Title :
“A study on the international diversification in the emerging equity
market and its effect on the Indian capital market”
*SK. SAMIM FERDOWS
Email- samimstat@gmail.com
DESIGNATION: SENIOR LECTURER, (MANAGEMENT INSTITUTE OF
DURGAPUR)
AFFILIATED TO W.B.U.T.
ADDRESS FOR COMMUNICATION:
C/O GOLAM MOHIUDDIN,
58/B LASKAR DIGHI ROAD (WEST),
P.O. & P.S. BURDWAN,
DIST. BURDWAN, PIN-713101.
STATE- WEST BENGAL.
PH NO. 9832236808 (M).
1
Title:
“A study on the international diversification in the emerging equity market and its
effect on the Indian capital market”
By
Sk Samim Ferdows ( Senior Lecturer of Management Institute of Durgapur)
Abhijit Roy (Lecturer of Dr. B.C.Roy Engg. College)
ABSTRACT
With the easy transfer of money and information in cross-country markets has opened the
floodgate to the international portfolio managers for the effective utilization of fund. As
the return in the emerging markets are more with a given level of risk than that of
developed markets so the tendency of flow of funds from the developed economy
towards the emerging one is very natural and justified. This trend has made the study
about the impact of international diversification in emerging markets as an interesting
one. Further it is very much relevant to know the impact of this international
diversification on Indian capital market. In this paper an attempt has been made to
examine the impact of international diversification and its effect on Indian capital market
taking BSE and three exchanges from ASIA (Philippines, Malaysia, and Singapore) and
one from America (Mexico). The study reveals that there is a lasting impact of
international diversification on India Capital Market affected by the other emerging
markets and the flow of FIIs.
Key words: BSE , FII, International diversification, Indian capital market.
Email Id - samimstat@gmail.com
abhijitroy81@gmail.com
2
1. INTRODUCTION
Emerging markets exhibited higher intra-day volatility compared to developed markets. It
is a sign of an emerging market owing to economic and socio-political variations; the
volatility in the emerging markets is generally on the high side. Countries like Indonesia,
Brazil and South Korea, did show higher intra-day volatility. Among all the emerging
countries studied, Brazil experienced very high intra-day volatility and also extreme
value volatility followed by Indonesia, South Korea and Mexico. Intra-day volatility for
India has been computed for 13 years. Compared to most of the emerging markets
sampled here, intra-day volatility in India is low. Extreme value volatility touched its
peak in 2000 at 3.17 percent and it continuously slide in the following years and
marginally increased to 1.69 percent in 2003. Between BSE SENSEX and S&P, CNX,
Nifty, Nifty appears to be more volatile both in terms of open to close and high low
dispersions. In India open to open, volatility is always higher than close-to-close
volatility and many a times higher than open to close. This observation holds true to both
the major exchanges. Intra-day volatility in 2003 has been very slightly higher than the
immediate preceding years though nothing disturbing is evidenced. Only Nifty showed a
little more intra-day volatility compared to the previous year and to the SENSEX.
The international diversification in equity market is effected Indian capital market
because FII (Foreign Institutional Investment) and FDI (Foreign Direct Investment) are
directly invested in Indian companies with their high volume capital that directly affected
Indian Stock Market- BSE & NSE. The impact of it the SENSEX is going to be touched
17000.
The performances of the emerging equity markets are matured counterparts in the
developed world have shown repeated reversals in recent times; in the pre-Mexican crisis
period (1990-1994), most of the emerging markets performed much better compared to
the matured markets in terms of both return and associated risk, while the pattern
reversed during 1995-2001 (a period affected by the Asian crisis). In the recent past
emerging markets (those of Asia and Latin America, in particular) have shown a
remarkable recovery, in terms of both the level of return and risk, while the matured
markets have experienced drop in return and rise in risk. Such reversals of market
performances make foreign equity investment extremely volatile and may have a
destabilizing effect on the domestic economy of the recipient
country. It is therefore prudent to evolve appropriate built-in mechanisms in these
economies such that destabilization and damages can be minimized in case foreign
investors suddenly withdraw from the equity market. It is in this context that a careful
examination of the nature of foreign institutional investment (FII) flow into an economy
may help identify, the strength of various factors likely to affect such flows, and also, the
possible impact of such flows on the performance of the equity market concerned.
