharju, M. (2001). How distance, language, and culture

influence stockholdings and trades. The Journal of Finance, 56(3), 1053-1073.

[13] Hail, L., & Leuz, C. (2009). Cost of capital effects and changes in growth

expectations around US cross-listings. Journal of financial economics, 93(3),

428-454.

[14] Michael, H., Pagano, M., Randl, O., & Zechner, J. (2008). Where is the Market?

Evidence from Cross-Listings in the US. Review of Financial Studies, 21, 725-761.

[15] Lau, S. T., Diltz, J. D., & Apilado, V. P. (1994). Valuation effects of international

stock exchange listings. Journal of banking & finance, 18(4), 743-755.

[16] Lee, I. (1991). The impact of overseas listings on shareholder wealth: The case of the

London and Toronto stock exchanges. Journal of Business Finance &

Accounting, 18(4), 583-592.

[17] Lee, D. (2004). Why does shareholder wealth increase when non-US firms announce

their listing in the US?.

[18] McWilliams, A., & Siegel, D. (1997). Event studies in management research:

Theoretical and empirical issues. Academy of management journal, 40(3), 626-657.

[19] Miller, D. P. (1999). The market reaction to international cross-listings:: evidence

from Depositary Receipts1. Journal of Financial economics, 51(1), 103-123.

[20] Mittoo, U. R. (2003). Globalization and the value of US listing: Revisiting Canadian

evidence. Journal of Banking & Finance, 27(9), 1629-1661.

[21] Portes, R., & Rey, H. (2005). The determinants of cross-border equity flows. Journal

of international Economics, 65(2), 269-296.

[22] Roosenboom, P., & Van Dijk, M. A. (2009). The market reaction to cross-

listings: Does the destination market matter?. Journal of Banking &

Finance, 33(10), 1898-1908.

[23] Sarkissian, S., & Schill, M. J. (2003). The overseas listing decision: New evidence of

proximity preference. The Review of Financial Studies, 17(3), 769-809.

[24] Sarkissian, S., & Schill, M. J. (2008). Are there permanent valuation gains to

overseas listing?. The Review of Financial Studies, 22(1), 371-412.

[25] Serra, A. P. (1999). Dual‐listings on international exchanges: the case of emerging

markets‟ stocks. European Financial Management, 5(2), 165-202.

[26] Stulz, R. M. (1999). Golbalization, corporate finance, and the cost of capital. Journal

of applied corporate finance, 12(3), 8-25.

[27] You, L., Lucey, B. M., & Shu, Y. (2013). An empirical study of multiple direct

international listings. Global Finance Journal, 24(1), 69-84.

ANNEXURE

Table A.1: List of ADR/GDR for the period 1992-2017

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

RELIANCE

INDUSTRIES

LTD.

27-May-1992 GDS 43,351.04 150.42 LUXEMBOURG/NA

SDAQ

GRASIM

INDUSTRIES

LTD.

25-Nov-1992 GDS 25,650.00 90.00 LUXEMBOURG/NA

SDAQ

HINDALCO

INDUSTRIES

LTD.

22-Jul-1993 GDR-W 22,758.32 72.02 LUXEMBOURG

SOUTHERN

PETROCHEMIC

AL INDUSTRIES

CORP.LTD.

29-Sep-1993 GDR 23,568.68 74.75 LUXEMBOURG

5 ITC LTD. 14-Oct-1993 GDR-W 21,708.40 68.85 LUXEMBOURG

BOMBAY

DYEING &

MANUFACTURI

CO.LTD.,THE

16-Nov-1993 GDR-W 15,686.85 50.00 LUXEMBOURG

MAHINDRA &

MAHINDRA

LTD.

30-Nov-1993 GDR 23,452.81 74.75 LUXEMBOURG

INDO GULF

FERTILISERS &

CHEMICALS

CORP.LTD.

18-Jan-1994 GDR 31,440.00 100.00 LUXEMBOURG

INDIAN RAYON

& INDUSTRIES

LTD.

25-Jan-1994 GDR 39,300.00 125.00 LUXEMBOURG

VIDEOCON

INTERNATIONA

L LTD.

26-Jan-1994 GDR 28,296.00 90.00 LUXEMBOURG

11 ARVIND MILLS

LTD.,THE 03-Feb-1994 GDR 39,300.00 125.00 LUXEMBOURG

GREAT

EASTERN

SHIPPING

CO.LTD.,THE

17-Feb-1994 GDR 31,370.00 100.00 LUXEMBOURG

TATA

ELECTRIC

COMPANIES

22-Feb-1994 GDR 23,580.00 75.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

INDIAN

ALUMINIUM

CO.LTD.

22-Feb-1994 GDR 18,785.85 59.88 LUXEMBOURG

JAIN

IRRIGATION

SYSTEMS LTD.

