relationship between fii flows and nifty index

8/7/2019 Relationship Between FII Flows and Nifty Index

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IMPACT OF FII ON INDIAN MARKET

-M P BIRLA INSTITUTE OF MANAGEMENT- 1 -

RESEARCH PROJECT

OnDETRMINATION OF RELATIONSHIPBETWEEN FII FLOWS

AND NIFTY INDEX

Submitted in partial fulfillment of the requirement for MBA

Degree of Bangalore University

BY

CHIPPLAKATTI SUNIL SUKUMARRegistration Number

04XQCM6019

Under the guidance of

DR T V N RAO

M.P.Birla Institute of Management

Associate Bharatiya Vidya Bhavan

Bangalore-560001

2004-2006


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DECLARATION

I hereby declare that the research project titled DETRMINATION OF

RELATIONSHIPBETWEEN FII FLOWS AND NIFTY INDEX is prepared under

the guidance of Dr T V N Rao in partial fulfillment of MBA degree of Bangalore

University, and is my original work.

This project does not form a part of any report submitted for degree or diploma

under Bangalore University or any other university.

Place: Bangalore Chippalakatti Sunil

Skumar


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PRINCIPALS CERTIFICATE

This is to certify that Mr.Chippalakatti Sunil Sukumar bearing

Registration No: 04XQCM6019 has done a research project on DETRMINATION

OF RELATIONSHIPBETWEEN FII FLOWS AND NIFTY INDEX under the

guidance ofDr T V N Rao M.P. Birla Institute of Management, Bangalore. This has

not formed a basis for the award of any degree/diploma for any other university.

Place: Bangalore Dr.N.S.MALLAVALLI

Date: PRINCIPAL

MPBIM, Bangalore


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GUIDES CERTIFICATE

I hereby declare that the research work embodied in this dissertation

entitledDETRMINATION OF RELATIONSHIPBETWEEN FII FLOWS AND

NIFTY INDEXhas been undertaken and completed by Mr. Chippalakatti Sunil

Skumar under my guidance and supervision.

I also certify that he has fulfilled all the requirements under the

covenant governing the submission of dissertation to the Bangalore University for the

award of MBA Degree.

Place: Bangalore Dr T V N Rao

Date: Research Guide

MPBIM, Bangalore


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ACKNOWLEDGEMENT

The successful accomplishment of any task is incomplete without

acknowledging the contributing personalities who both assisted and inspired and lead

us to visualize the things that turn them into successful stories for our successors.

First of all I thank the Almighty God for his grace bestowed on us throughout this

project.

My special thanks to my project Guide Dr T V N Rao, who guided me with the

timely advice and expertise and has helped remarkably to complete the project.

Last, but not the least, I would like to thank my Parents and all my Friends

for their wholehearted direct and indirect support and encouragement.


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CHAPTER CONTENTS PAGE

NO.

ABSTRACT

1.

2.

3.

4.

5.

6.

INTRODUCTION:

THOEORETICAL CONSIDERATIONS

LITERATURE REVIEW:

RESEARCH METHODOLOGY:

INTRODUCTION PROBLEM STATEMENT OBJECTIVES METHODOLOGY SCOPE OF THE STUDY SAMPLE OF SIZE DATA DATABASE

DATA ANALYSIS:

TEST FOR UNIT ROOT (ADF &PP) RESULTS FROM ADF & PP RESULTS FROM GRANGERS CAUSALITY

TEST TABLES.

FINDINGS AND CONCLUSION:

LIMITATION OF THE STUDY

1-15

16-26

27-30

31-40

41

42

BIBLIOGRAPHY: 43


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INTRODUCTION

Foreign Institutional Investment in India: An Overview

SEBIs definition of FIIs presently: Includes foreign pension funds, mutual funds,

charitable/endowment/university funds etc. As well as asset management companies

and other money managers operating on their Behalf

India embarked on a programme of economic reforms in the early 1990s to tie over

its balance of payment crisis and also as a step towards globalization. An important

milestone in the history of Indian economic reforms happened on September 14, 992,

when the FIIs (Foreign Institutional Investors) were allowed to invest in all thesecurities traded on the primary and secondary markets, including shares, debentures

and warrants issued by companies which were listed or were to be listed on the stock

exchanges in India and in the schemes floated by domestic mutual funds. Initially, the

holding of a single FII and of all FIIs, NRIs (Non-Resident Indians) and OCBs

Overseas Corporate Bodies) in any company were subject to a limit of 5% and 24%

of the companys total issued capital respectively. In order to broad base the FII

investment and to ensure that such an investment would not become a camouflage for

individual investment in the nature of FDI, a condition was laid down that the funds

invested by FIIs had to have at least 50 participants with no one holding more than