Globalization has meant increased cross-border capital flows, tighter links among
financial markets, and greater commercial presence of foreign financial firms around the
world. An element of the globalization trend has been the migration of securities market
activities abroad, particularly in the case of emerging markets. Many firms now cross-list
3
in global markets, including using Depositary receipts. Many stock exchanges, especially
in emerging markets, have seen trading migrate abroad. With foreign listing,
firms can obtain access to more liquid markets, attract more easily funds at lower costs
and better terms, and tap into wider investor bases. In addition, firms that operate under
weak minority shareholder protection frameworks might use the foreign listing as a signal
to their shareholders that they are willing to protect minority shareholder rights. The
share of trading abroad also seems to be on an increasing trend and advances in
technology further accelerate these trends, as remote access to foreign markets has
become increasingly easy. High liquidity increases the value of additional transactions,
leading to more concentration of order flow and even greater liquidity at global
exchanges. These developments may make it even more attractive for firms to list abroad.
In the following study an attempt has been made to identify the trend of international
diversification in emerging markets and the impact of other emerging markets on Indian
capital market.
The rest of the paper is presented as follows:
In first section the objective of the study is shown followed by the limitation of the study
in next section. In section three the details of the research methodology is explained
along with the sources of data. Section four illustrates the previous related works under
the heading review of literature. As the study is done with reference to ICICI Direct .com
so a brief the profile is depicted in fifth section. The core part of the study that is the
empirical analysis is carried on in section six. Followed by the findings and suggestion
and conclusion in section seven and eight respectively.
2. REVIEW OF THE LITERATURE
Geert Bekaert & Campbell R. Harvey (Jun 1997) defined that Returns in emerging capital
markets are very different from returns in developed markets. From average returns, they
analyze the volatility of the returns in emerging equity markets and characterize the timeseries of volatility in emerging markets & explore the distributional foundations of the
variance process. They investigate the cross-section of volatility and use measures such
as asset concentration, market capitalization to GDP, size of the trade sector, crosssectional volatility of individual securities within each country, turnover, foreign
exchange variability and national credit ratings to characterize why volatility is different
across emerging markets.
Geert Bekaert (1995) develops a return-based measure of market integration for nineteen
emerging equity markets. From his conclusions emerge, First, global factors account for a
small fraction of the time variation in expected returns in most markets, and global
predictability has declined over time. Second, the emerging markets exhibit differing
degrees of market integration with the U.S. market, and the differences are not necessarily
associated with direct barriers to investment. Third, the most important de facto barriers
to global equity-market integration are poor credit ratings, high and variable inflation,
exchange rate controls, the lack of a high-quality regulatory and accounting framework,
4
the lack of sufficient country funds or cross-listed securities, and the limited size of some
stock markets.
Geert Bekaert & Campbell R. Harvey (April 2000) proposes a cross-sectional time-series
model to assess the impact of market liberalizations in emerging equity markets on the
cost of capital, volatility, beta, and correlation with world market returns. Liberalizations
are defined by regulatory changes, the introduction of depositary receipts and country
funds, and structural breaks in equity capital flows to the emerging markets.
Michael J. Brennan and H. Henry CAO (1997) in their article developed a model of
international equity portfolio investment flows based on differences in informational
endowments between foreign and domestic investors. When domestic investors possess a
cumulative information advantage over foreign investors about their domestic market,
investors tend to purchase foreign assets in periods when the return on foreign assets is
high and to sell when the return is low.
Pavlos Petroulas (May 24, 2004) state that a lot of attention has been directed towards
recent financial crises around the world. Empirical studies have found that short-term
flows increase financial fragility and also increase the probability of financial crises. This
is not the case though for rich countries, where short-term capital flows have no effect on
growth. The results in this study indicate that opening up emerging markets capital
accounts, which imply increased short-term capital flows, is not a clear-cut way to
prosperity.