25-Feb-1994 EDR 9,402.34 29.97 LUXEMBOURG

16 WOCKHARDT

LTD. 25-Feb-1994 GDR 23,580.00 75.00 LUXEMBOURG

UNITED

PHOSPHORUS

LTD.

25-Feb-1994 GDR 17,254.88 55.00 LUXEMBOURG

18 GARDEN SILK

MILLS LTD. 04-Mar-1994 GDR 14,135.86 44.99 LUXEMBOURG

19 CESC LTD. 14-Apr-1994 GDR-W 28,042.35 89.25 LUXEMBOURG

20 DCW LTD. 19-May-1994 GDR 7,843.12 25.00 LUXEMBOURG

TUBE

INVESTMENTS

OF INDIA LTD.

20-May-1994 GDR 14,307.00 45.60 LUXEMBOURG

CORE

PARENTERALS

LTD.

21-Jun-1994 GDR 21,960.75 70.00 LUXEMBOURG

RANBAXY

LABORATORIE

S LTD.

29-Jun-1994 GDS 31,372.50 100.00 LUXEMBOURG

24 E.I.D.-PARRY

(INDIA) LTD. 07-Jul-1994 GDR 15,690.60 50.00 LUXEMBOURG

25 TATA MOTORS

LTD. 15-Jul-1994 GDR-W 40,423.30 128.87 LUXEMBOURG

DR.REDDY'S

LABORATORIE

S LTD.

18-Jul-1994 GDR 15,057.60 48.00 LUXEMBOURG

27 FINOLEX

CABLES LTD. 19-Jul-1994 GDR 17,254.88 55.00 LUXEMBOURG

SANGHI

POLYESTERS

LTD.

28-Jul-1994 GDR 15,685.00 50.00 LUXEMBOURG

29 JCT LTD. 29-Jul-1994 GDR 14,847.83 47.32 LUXEMBOURG

SIV

INDUSTRIES

LTD.

01-Aug-1994 GDR 14,118.75 45.00 LUXEMBOURG

HINDUSTAN

DEVELOPMENT

CORP.LTD.

21-Sep-1994 GDR-W 20,392.12 65.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

CENTURY

TEXTILES &

INDUSTRIES

LTD.

21-Sep-1994 GDR 31,375.00 100.00 LUXEMBOURG

GUJARAT

NARMADA

VALLEY

FERTILIZERS

CO.LTD.

06-Oct-1994 GDR 17,300.18 55.14 LUXEMBOURG

EAST INDIA

HOTELS

LTD.,THE

07-Oct-1994 GDR 12,549.00 40.00 LONDON

SHRIRAM

INDUSTRIAL

ENTERPRISES

LTD.

14-Oct-1994 GDR-W 12,564.69 40.05 LONDON

36 USHA

BELTRON LTD. 14-Oct-1994 GDR 9,411.00 30.00 LUXEMBOURG

37 JK CORP LTD. 17-Oct-1994 GDR 17,254.88 55.00 LONDON

INDIA

CEMENTS

LTD.,THE

18-Oct-1994 GDR 15,528.15 49.50 LUXEMBOURG

39 BAJAJ AUTO

LTD. 27-Oct-1994 GDR 36,087.00 115.00 LONDON

40 NEPC-MICON

LTD. 14-Nov-1994 GDR 14,968.26 47.70 LUXEMBOURG

41 LARSEN &

TOUBRO LTD. 18-Nov-1994 GDS 42,352.87 135.00 LUXEMBOURG

RAYMOND

WOOLLEN

MILLS

LTD.,THE

23-Nov-1994 GDR 18,822.00 60.00 LONDON

43 ORIENTAL

HOTELS LTD. 14-Dec-1994 GDR 9,411.00 30.00 LUXEMBOURG

INDIAN

PETROCHEMIC

ALS CORP.LTD.

15-Dec-1994 GDS 26,666.62 85.00 LUXEMBOURG

45 ASHOK

LEYLAND LTD. 20-Mar-1995 GDR 43,411.33 137.77 LONDON/NASDAQ

INDIAN

HOTELS

CO.LTD.,THE

28-Apr-1995 GDS 27,069.56 86.25 LONDON/NASDAQ

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

HIMACHAL

FUTURISTIC

COMMUNICATI

ONS LTD.

02-Aug-1995 GDR 15,705.50 50.00 LONDON

FLEX

INDUSTRIES

LTD.

30-Nov-1995 GDR 10,485.00 30.00 LUXEMBOURG

49 BSES LTD. 04-Mar-1996 GDR 43,187.50 125.00 LONDON

STEEL

AUTHORITY OF

INDIA LTD.

07-Mar-1996 GDR 42,668.75 125.00 LONDON

INDO RAMA

SYNTHETICS

(INDIA) LTD.