5%. Ever since this day, the regulations on FII investment have gone through

enormous changes and have become more liberal over time.

Net FII inflows into India increased steadily through the decade of the 1990s to reach

an annual peak of US$10.25 billion in 2004-05 Cumulatively, FII investments as on

October 31, 2005 have been US$ 39.27 billion.1 every year since FIIs were allowedto participate in the Indian market, FII net inflows into India have been positive,


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Except for 1998-99. This reflects the strong economic fundamentals of the country, as

well as the confidence of the foreign investors in the growth with stability of the

Indian market. The year 2003 marked a watershed in FII investment in India. FIIs

started the year 2003 in a big way by investing Rs. 985 crore in January itself.

Meanwhile, corporate India continued to report good operational results. This, along

with good macroeconomic fundamentals, growing industrial and service sectors led

FIIs to perceive great RBI data generally shows that investment by FIIs has been

smaller, when compared with SEBI data. This discrepancy in the statistical system

needs to be corrected. One possible explanation may involve differences in the

treatment of reinvestment of profit earned. Potential for investment in the Indian

economy. In April 2003, prices of commodities like steel and aluminum went up,

propelling FII investment in May 2003 to Rs. 3,060 crore. Around the same time,

Morgan Stanley Capital International (MSCI) in its MSCI Emerging Markets Index

gave a weight of 4.3 per cent to India among the emerging markets of the world.2

Calendar year 2004 ended with net FII inflows of US$9.2 billion, an all-time highsince the liberalization.


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FII Investments in India

FOREIGN INVESTMENT INFLOWS

Year A. Direct investment B. Portfolio investment Total (A+B)

Rs. crore US $ million Rs. crore US $ million Rs. crore US $ million

1 2 3 4 5 6 7

1990-91 174 97 11 6 185 103

1991-92 316 129 10 4 326 133

1992-93 965 315 748 244 1713 559

1993-94 1838 586 11188 3567 13026 4153

1994-95 4126 1314 12007 3824 16133 5138

1995-96* 7172 2144 9192 2748 16364 4892

1996-97* 10015 2821 11758 3312 21773 6133

1997-98* 13220 3557 6696 1828 19916 5385

1998-99* 10358 2462 -257 -61 10101 2401

1999-00* 9338 2155 13112 3026 22450 5181

2000-01* 18406 4029 12609 2760 31015 6789

2001-02* 29235 6130 9639 2021 38874 8151

2002-03* 24367 5035 4738 979 29105 6014

2003-04* 21473 4673 52279 11377 73752 16050

2004-05* P 24870 5535 40029 8909 64899 14444


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-M P BIRLA INSTITUTE OF MANAGEMENT- 10-

FII Investment (% of GDP):

FII flows to India

Foreign investment inflows to india

-10000

0

10000

2000030000

40000

50000

60000

1990-91

1991

-92

1992

-93

1993

-94

1994

-95

1995

-96

1996

-97

1997-98

1998-99

1999-00

2000-01

2001

-02

2002-03

2003-04

2004-05

incrs

direct investment portfolio investment


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Growth of FII

Growth of FII

0

10000

20000

30000

40000

50000

60000

70000

80000

90-9191-9292

-9393

-9494

-9595

-9696

-9797-9898-9999-0000-012-Jan

3-Fe

b4-Mar

5-Ap

r

fiiinvestment

0

50000

100000

150000

200000

250000

300000

350000

400000

cuma

lativefiiinvestment

f ii investment cum fii

The sources of FII in India:

The closed-end country fund, The India Fund launched in June 1986 provided a

channel for portfolio investment in India before the stock market liberalization in

1992. Global Depository Receipts, American Depository Receipts, Foreign Currency

Convertible Bonds and Foreign Currency Bonds issued by Indian companies and

traded in foreign exchanges provide other routes for portfolio investment in India by

foreign investors. It is also possible for foreigners to trade in Indian securities withoutregistering as an FII but such cases require approval from the RBI or the Foreign

Investment Promotion Board. That these national affiliations do not necessarily mean

that the actual investor funds come from these particular countries. Given the

significant financial flows among the industrial countries, national affiliations are


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very rough indicators of the home of the FII investments. In particular institutions

operating from Luxembourg, Cayman Islands or Channel Islands, or even those based

at Singapore or Hong Kong are likely to be investing funds largely on behalf of

residents in other countries. Nevertheless, the regional breakdown of the FIIs does

provide an idea of the relative importance of different regions of the world in the FII

flows

The trickle of (FII) flows to India that began in January 1993 has gradually expanded

to an average monthly inflow of close to Rs. 4100 crores during the last six Months of

2005. Over 740 FIIs were registered with SEBI by end of 2005. The total Amount of

(FII) investment in India had accumulated to a formidable sum of over Rs. 3,50,000

crores during these timeThe sources of these FII flows are varied. The FIIs registered

with SEBI come from as many as 28 countries (including money management

companies operating in India on behalf of foreign investors). US-based institutions

accounted for slightly over 42%, those from the UK constitute about 20% with other

Western European countries hosting another 17% of the FIIs


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Holdings of the FII in Indian Company:

Most of there subsidiary FII having majority share and also There are so many Indian

companies where FII having more than 10% of share, following are the table shows the

shareholding pattern of FII in Nifty and Non nifty companies and the top 25 companies where

FII having more holdings.


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TOP 25 companies were FII holdings

Evolution of Policies and Regulation:


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Domestic institutional and individual investors, used as they are to the ongoing

practices of Indian corporates, often accept such practices, even when these do not

measure up to the international benchmarks of best practices. FIIs, with their vast

experience with modern corporate governance practices, are less tolerant of

malpractice by corporate managers and owners (dominant shareholder). FII

participation in domestic capital markets often lead to vigorous advocacy of sound

corporate governance practices, improved efficiency and better shareholder value.

Improvements to market efficiency:

A significant presence of FIIs in India can improve market efficiency through two

channels. First, when adverse macroeconomic news, such as a bad monsoon, unsettles

many domestic investors, it may be easier for a globally diversified portfolio manager

to be more dispassionate about India's prospects, and engage in stabilizing trades.

Second, at the level of individual stocks and industries, FIIs may act as a channel

through which knowledge and ideas about valuation of a firm or an industry can more

rapidly propagate into India. For example, foreign investors were rapidly able to

assess the potential of firms like Infosys, which are primarily export-oriented,

applying valuation principles that prevailed outside India for software servicescompanies.


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Costs:

There are concerns that foreign investors are chronically ill informed about India, and

this lack of sound information may generate herding (a large number of FIIs buying

or selling together) and positive feedback trading (buying after positive returns,

selling after negative returns). These kinds of behavior can exacerbate volatility, and

push prices away from fair values. FIIs behavior in India, however, so fardoes not

exhibit these patterns.

There are concerns that in an extreme event, there can be a massive flight of foreign

capital out of India, triggering difficulties in the balance of payments front. India's

experience with FIIs so far, however, suggests that across episodes like the Pokhran

blasts, or the 2001 stock market scandal, no capital flight has taken place. A billion or

more of US dollars of portfolio capital has never left India within the period of one

month. When juxtaposed with India's enormous current account and capital account

flows, this suggests that there is little evidence of vulnerability so far.40

Possibility of taking over companies:While FIIs are normally seen as pure portfolio investors, without interest in control,

portfolio investors can occasionally behave like FDI investors, and seek control of

companies that they have a substantial shareholding in. Such outcomes, however,

may not be inconsistent with India's quest for greater FDI. Furthermore, SEBI's

takeover code is in place, and has functioned fairly well, ensuring that all investors

benefit equally in the event of a takeover.