Fernando A. Broner (CREI, Universitat Pompeu Fabra) and Roberto Rigobon (MIT and
NBER and University of Maryland) (October 2004) defined that the standard deviations
of capital flows to emerging countries are 80 percent higher than those to developed
countries. First, they show that very little of this difference can be explained by more
volatile fundamentals or by higher sensitivity to fundamentals. Second, they show that
most of the difference in volatility can be accounted for by three characteristics of capital
flows: (i) capital flows to emerging countries are more subject to occasional large
negative shocks (“crises”) than those to developed countries, (ii) shocks are subject to
contagion, and (iii) shocks to capital flows to emerging countries are more persistent than
those to developed countries. Finally, they study a number of country characteristics to
determine which are most associated with capital flow volatility.
3. Objectives:
The main objectives of this study are:
 To know about the evolution of financial markets.
 To understand the changes that have recently encroached financial markets
 To know about the impact of FDI (Foreign Direct Investment) and FII (Foreign
Institutional Investment) in Indian Capital Market.
 To know the impact of other emerging equity market on Indian stock market
 To inspect the changes density brought about by the study of different factors of
changes emergence of private players.
 To critically analyze my company stands to gain from the changes to make a
comparative
 To know the future trend.
 To know about international stock market.
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4. METHODOLOGY
To achieve the above objectives, I planned to adopt the following methodology to collect
the necessary data for project For the purpose of this thesis the average return of the stock
exchange of Singapore Stock Exchange (SYMAX), Mexico Stock Exchange
(MEXBOL), Philippines Stock Exchange (FTSE), Bursa Malaysia Stock Exchange
(FBM30) and India Stock Exchange (SENSEX) has been chosen. Here Singapore,
Mexico, Philippine and Bursa Malaysia exchange has been chosen on the independent
variable and SENSEX has been chosen on the dependent variable. Taking these five
variables, MULTIPLE REGRESSION EQUATION is fitted to see the influence of these
four exchanges of emerging equity market (Singapore, Mexico, Philippine, Bursa
Malaysia) on the Indian Equity Market (SENSEX). Further a Bivariate correlation is
tested and shown in the matrix.
4.1 SOURCE OF DATA
Secondary data
The secondary data were collected from the books, magazines and website.
The index data are collected from the website of the World federation of Exchanges.
Other relevant data are collected from the respective web sites of exchanges such as BSE,
Philippines Stock Exchange, Bursa Malaysia Stock Exchange, Mexico Stock Exchange
and Singapore Stock Exchange.
5. EMPIRICAL ANALYSIS
In the era of globalization the world is becoming a global village. All most all
developing countries are going for liberalization and open market economy. Developing
countries like India, Mexico, Philippines, China, Singapore, Malaysia, and Brazil are
lifting their trade barriers to enable the foreign investors to participate in their economy.
As a result of that foreign funds in the form of Foreign Direct Investment (FDI) and
Foreign Institutional Investment (FII) are flowing in the market. As the returns of the
emerging markets is much more higher than the returns in developed market so a large
pool of investment is flowing form the developed economy towards the emerging market.
So in this days the portfolio of investors are no more bounded in the national territory
rather it is the funds are invested in the international market to make the portfolio an
international portfolio. That means for the purpose of the diversification the funds are
invested in the markets spread all over the world. Emerging markets are the first choice
of the International portfolio managers because of its above normal returns.
India is one of the fastest growing emerging markets in the world. So the flow of FII in
Indian market is obvious as a result of international diversification. These FIIs in Indian
market have a clear effect, which depicts the impact of international diversification on an
emerging market like India.
In the following literature the trend of the FII investment of India and its impact on
Indian capital market is shown. Further, as Indian capital market is proved to be an
6
efficient market in its semi strong form going towards the near strong from, the impact of
the other emerging markets on Indian Capital market is also analyzed, because these
others emerging markets are not out of the purview of international portfolio managers.