21-Mar-1996 GDR 17,500.00 50.00 LUXEMBOURG

52 BHARAT

HOTELS LTD. 16-May-1996 GDR 6,825.00 19.50 LUXEMBOURG

53 CROMPTON

GREAVES LTD. 02-Jul-1996 GDR 17,540.00 50.00 LONDON

INDUSTRIAL

CREDIT &

INVESTMENT

CORP.OF INDIA

LTD.,THE

02-Aug-1996 GDR 78,366.60 220.10 LONDON

KESORAM

INDUSTRIES

LTD.

09-Aug-1996 GDR 10,770.00 30.00 LUXEMBOURG

56 STATE BANK

OF INDIA 03-Oct-1996 GDR 1,32,442.10 369.95 LONDON

PENTAFOUR

SOFTWARE &

EXPORTS LTD.

03-Dec-1996 GDR 4,182.75 11.70 LUXEMBOURG

VIDESH

SANCHAR

NIGAM LTD.

24-Mar-1997 GDR 1,88,952.47 526.55 LONDON

59 BPL CELLULAR

HOLDINGS LTD. 15-May-1997 ADR 35,840.00 100.00

MAHANAGAR

TELEPHONE

NIGAM LTD.

04-Dec-1997 GDR 1,63,226.70 418.53 LONDON

INFOSYS

TECHNOLOGIE

S LTD.

11-Mar-1999 ADS 29,897.42 70.38 NASDAQ

62 ICICI LTD. 22-Sep-1999 ADS 1,37,183.13 315.00 NYSE

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

63 SATYAM

INFOWAY LTD. 19-Oct-1999 ADS 37,519.24 86.42 NASDAQ

64 GAIL (INDIA)

LTD. 04-Nov-1999 GDR 1,08,542.44 249.81 LONDON

65 DISHNET DSL

LTD. 28-Feb-2000 GDR 46,237.20 106.00

66 TATA TEA LTD. 02-Mar-2000 GDS 32,737.50 75.00 LUXEMBOURG

67 SSI LTD. 24-Mar-2000 GDS 43,650.00 100.00 LONDON

68 ICICI BANK

LTD. 27-Mar-2000 ADS 76,335.00 175.00 NYSE

69 REDIFF.COM

INDIA LTD. 19-Jun-2000 ADS 28,369.21 63.48 NASDAQ

SILVERLINE

TECHNOLOGIE

S LTD.

20-Jun-2000 ADS 48,330.00 108.00 NYSE

71 APTECH LTD. 28-Jul-2000 GDS 33,667.50 75.00 LONDON

72 WIPRO LTD. 24-Oct-2000 ADS 52,837.34 113.80 NYSE

SATYAM

COMPUTER

SERVICES LTD.

18-May-2001 ADS 76,000.55 161.91 NYSE

74 PENTAMEDIA

GRAPHICS LTD. 16-Jul-2001 GDR 8,991.60 19.05 LUXEMBOURG

75 HDFC BANK

LTD. 25-Jul-2001 ADS 81,299.25 172.50 NYSE

PENTASOFT

TECHNOLOGIE

S LTD.

05-May-2002 GDR 3,173.26 6.48 LUXEMBOURG

77 MASCON

GLOBAL LTD. 30-Jul-2002 GDR 4,873.00 10.00 LUXEMBOURG

78 QUINTANT

SERVICES LTD. 23-Jan-2003 ADR 4.79 0.01

79 AFTEK

INFOSYS LTD. 10-Feb-2003 GDR 7,153.50 15.00 LUXEMBOURG

MOREPEN

LABORATORIE

S LTD.

31-Mar-2003 GDR 7,243.75 15.25 LUXEMBOURG

81 STERLING

BIOTECH LTD. 03-Oct-2003 GDR 7,728.20 17.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

82 SIFY LTD. 07-Oct-2003 ADS 2,021.72 4.46

BALLARPUR

INDUSTRIES

LTD.

18-Nov-2003 GDS 15,939.00 35.00 LUXEMBOURG

MAARS

SOFTWARE

INTERNATIONA

L LTD.

05-Dec-2003 GDR 5,958.63 13.05 LUXEMBOURG

CREST

ANIMATION

STUDIOS LTD.

23-Jan-2004 GDR 2,531.09 5.58 LUXEMBOURG

ASSOCIATED

CEMENT

COMPANIES

LTD.,THE

18-Mar-2004 GDS 18,114.00 40.00 LONDON

CRANES

SOFTWARE

INTERNATIONA

L LTD.

31-Mar-2004 GDR 5,033.24 11.60 LUXEMBOURG

ELDER

PHARMACEUTI

CALS LTD.