Complexities of monetary management

A policymaker trying to design the ideal financial system has three objectives. The

policy maker wants continuing national sovereignty in the pursuit of interest rate,

inflation and exchange rate objectives; financial markets that are regulated,


21/51



supervised and cushioned; and the benefits of global capital markets. Unfortunately,

these three goals are incompatible. They form the impossible trinity. India's

openness to portfolio flows and FDI has effectively made the countrys capital

account convertible for foreign institutions and investors. The problems of monetary

management in general, and maintaining a tight exchange rate regime, reasonable

interest rates and moderate inflation at the same time in particular, have come to the

fore in recent times. The problem showed up in terms of very large foreign exchange

reserve inflows requiring considerable sterilization operations by the RBI to maintain

stable macroeconomic conditions. The Government had to introduce a Market

Stabilization Scheme (MSS) from April 1, 2004.

With the foreign exchange invested in highly liquid and safe foreign assets with low

rates of return, and payment of a higher rate of interest on the treasury bills issued

under MSS, sterilization involves a cost. With a rapid rise in foreign exchange

reserves, and the need for having an MSS-based sterilization involving costs,

questions have been raised about the desirability of encouraging more foreign

exchange inflows in general and FII inflows in particular. While there is indeed the

issue of timing the policy of encouragement appropriately, to avoid the pitfalls ofthrowing the baby with the bath water, there can not be a turnaround from the

avowed policy of gradual liberalization,


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2. Literature review

FII Flows to India Nature and Causes (RAJESH CHAKRABARTI 2001).

Introduction:

International capital flows and capital controls have emerged as important policy

issues in the Indian context as well. The danger of Mexico-style abrupt and sudden

outflows inherent with FII flows and their destabilizing effects on equity and foreign

exchange markets have been stressed. Some authors have argued that FII flows have,

in fact, had no significant benefits for the economy at large. While these concerns are

all well placed, comparatively less attention has been paid so far to analyzing the FII

flows data and understanding their key features. A proper understanding of the nature

and determinants of these flows, however, is essential for a meaningful debate about

their effects as well as for predicting the chances of their sudden reversals. In an

attempt to address this lacuna, this paper undertakes an empirical analysis of FII

investment flows to India. The broad objective of the present paper is to gain a better

understanding of the nature and determinants of FII flows. Towards this end we first

take a look at the FII investment flows data to bring out the key features of these

flows. Next we study the relationship between FII flows and the stock market returns

in India with a close look at the issue of causality. Finally we study the impact of

other factors identified in the portfolio flows literature on the FII flows to India. In all

of these investigations we make a distinction between the pre-Asian crisis period and

the post-Asian crisis period to check if there was a regime shift in the relationships

owing to the Asian crisis.


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Methodology:

To Study the relationship between FII flows and possible economic factors affecting

it, particularly stock returns in the Indian market. They conduct the Pair-wise Granger

causality tests between net FII inflows and monthly return on the BSE Index. Before

conducting the Granger causality tests author made ADF and PP test for check the

collected data are stationary or not,

Granger causality tests was conducted for 3 period

Panel A: Entire Sample: May1993 Dec 1999

Panel B: Pre-Asian Crisis period: May 1993 June 1997

Panel C: Asian Crisis and after: July 1997 Dec 1999

Collection of data:FII net flows from May 1993 to Dec 1999

Bse index monthly return from May 1993 to Dec 1999

Hypothesis:

H0: Returns do not cause FII flows

H0: Flows do not cause returns


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Main Findings and Conclusion:

This empirical investigation of FII flows to India has elicited the following stylized

facts about such flows:

1. FII flows are correlated with returns in the Indian markets.

2. This high correlation is not necessarily evidence of FII flows Causing price

pressureif anything, the causality is likely to be the other way around.

3. A collection of domestic and international variables likely to affect both flows

and returns fails to diminish the importance of returns in explaining FII flows.

4. Since the US and world returns are not significant in explaining The FII flows,

there is no evidence1of any informational Disadvantage of FIIs in comparison

with the domestic investors in India.