5.1 Foreign Institutional Investors- an Indian perspective
The capital market of India is one of the fastest growing markets in the world. It all
started with the liberalization of Indian economy, which was initiated with the view to
integrate it with the global economy. The process began in the year 1992 as per the
recommendations of the Narasimham Committee report on the Financial System, to open
up the countries stock markets for the direct participation of Foreign Institutional
Investors (FII). In simple terms, FII is an entity established or incorporated outside India
which proposes to make investment in India. These institutional investors include hedge
funds, insurance companies, investment trustees, pension funds, mutual funds etc.
5.2 Trend in FIIs investments in India:
With the opening up of the borders for capital movement, the foreign investments in
India have grown enormously. Starting from the liberalization period, the intervention of
FIIs in terms of their participation (refer Table-1) and quantum of investment (refer
Table-2) is gradually growing.
Table-1: Distribution of FIIs in
different years
Year
Number of FIIs
1993
1
1994
0
1995
50
1996
100
1997
29
1998
45
1999
33
2000
62
2001
50
2002
47
2003
68
2004
143
Source: www.sebi.gov.in
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Table -2: Trends in FII Investment (in US $ mn) in different years
Year
Gross Purchases
Gross Sales
Net Investment
1992-93
17.40
4
13.40
1993-94
5592.50
466.3
5126.20
1994-95
7631.00
2834.80
4796.30
1995-96
9693.50
2751.60
6942.00
1996-97
15553.90
6989.40
8574.50
1997-98
18694.70
12737.20
5957.50
1998-99
16115.10
17699.40
-1584.50
1999-00
31407.60
25619.60
5788
2000-01
74050.70
64116.30
9934.30
2001-02
49920.10
41165
8755.20
2002-03
45031.50
43232.70
1798.70
2003-04
128729.80
90568.40
38161.50
2004-05
203532.80
156354.10
47178.50
Source : www.sebi.gov.in
From the table above it is evident that in each year, except 1998-99, the net investment of
FIIs is positive. This implies the growing amount of foreign exchange reserve of our
country.
The matching of the gross purchase and gross sale of FIIs is shown in the following
chart.
Chart -1 : Trend in FII Investment
Trend in FII investment
250000
200000
150000
Gross
Purchases
100000
Gross Sales
50000
19
92
19 93
94
19 95
96
19 97
98
20 99
00
20 01
02
20 03
04
-0
5
0
5.3 Why India? :
One of the basic reasons why FIIs getting attracted towards Indian market is the
inherent strength of Indian economy. SEBI’s initiatives towards the development of
Indian stock market, like transparency, implementation of screen based trading, efficient
settlement mechanism etc, have created havoc in attracting FIIs. For the last few years
Indian stock market is giving double digit returns and is one of the best investing
8
destinations for FIIs. The P/E ratio of the market is on the higher side in comparison to
BRIC nations and other Asian markets.
5.4 Impact of the FIIs inflow on the stock market:
FIIs investments are very volatile in nature. Further the quantum of investment in FIIs
is so large that they can put a considerable impact on the movement of various indices.
The following table (Table-3) depicts the comparative amount of foreign portfolio
investment in relation to average Sensex points.
Table-3 Distribution of average sensex and Foreign Portfolio Inv. in different years.
Year
Average
Foreign Portfolio
Sensex(points)
Inv.( $mn)
1992-93
2856
244
1993-94
2899
3587
1994-95
3975
3524
1995-96
3259
2748
1996-97
3459
3312
1997-98
3813
1826
1998-99
3295
.51
1999-00
4568
3026
2000-01
4270
2760
2001-02
3332
2021
2002-03
3206
979
2003-04
4492
11377
2004-05
5741
8509
2005-06
8260
12492
The following chart shows the movement of Sensex with the inflow of foreign portfolio
investments.
Chart-2 : Movement of Sensex with FPI
14000
12000
10000
8000
6000
4000
2000
0
2004-05
2002-03
2000-01
1998-99
1996-97
1994-95
1992-93
Average
Sensex(points)
Foreign
Portfolio Inv.(
$mn)
9
5.5 Future of FIIs :
Participatory notes(PN) offer the advantage of preserving the anonymity of the
overseas investor. As of now SEBI has not banned the issuance of PN, but it has banned
FIIs from issuing PNs to unregulated entities. At the same time SEBI has amended its
definition of the regulated entities, thus making it less strict. In this way SEBI is
balancing the whole matter to create a conducive environment for the FIIs.