30-Apr-2004 GDR 5,484.13 12.36 LUXEMBOURG

89 MEGHMANI

ORGANICS LTD. 30-Jul-2004 SDS 13,043.97 28.11 SINGAPORE

TELEDATA

INFORMATICS

LTD.

10-Aug-2004 GDR 3,716.80 8.00 LUXEMBOURG

91 LIC HOUSING

FINANCE LTD. 07-Sep-2004 GDS 13,841.44 29.85 LUXEMBOURG

92 MICRO INKS

PVT.LTD. 10-Nov-2004 GDS 18,060.00 40.00 LUXEMBOURG

93 AMTEK AUTO

LTD. 22-Nov-2004 GDR 31,105.20 69.00 LONDON

94 GAMMON

INDIA LTD. 22-Dec-2004 GDR 5,265.60 12.00 LUXEMBOURG

95 GRANULES

INDIA LTD. 20-Jan-2005 GDR 3,786.97 8.65 LUXEMBOURG

96 ESSAR

PROJECTS LTD. 31-Jan-2005 GDR 37,573.40 86.00

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

INDIABULLS

FINANCIAL

SERVICES LTD.

03-Mar-2005 GDR 26,190.00 60.00 LUXEMBOURG

98 UTI BANK LTD. 16-Mar-2005 GDR 1,12,039.15 257.00 LONDON

99 CENTURION

BANK LTD. 29-Mar-2005 GDR 35,032.00 80.00 LUXEMBOURG

100

SREI

INFRASTRUCTU

RE FINANCE

LTD.

18-Apr-2005 GDR 15,316.00 35.00 LONDON

101 BHARAT

FORGE LTD. 19-Apr-2005 GDR 43,760.00 100.00 LUXEMBOURG

102

MOSCHIP

SEMICONDUCT

TECHNOLOGY

LTD.

26-Apr-2005 GDR 3,185.00 7.29 LUXEMBOURG

103

BAJAJ

HINDUSTHAN

LTD.

13-May-2005 GDR 26,058.00 60.00 LUXEMBOURG

104 EMCO LTD. 23-Jun-2005 GDR 4,357.50 10.00 LUXEMBOURG

105

VIDEOCON

INDUSTRIES

LTD.

28-Jun-2005 GDR 1,52,460.00 350.00 LUXEMBOURG

106

APOLLO

HOSPITALS

ENTERPRISE

LTD.

07-Jul-2005 GDR 32,730.00 75.00 LUXEMBOURG

107

CREW

B.O.S.PRODUCT

S LTD.

25-Jul-2005 GDR 2,176.00 5.00 LUXEMBOURG

108

IND-SWIFT

LABORATORIE

S LTD.

16-Aug-2005 GDR 4,630.43 10.63 LUXEMBOURG

109

TANEJA

AEROSPACE &

AVIATION LTD.

13-Sep-2005 GDR 3,369.98 7.68 LUXEMBOURG

110

KEI

INDUSTRIES

LTD.

19-Sep-2005 GDR 4,390.00 10.00 LUXEMBOURG

111 JINDAL SAW

LTD. 20-Sep-2005 GDS 32,928.11 74.99 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

112

SUJANA

UNIVERSAL

INDUSTRIES

LTD.

28-Sep-2005 GDR 7,052.80 16.00 LUXEMBOURG

113 ELECTROSTEEL

CASTINGS LTD. 05-Oct-2005 GDR 17,724.00 40.00 LONDON

114

LLOYD

ELECTRIC &

ENGINEERING

LTD.

10-Oct-2005 GDR 12,828.25 28.75 LONDON

115 WANBURY

LTD. 12-Oct-2005 GDR 4,488.00 10.00 LUXEMBOURG

116 USHA MARTIN

LTD. 27-Oct-2005 GDR 11,277.50 25.00 LUXEMBOURG

117

ORCHID

CHEMICALS &

PHARMACEUTI

CALS LTD.

02-Nov-2005 GDR 18,139.77 40.15 LUXEMBOURG

118 REI AGRO LTD. 17-Nov-2005 GDR 13,804.23 30.16 LONDON

119

PATNI

COMPUTER

SYSTEMS LTD.

24-Nov-2005 ADS 57,250.58 125.22 NYSE

120

EVEREADY

INDUSTRIES

INDIA LTD.

02-Dec-2005 GDR 15,219.60 33.00 LUXEMBOURG

121 LYKA LABS

LTD. 07-Dec-2005 GDR 2,308.50 5.00 LUXEMBOURG

122

MICRO

TECHNOLOGIE

S (INDIA) LTD.

07-Dec-2005 GDR 3,910.60 8.47 LUXEMBOURG

123

GATEWAY

DISTRIPARKS

LTD.

12-Dec-2005 GDR 39,256.14 84.97 LUXEMBOURG

124

GREAT

EASTERN

ENERGY

CORP.LTD.