5.6. Impact of other emerging markets on Indian capital markets:
As Indian capital market is proved to be an efficient market in its semi strong form going
towards the near strong from, the impact of the other emerging markets on Indian Capital
market is also analyzed, because these others emerging markets are not out of the
purview of international portfolio managers. Here the impact of other emerging markets
namely Singapore, Malaysia, Filipinos, and Mexico is taken to find out their impact on
Indian capital market.
The multiple regression equation is form taken Indian stock market as dependent variable
and other emerging markets are taken as independent or explanatory variables. BSE
sensex is used as a proxy of the Indian capital market. The regression equation is fitted as
follows.
Bse = α + β1. phill+ β2.malys+ β3.mex+ β4.sing+ei
Bse = Sensex
Phill = Philippines Stock Exchange
Malys = Malaysia Stock Exchange
Mex = Mexico Stock Exchange
Sing= Singapore Stock Exchange
α = positive vertical intercept and
ei = error term
As E (ei) = 0 so we are ignoring the error term
Based on the model above the data of the five exchanges under sample are analyze taking
BSE as the impendent variable and other four exchanges such as Philippines Stock
Exchange, Malaysia Stock Exchange, Mexico Stock Exchange, Singapore Stock
Exchange as independent variables. Using the multiple regression analysis the impact of
other four exchanges on BSE is obtain. Further, correlation using Bivariate data between
all exchanges is calculated and a correlation matrix is prepared. For the purpose of
Analysis of Variance (ANOVA) the hypothesis is tasted to judge the significance of the
value of F ratio where
Null Hypothesis:
H0 = the difference in sample means is due to matter of
chance
10
Alternative Hypothesis: H1 = the difference in sample means is due to the
impact of international diversification
Apart form this individual impact of each independent variable on the dependent variable
is also soon drawing the exponential curve. The finding of the study is shown is
following section.
6. FINDINGS AND SUGGESTIONS
The analysis using the data of five stock exchanges taken under sample is showing
different relations between the dependent and independent variables. In the following
table (Table 1) the output of multiple regression analysis is shown under the heading
model summary. The analysis, giving the result of R square as 0.728 is highly significant
for the purpose of this study. This high value of R square (0.728) confirms a high degree
of impact of other stock exchanges of emerging economics on BSE SENSEX. That
means other emerging market reflecting the impact of international diversification affects
Indian capital market.
Table 4- Output summery showing R Square coefficients
Model Summary
Model
R
R Square Adjusted R Std. Error of
Square
Estimate
1
.853
.728
.629
15931.2017
the
Predictors: (Constant), SING, MEX, PHILL, MALYS
The details about the dependent and independent variables are given in the following
table 2. After minute analysis of table it is clear that Beta coefficient of Philippines and
Malaysia stock exchanges are negative which means these two exchanges have negative
or inverse impact on BSE. Other two exchanges are showing a positive Beta coefficient
out of which Singapore exchange is showing a very high value of Beta (0.810). The
overall “t” value of the study is 2.723 that are significant.
Table 5- Output summery showing Beta coefficients
Coefficients
Unstandardi
Standardiz t
zed
ed
Coefficients
Coefficien
ts
Model
B
Std. Error Beta
1
(Constant) 40561.281 14896.307
2.723
PHILL
-.978
.814
-.285
-1.201
MALYS
-.157
.136
-.320
-1.158
MEX
.494
.305
.322
1.620
SING
.615
.122
.810
5.021
a Dependent Variable: BSE
Sig.
.020
.255
.271
.133
.000
11
The analysis regarding ANOVA is given in the following table (Table 3). The essence of
ANOVA is that in this analysis the total amount of variation in set of data is broken down
into two types, that amount which can be attribute to the chance factor and that amount
which can be attributed to specified causes. So we set out Null and Alternative
Hypothesis (as stated in the previous section) as follows:
H0 = the difference in sample means is a matter of chance
H1 = the difference in sample means is due to the impact of international
diversification
The ANOVA is showing an F ratio, which is calculated as means square between the
samples divided by the means square within sample. The calculated F ratio here is 7.367,
which are much, more than the table value (3.36) at 95% confidence level. This analysis
reject the Null Hypothesis that difference in sample means is a matter of chance. The
acceptance of Alternative hypothesis proves that the difference the sample means is due
to the impact of international diversification.
Table 6 ANOVA table
Model
Sum
of df
Mean
F
Squares
Square
1
Regression 7478742130 4
186968553 7.367
.358
2.589
Residual 2791835080 11
253803189.
.257
114
Total
1027057721 15
0.614
Predictors: (Constant), SING, MEX, PHILL, MALYS
Dependent Variable: BSE
Sig.
.004
The impact of independent variables individually is shown using the following
exponential growth curve. In the following figure (Figure 1) the relationship between
observe and growth curve between BSE and Philippines exchange is clarified. The
impact of negative Beta between BSE and Philippines is clear in the growth curve. In
figure 2 and 3 also the impact of negative Beta and very low value of positive Beta on
BSE due to Malaysia and Mexico Stock Exchange respectively is clearly shown. The
impact of a very high degree of positive Beta (0.810) of Singapore exchange with BSE is
expressed in Figure 4 with an upward rising growth curve.
Figure 1 Exponential growth chart between BSE and Philippines
12
BSE
160000
140000
120000
100000
80000
60000
Observed
40000
Grow th
0
10000
20000
30000
PHILL
Figure 2 Exponential growth chart between BSE and
Mexico
BSE
160000
140000
120000
100000
80000
60000
Observed
40000
Grow th
0
20000
40000
60000
80000
100000
MEX
13
Figure 3 Exponential growth chart between BSE and
Singapore
BSE
160000
140000
120000
100000
80000
60000
Observed
40000
Grow th
0
20000
40000
60000
80000
100000
120000
SING
The correlation matrix between BSE and other four exchanges under sample is showing
low degree of negative correlation except Singapore, which is showing a high degree of
positive correlations (0.702). Other exchanges also showing positive relationship between
them except Singapore exchange having low or moderate correlations between them. The
result of the correlations would have been much more dependable if more number of
observations can be collected.
Table 7 Distribution of Correlations Matrix
BSE
PHILL
MALYS
BSE
Pearson Correlation 1.000
Sig. (2-tailed)
.
N
16
Pearson Correlation -.291
Sig. (2-tailed)
.274
N
16
Pearson Correlation -.252
Sig. (2-tailed)
.347
PHILL
-.291
.274
16
1.000
.
16
.735
.001
MALYS
-.252
.347
16
.735
.001
16
1.000
.
MEX
-.012
.964
16
.309
.244
16
.574
.020
SING
.702
.002
16
.161
.552
16
.115
.671
14
N
16
16
16
MEX
Pearson Correlation -.012
.309
.574
Sig. (2-tailed)
.964
.244
.020
N
16
16
16
SING
Pearson Correlation .702
.161
.115
Sig. (2-tailed)
.002
.552
.671
N
16
16
16
Correlation is significant at the 0.01 level (2-tailed).
Correlation is significant at the 0.05 level (2-tailed).
16
1.000
.
16
-.077
.777
16
16
-.077
.777
16
1.000
.
16
7. Limitations:
The time sires data taken for the purpose of analysis is less in number. Only sixteen
observation of each variable are abatable for the purpose of the study. Some more
observation would have made the multiple regression analysis trustworthier.
Pearson’s correlations using the Bivariate data world have been more reliable with more
number of observations.
FDI data of India an other emerging market required more insights.
As FIIs are directly related to the stock exchange, so, an index study of other emerging
market is due, as it is done in case of Indian market.
Relevant data have been collected form website without checking for its authenticity.