13-Dec-2005 GDR 15,351.80 33.33 LONDON-AIM

125

NAGARJUNA

CONSTRUCTIO

N CO.LTD.

14-Dec-2005 GDR 55,008.00 120.00 LUXEMBOURG

126

DWARIKESH

SUGAR

INDUSTRIES

LTD.

15-Dec-2005 GDR 5,460.00 12.00 LUXEMBOURG

127 IL&FS 15-Dec-2005 GDS 45,026.80 98.96 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

INVESTSMART

LTD.

128 HIMATSINGKA

SEIDE LTD. 21-Dec-2005 GDS 27,222.00 60.00 LUXEMBOURG

129

BALRAMPUR

CHINI MILLS

LTD.

20-Jan-2006 GDR 22,180.00 50.00 LUXEMBOURG

130 VAIBHAV

GEMS LTD. 25-Jan-2006 GDR 30,927.71 69.83 LUXEMBOURG

131 FEDERAL

BANK LTD.,THE 31-Jan-2006 GDR 35,063.04 79.40 LONDON

132

VALECHA

ENGINEERING

LTD.

03-Feb-2006 GDR 5,351.83 12.10 LUXEMBOURG

133 MADHUCON

PROJECTS LTD. 21-Feb-2006 GDR 27,532.44 62.01 LUXEMBOURG

134

SHREYAS

SHIPPING &

LOGISTICS LTD.

21-Feb-2006 GDR 3,552.00 8.00 LUXEMBOURG

135 KRBL LTD. 24-Feb-2006 GDR 5,334.00 12.00 LUXEMBOURG

136

ERA

CONSTRUCTIO

NS (INDIA) LTD.

27-Feb-2006 GDR 13,326.00 30.00 LUXEMBOURG

137

RUCHI SOYA

INDUSTRIES

LTD.

09-Mar-2006 GDR 26,730.00 60.00 LUXEMBOURG

138

NOIDA TOLL

BRIDGE

CO.LTD.

21-Mar-2006 GDR 21,968.10 49.50 LONDON-AIM

139

MAN

INDUSTRIES

(INDIA) LTD.

22-Mar-2006 GDR 15,564.50 35.00 DUBAI

140

DHAMPUR

SUGAR MILLS

LTD.

23-Mar-2006 GDS 23,914.44 53.68 LUXEMBOURG

141 JK PAPER LTD. 30-Mar-2006 GDR 5,313.64 11.89 LUXEMBOURG

142 MCDOWELL &

CO.LTD. 30-Mar-2006 GDS 58,097.00 130.00 LUXEMBOURG

143

ALPS

INDUSTRIES

LTD.

31-Mar-2006 GDR 9,724.98 21.80 LUXEMBOURG

144

HINDUSTAN

CONSTRUCTIO

N CO.LTD.,THE

31-Mar-2006 GDS 44,610.00 100.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

145 ROLTA INDIA

LTD. 07-Apr-2006 GDR 46,192.05 103.50 LONDON

146

BSEL

INFRASTRUCTU

RE REALTY

LTD.

10-Apr-2006 GDR 9,171.70 20.50 LUXEMBOURG

147 CIPLA LTD. 18-Apr-2006 GDS 76,755.00 170.00 LUXEMBOURG

148 GV FILMS LTD. 20-Apr-2006 GDR 9,255.75 20.50 LUXEMBOURG

149

VISU

INTERNATIONA

L LTD.

24-Apr-2006 GDR 4,352.80 9.66 LUXEMBOURG

150

KOTAK

MAHINDRA

BANK LTD.

27-Apr-2006 GDS 45,014.94 99.90 LUXEMBOURG

151

PARAMOUNT

COMMUNICATI

ONS LTD.

02-May-2006 GDR 6,735.00 15.00 LUXEMBOURG

152 RANA SUGARS

LTD. 02-May-2006 GDR 8,082.00 18.00 DUBAI

153 TRICOM INDIA

LTD. 04-May-2006 GDR 2,261.99 5.03 LUXEMBOURG

154 SUBEX

SYSTEMS LTD. 23-Jun-2006 GDR 62,748.84 135.82 LUXEMBOURG

155 KLG SYSTEL

LTD. 01-Sep-2006 GDR 3,489.75 7.50 LUXEMBOURG

156 SHAH ALLOYS

LTD. 15-Sep-2006 GDR 3,210.65 6.96 LUXEMBOURG

157

SOMA

TEXTILES &

INDUSTRIES

LTD.

20-Oct-2006 GDR 7,838.63 17.30 LUXEMBOURG

158 ORG

INFORMATICS LTD.

06-Dec-2006 GDR 4,451.00 10.00 LUXEMBOURG

159 SUBEX AZURE

LTD. 19-Feb-2007 GDR 15,878.42 36.03 LONDON

160 MARG

CONSTRUCTIONS

LTD.