8. CONCLUSIONS AND RECOMMENDATIONS
Over the past decade India has gradually emerged as an important destination of global
investors' investment in emerging equity markets. In this paper we explore the
relationship of foreign institutional investment (FII) flows to the Indian equity market
with its possible impact based on a time series of yearly data for the period 1992-03 to
2005-06. Here we try to identify the relevant covariates of FII flows into and out of the
Indian equity market and also to determine the nature of causality between the relevant
variables. We incorporate into the analysis variables that appear, a priori, to be the
primary determinants of global investors' demand/supply for/of stocks in the Indian
market. The variables taken are reflecting yearly volatility (representing risk) in
domestic and international equity markets, based on the BSE SENSEX, Philippines Stock
Exchanges, Malaysia Stock Exchange, Mexico Stock Exchange and Singapore Stock
Exchange as well as measures of co-movement of impact in these markets (with the
relevant betas). In this study several macroeconomic variables like daily returns on the
Rupee-Dollar exchange rate, short run interest rate and index of industrial production
(IIP); that are likely to affect foreign investors' expectation about returns in the equity
market is not considered, which needed special attention. The data set embodies year-toyear variations and hence, is better suited for examination of various interrelationships of
equity. Also, we relate yearly FII flows to the exchange index values mentioned above
combining three kinds of flows, namely, FII flows into the country or FII purchases, FII
15
flows out of the country or FII sales and the net FII inflows into the country or FII net.
Our results show that, though there is a general perception that FII activities exert a
strong demonstration effect and thus drive the domestic stock market in India, evidence
suggests that FII flows to and from the Indian market tend to be caused by return in the
domestic equity market and not the other way round. The regression analysis, in various
stages, reveals that returns in the Indian equity market are indeed an important (and
perhaps the single most important) factor that influences FII flows into the country.
While, the dependence of net FII flows on daily return in the domestic equity market (at a
lag, to be more specific) is suggestive of foreign investors' return-chasing behavior, the
recent history of market return and its volatility in emerging and domestic stock markets
have some significant effect as well. However, while FII sale (and FII net inflow) is
significantly affected by the performance of the Indian equity market, FII purchase is not
responsive to this market performance. Looking at the role of the betas of the Indian
market with respect to the Philippines Stock Exchanges, Malaysia Stock Exchange,
Mexico Stock Exchange and Singapore Stock Exchange indices it is concluded that
foreign institutional investors do not seem to use the Indian equity market for the purpose
of diversification of their investments. It is also seen that return from exchange rate
variation and fundamentals of the emerging economies may have strong influence on
international diversification decisions. Policy implications that emerge are that a move
towards a more
Liberalized regime, in the emerging market economies like India, should be accompanied
by further improvements in the regulatory system of the financial sector. To fully reap the
benefits of capital market integration, in India (and other countries having thin and
shallow equity markets) the prime focus should be on regaining investors' confidence in
the equity market so as to strengthen the domestic investor base of the market, which in
turn could act as a built-in cushion against possible destabilizing effects of sudden
reversal of foreign inflows.
16
LIST OF TABLES & ILLUSTRATIONS
Table – 1: Trends in FII Investment
Table – 2: Trends in FII Investment
Table – 3: Impact of the FIIs inflow on the stock market
Table – 4: Model specification
Table – 5: Coefficients
Table – 6: ANOVA
Table – 7: Correlation Matrix
APPENDICES 1: Summary Statistics
APPENDICES 2: FDI Inflows in the East Asian developing
countries
Chart – 1: Trend in FII Investment
Chart – 2: Movement of SENSEX with FPI
Figure – 1: Exponential growth chart between BSE and
Philippines
Figure – 2: Exponential growth chart between BSE and
Mexico
Figure – 3: Exponential growth chart between BSE and
Singapore
17
ABBREVIATIONS
FII = Foreign Institutional Investment
FDI = Foreign Direct Investment
BSE = Bombay Stock Exchange
NSE = National Stock Exchange
IPO = Initial Public Offer
FPI = Foreign Portfolio Investment
BTST = Buy Today Sell Tomorrow
MF = Mutual Fund
NAV = Net Assets Value
SIP = Systematic Investment Plans
ADR = Average Daily Return
IIP = Index of Industrial Production
18
REFERENCES






Bekaert G and Campbell R H (1995), “ Time Varying World Market Integration”,
Journal of Finance, Volume 50, pp. 403-444.