28-Feb-2007 GDR 8,862.00 20.00 LUXEMBOURG

161 UTTAM GALVA

STEELS LTD. 29-Mar-2007 GDR 13,036.65 29.99 SINGAPORE

162 INDUSIND BANK

LTD. 30-Mar-2007 GDR 14,746.50 33.83 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

163 IKF

TECHNOLOGIES

LTD.

30-Mar-2007 GDR 4,794.90 11.00 LUXEMBOURG

164

STERLITE

INDUSTRIES (INDIA) LTD.

18-Jun-2007 ADS 821,721.60 2,016.00 NYSE

165

INDIABULLS

REAL ESTATE LTD.

03-Jul-2007 GDR 162,320.00 400.00 LUXEMBOURG/LON

DON

166

KOHINOOR

BROADCASTING CORP.LTD.

20-Jul-2007 GDR 2,944.09 7.30 LUXEMBOURG

167

CAT

TECHNOLOGIES

LTD.

27-Jul-2007 GDR 2,615.01 6.46 LUXEMBOURG

168

WEBEL-SL

ENERGY

SYSTEMS LTD.

09-Aug-2007 GDR 7,999.20 19.80 SINGAPORE

169 K.S.OILS LTD. 10-Sep-2007 GDR 12,426.61 31.42 SINGAPORE

170 CYBERMATE

INFOTEK LTD. 27-Sep-2007 GDR 4,770.00 12.00 LUXEMBOURG

171

FINANCIAL

TECHNOLOGIES (INDIA) LTD.

11-Oct-2007 GDR 45,206.50 115.00 LUXEMBOURG/LON

DON

172

NORTHGATE

TECHNOLOGIES LTD.

18-Oct-2007 GDR 11,841.00 30.00 LUXEMBOURG

173

K SERA SERA

PRODUCTIONS

LTD.

02-Nov-2007 GDR 9,842.50 25.00 LUXEMBOURG

174

WEST COAST

PAPER MILLS

LTD.,THE

30-Nov-2007 GDR 3,582.20 9.03 SINGAPORE

175

VISESH

INFOTECNICS

LTD.

04-Dec-2007 GDR 3,943.00 10.00 SINGAPORE

176 EASUN

REYROLLE LTD. 05-Dec-2007 GDR 5,917.50 15.00 SINGAPORE

177 CALS REFINERIES

LTD. 12-Dec-2007 GDR 78,720.00 200.00 LUXEMBOURG

178 VYAPAR

INDUSTRIES LTD. 13-Dec-2007 GDR 7,870.06 19.99 SINGAPORE

179 GITANJALI GEMS

LTD. 14-Dec-2007 GDR 70,830.00 180.00 LONDON

180 AKSH OPTIFIBRE

LTD. 08-Jan-2008 GDR 7,854.00 20.00 LUXEMBOURG

181 COUNTRY CLUB

(INDIA) LTD. 09-Jan-2008 GDR 34,143.01 86.90 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

182 CONFIDENCE PETROLEUM

INDIA LTD.

11-Jan-2008 GDR 9,822.50 25.00 SINGAPORE

183

ACCENTIA

TECHNOLOGIES LTD.

21-Feb-2008 GDR 9,216.10 23.00 SINGAPORE

184 ANANT RAJ

INDUSTRIES LTD. 29-Feb-2008 GDR 60,263.23 150.96 LUXEMBOURG

185

PROTO

DEVELOPERS &

TECHNOLOGIES LTD.

23-Apr-2008 GDR 4,804.80 12.00 LUXEMBOURG

186 HINDUJA

FOUNDRIES LTD. 23-Apr-2008 GDR 5,992.50 15.00 LUXEMBOURG

187 SANRA

SOFTWARE LTD. 02-May-2008 GDR 11,178.75 27.50 LUXEMBOURG

188 BIHAR TUBES

LTD. 18-Jun-2008 GDR 8,580.00 20.00 LUXEMBOURG

189 SYBLY

INDUSTRIES LTD. 19-Jun-2008 GDR 3,000.81 6.99 LUXEMBOURG

190

ABL

BIOTECHNOLOGI

ES LTD.

20-Jun-2008 GDR 2,870.40 6.68 LUXEMBOURG

191 BECKONS

INDUSTRIES LTD. 11-Jul-2008 GDR 2,136.00 5.00 LUXEMBOURG

192 BRUSHMAN

(INDIA) LTD. 31-Jul-2008 GDR 6,798.40 16.00 LUXEMBOURG

193

EMPOWER

INDUSTRIES

INDIA LTD.

15-Sep-2008 GDR 918.80 2.00 LUXEMBOURG

194

VISHAL INFORMATION

TECHNOLOGIES LTD.

25-Mar-2009 GDR 19,478.06 38.32 LUXEMBOURG

195

ASAHI

INFRASTRUCTUR

E & PROJECTS LTD.

29-Apr-2009 GDR 3,003.16 5.98 LUXEMBOURG

196 IT PEOPLE

(INDIA) LTD. 25-May-2009 GDR 4,717.28 9.99 LUXEMBOURG

197 AVON CORP.LTD. 19-Jun-2009 GDR 4,813.00 10.00 LUXEMBOURG

198 SUZLON ENERGY

LTD. 20-Jul-2009 GDR 52,323.77 108.04 LUXEMBOURG

199 TATA STEEL LTD. 21-Jul-2009 GDR 241,350.00 500.00 LONDON

200 TATA POWER CO.LTD.,THE

22-Jul-2009 GDR 162,039.50 335.00 LUXEMBOURG

201 AXIS BANK LTD. 17-Sep-2009 GDR 45,835.33 95.55 LONDON

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

202 KAASHYAP

TECHNOLOGIES

LTD.

09-Oct-2009 GDR 2,046.00 4.40 LUXEMBOURG

203

RISHABHDEV

TECHNOCABLE LTD.

30-Oct-2009 GDR 2,387.53 5.14 LUXEMBOURG

204 BOMBAY RAYON

FASHIONS LTD. 18-Nov-2009 GDR 44,913.83 97.09 SINGAPORE

205 DISH TV INDIA

LTD. 23-Nov-2009 GDR 46,490.00 100.00 LUXEMBOURG

206 FCS SOFTWARE

SOLUTIONS LTD. 10-Dec-2009 GDR 11,259.52 24.10 LUXEMBOURG

207

SEL

MANUFACTURIN

G CO.LTD.

14-Dec-2009 GDR 3,970.77 8.51 LUXEMBOURG

208

STERLING INTERNATIONAL

ENTERPRISES

LTD.

15-Dec-2009 GDR 93,867.66 201.26 LUXEMBOURG

209

SHREE

ASHTAVINAYAK

CINE VISION LTD.

23-Dec-2009 GDR 33,732.00 72.00 LUXEMBOURG

210 SUJANA METAL PRODUCTS LTD.

23-Dec-2009 GDR 14,055.00 30.00 LUXEMBOURG

211 SUJANA TOWERS

LTD. 23-Dec-2009 GDR 14,055.00 30.00 LUXEMBOURG

212 BILCARE LTD. 06-Jan-2010 GDR 16,142.00 35.00

213 RAINBOW

PAPERS LTD. 27-Jan-2010 GDR 12,507.56 27.02 LUXEMBOURG

214 BIRLA POWER

SOLUTIONS LTD. 27-Jan-2010 GDR 9,258.00 20.00 LUXEMBOURG

215 B.A.G.FILMS &

MEDIA LTD. 15-Feb-2010 GDR 8,084.03 17.43 LUXEMBOURG

216 GLORY

POLYFILMS LTD. 18-Feb-2010 GDR 1,659.30 3.59 LUXEMBOURG

217

NECTAR

LIFESCIENCES

LTD.

26-Feb-2010 GDR 16,162.01 34.96 LUXEMBOURG

218 S.E.INVESTMENT

S LTD. 10-Mar-2010 GDR 17,646.33 38.86 LUXEMBOURG

219

TELEDATA

TECHNOLOGY SOLUTIONS LTD.

12-Mar-2010 GDR 16,802.87 36.97 LUXEMBOURG

220 BIRLA COTSYN

(INDIA) LTD. 15-Mar-2010 GDR 11,395.00 25.00 LUXEMBOURG

221 ASHCO NIULAB

INDUSTRIES LTD. 16-Apr-2010 GDR 4,449.00 10.00 LUXEMBOURG

222

KEMROCK

INDUSTRIES & EXPORTS LTD.

29-Apr-2010 GDR 22,285.00 50.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

223 KBS CAPITAL

MANAGEMENT

LTD.

19-May-2010 GDR 1,122.40 2.44 LUXEMBOURG

224 NISSAN COPPER

LTD. 20-May-2010 GDR 10,472.00 22.40 LUXEMBOURG

225 HIRAN

ORGOCHEM LTD. 20-May-2010 GDR 4,675.00 10.00 LUXEMBOURG

226 ZENITH BIRLA (INDIA) LTD.

28-May-2010 GDR 10,699.55 22.99 LUXEMBOURG

227

RESURGERE

MINES &

MINERALS INDIA LTD.