C. R. Kothari, Research Methodology – Methods and Techniques, New Age
International Publishers, second edition (2004), pp. 256-264.
Chee-Keong Choong and Kian-Ping Lim (2007), “Foreign Direct Investment in
Malaysia: An Economic Analysis”, The ICFAI Journal of Applied Economics,
Volume 6 no. 1, pp. 75.
Joydeep Biswas (2007), “Emerging Equity Market: A Cross-country Time Series
Analysis”, The ICFAI Journal Of Applied Finance, Volume 13 No. 7, pp. 55.
M. T. Raju and Anirban Ghosh (2004), “Stock Market Volatility an International
Comparison”, SEBI Working Paper Series No. 8
Websites of BSE, Philippines Stock Exchange, Malaysia Stock Exchange, Mexico
Stock Exchange, Singapore Stock Exchange.
APPENDIX 1
Summary Statistics
Market
Capitalization
Ratio
Mean SD
Turnover
Ratio
Mean
SD
Indonesia
0.227
0.133
0.522
0.342
Thailand
0.319
0.239
0.792
0.237
India
0.312
0.143
0.829
0.753
Malaysia
1.458
0.685
0.384
0.184
Philippin
es
Korea
0.464
0.265
0.261
0.193
0.416
0.270
2.210
0.939
Pakistan
0.185
0.092
1.687
1.698
Banglade
sh
0.028
0.034
0.451
0.260
Valuetraded
Ratio
Mea SD
n
0.11 0.05
1
8
0.32 0.23
6
0
0.34 0.32
6
9
0.65 0.53
8
9
0.12 0.11
3
1
1.04 0.80
9
5
0.17 0.14
1
8
0.01 0.00
1
8
Growth
of
Listed
Companies
Mea SD
n
0.03 0.044
6
0.02 0.134
7
0.11 0.066
0
0.06 0.050
9
0.01 0.016
5
0.13 0.435
2
0.00 0.023
3
0.03 0.020
4
Risk
Mea
n
0.16
5
0.19
1
0.22
2
0.08
0
0.10
3
0.09
8
0.17
1
0.13
3
Market
Integration
SD
Mean
SD
4.546 0.649
0.213
6.368 0.405
0.246
4.050 0.121
0.193
5.478 0.189
0.116
4.347 0.271
0.098
6.587 0.502
0.214
6.240 0.124
0.320
5.560 0.282
0.274
19
Sri Lanka 0.110
0.051
0.158
0.059
0.01
7
0.01
2
0.00
6
0.020
0.16
9
4.554 0.018
0.150
APPENDIX II
FDI Inflows in the East Asian Developing Countries
Country/Group FDI Inflows (Million of Dollars)
1970 1980 1985 1990 1995 1997
1998
Developing
788 395 5191 24230 75293 107205 95599
Countries: Asia
China
57
1659 3487 25849 44237 43751
China,
Hong 50
710 -267 3275 6213 11368 14776
Kong SAR
Indonesia
83
180 310 1092 4346 4677
-356
Korea
66
6
234 789
1776 2844
5412
Malaysia
94
934 695 2611 5816 6513
2700
Philippines
-25
-106 12
550
1459 1249
1752
Singapore
93
1236 1047 5575 8788 12967 6316
Thailand
43
189 160 2542 2004 3627
5143
Source: UNCTAD (2002), Division on Investment, Technology and
The
source
also
can
be
www.UNCTAD.org./en/subsite/dite/fdistats_files/fdistats.htm
1999 2000
2001
99728 143479 102066
40319 40772
24591 64448
46846
22834
-2745 -4550
-3277
10598 10186 3198
3532 5542
554
737
1489
1792
7197 6390
8609
3562 2448
3759
Enterprise Development.
obtained
at:
20