25-Jun-2010 GDR 25,015.25 53.75 LUXEMBOURG

228 FARMAX INDIA

LTD. 29-Jun-2010 GDR 27,879.44 59.93 LUXEMBOURG

229 JINDAL COTEX

LTD. 30-Jun-2010 GDR 18,057.50 38.75 LUXEMBOURG

230 JUPITER

BIOSCIENCE LTD. 02-Jul-2010 GDR 10,022.20 21.47 LUXEMBOURG

231 NU TEK INDIA

LTD. 04-Aug-2010 GDR 13,403.80 29.00 LUXEMBOURG

232 BIRLA SHLOKA

EDUTECH LTD. 06-Aug-2010 GDR 4,602.00 10.00 LUXEMBOURG

233 SOUTHERN ISPAT

& ENERGY LTD. 10-Aug-2010 GDR 4,630.00 10.00 LUXEMBOURG

234

TULSI

EXTRUSIONS LTD.

23-Aug-2010 GDR 6,679.21 14.33 LUXEMBOURG

235 COX & KINGS

LTD. 24-Aug-2010 GDR 30,413.50 65.00 LUXEMBOURG

236 SYNCOM

HEALTHCARE

LTD.

03-Sep-2010 GDR 9,684.02 20.75 LUXEMBOURG

237 SURYA

PHARMACEUTIC

AL LTD.

12-Oct-2010 GDR 11,185.00 25.00 LUXEMBOURG

238 CHROMATIC

INDIA LTD. 22-Oct-2010 GDR 15,907.79 35.78 LUXEMBOURG

239 KARUTURI

GLOBAL LTD. 22-Oct-2010 GDR 9,754.52 21.94 SINGAPORE

240 NAKODA LTD. 26-Nov-2010 GDR 11,091.95 24.25 LUXEMBOURG

241 BHORUKA

ALUMINIUM LTD. 03-Dec-2010 GDR 4,680.34 10.38 LUXEMBOURG

242 AQUA LOGISTICS

LTD. 10-Feb-2011 GDR 28,432.80 62.38 LUXEMBOURG

243 TRANSGENE BIOTEK LTD.

22-Feb-2011 GDR 10,396.00 23.00 LUXEMBOURG

244 RASOYA

PROTEINS LTD. 01-Mar-2011 GDR 14,438.40 32.00 LUXEMBOURG

SNO. COMPANY DATE INSTRUM

-ENT

ISSUE AMOUNT

STOCK

EXCHANGE

LISTING

INR

(Rs.lacs) USD mn

245 KARUR

K.C.P.PACKKAGI

NGS LTD.

17-Mar-2011 GDR 5,089.50 11.25 LUXEMBOURG

246 WINSOME YARNS

LTD. 29-Mar-2011 GDR 5,914.31 13.24 LUXEMBOURG

247

WINSOME

TEXTILE

INDUSTRIES LTD.

31-Mar-2011 GDR 4,465.00 10.00 LUXEMBOURG

248 TEXMO PIPES &

PRODUCTS LTD. 11-Apr-2011 GDR 4,420.00 10.00 LUXEMBOURG

249 VIKASH METAL &

POWER LTD. 12-Apr-2011 GDR 5,304.00 12.00 LUXEMBOURG

250

SURYACHAKRA

POWER

CORP.LTD.

26-Apr-2011 GDR 10,255.70 23.00 LUXEMBOURG

251 NEHA

INTERNATIONAL

LTD.

27-Apr-2011 GDR 8,880.00 20.00 LUXEMBOURG

252 INDOWIND

ENERGY LTD. 13-May-2011 GDR 8,151.16 18.15 LUXEMBOURG

253 PANAMA

PETROCHEM LTD. 20-Jul-2011 GDR 6,224.44 14.00 LUXEMBOURG

254 NEO CORP

INTERNATIONAL

LTD.

05-Aug-2011 GDR 10,349.49 23.10 LUXEMBOURG

255

EDSERV

SOFTSYSTEMS LTD.

10-Aug-2011 GDR 10,799.67 23.89 LUXEMBOURG

256

GEMMIA

OILTECH (INDIA) LTD.

16-Aug-2011 GDR 33,936.75 75.00

257 WELSPUN

CORP.LTD. 18-Aug-2011 GDR 52,452.08 115.00 SINGAPORE

258 INDUSTRIAL INVESTMENT

TRUST LTD.

15-Jun-2012 GDS 33,394.79 59.89 LUXEMBOURG

259 RAJ OIL MILLS

LTD. 24-Jul-2012 GDS 4,346.76 7.76 LUXEMBOURG

260 ZYLOG SYSTEMS

LTD. 25-Apr-2013 GDS 10,834.30 20.00 LUXEMBOURG

261 ZEE LEARN LTD. 22-May-2013 GDR 11,104.40 20.00 LUXEMBOURG

262 VIDEOCON D2H

LTD. 31-Mar-2015 ADR 203,420.75 325.00 NASDAQ