5. There appears to be significant differences in the nature of FII flows before

and after the Asian crisis. In the post Asian crisis period it seems that the

returns on the BSE National Index have become the sole driving force behind

FII

An Analysis of Stock Market Efficiency in the Light of Capital Inflows

and Exchange Rate Movements: The Indian Context (BHATTACHARYA &

MUKHERJEE)

Introduction:

There are number of studies on exchange rate affecting stock prices directly. Theory

explained that a change in the exchange rates would affect a firms foreign operation

and overall profits. This would, in turn, affect its stock prices. The nature of the

change in stock prices would depend on the multinational characteristics of the firm.


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Conversely, a general downward movement of the stock market will motivate

investors to seek better returns elsewhere. This decreases the demand for money,

pushing interest rates down, causing further outflow of funds and hence depreciating

the currency. While the theoretical explanation was clear, empirical evidence was

mixed. If FIIs use positive feedback trading strategies, causality may run from stock

prices to foreign investment. The portfolio balancing efforts of foreign investors

would also put pressure on demand for (or supply) of currency, which may affect its

exchange rate. On the other hand, the payoff of foreign investors depends on

exchange rate movements as well as on stock price movements, and they may

rebalance their portfolio in response to an (an anticipated) change in exchange rate.

The relationship of FII investment with stock prices on the one hand, and with

exchange rate on the other hand may produce indirect relation between exchange rate

and stock prices

Methodology and Data Sources:

TO test for the causal relationship between two variables, the standard Granger

(1969) test has been employed. This test states that, if past values of a variable Y

significantly contribute to forecast the value of another variable Xt+1 then Y is said to

Granger cause X and vice versa.

Unit Root Test:

Empirical studies (for example, Engle and Granger, 1987) have shown that many

time series variables are non-stationary or not integrated of order zero. The time

series

variables considered in this paper are the stock prices and seven macroeconomic

variables, namely, money supply, index of industrial production, real GDP, rate of

inflation, real effective exchange rate, foreign exchange reserves and value of trade


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balance. In order to avoid a spurious regression situation the variables in a regression

model must be stationary or cointegrated. Therefore, in the first step, we perform unit

root tests on these eight time series variables to investigate whether they are

stationary or not. The Augmented Dickey-Fuller (ADF) unit root test is used for this

purpose.

The tests are based on the null hypothesis (H0): Yt is not I (0). If the

calculated ADF statistics are less than their critical values from Fullers table,

then the null hypothesis (H0) is accepted and the series are non-stationary.

Data collection:

They used monthly data series for three variables for the period Jan 1993 to Mar2005.

The monthly return on stock prices is calculated by taking a percentage change in the

BSE Sensitive

Net investments by FIIs (in equities) in the Indian capital market and The indices of

Real Effective Exchange Rate of the Indian Rupee (36-country bilateral weight with

base 1985=100).

The major findings are:

1. A bi-directional causality between stock price and the net foreign institutional

Investment, thus implying that the market informational efficiency hypothesis

Can be rejected for BSE Sensitive Index with respect to the FII,

2. Uni-directional causality runs from change in exchange rate to stock returns

(At 10% level of significance), not vice versa, implying that the exchange rate

Movements lead the BSE sensitive index, and

3. No causal relationship exists between exchange rate and net investment by

FIIs.


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IN THE INDIAN EQUITY MARKET: A FIRM LEVEL ANALYSIS

(Khan Masood ahmad, Shahid Ashraf, Shahid Ahmed)

Introduction:

The FII investment in India, as a percentage of market capitalization, has been

improving. It ranged between 8 to 10% during 2002-04. Further, the percentage of

FIIs shareholding improves if we consider only the floating stock of the companies.

The FIIs have also been very enthusiastic in subscribing to some of the large IPOs of

government enterprises like Maruti, ONGC and NTPC, as well as private companies

like TCS. If we focus on the FIIs shareholding in some top market capitalized

companies ranging from government owned to private companies across software,

petroleum, finance and old economy, the FIIs shareholding as percentage of total

equity seems to range from a low of 1.88% to a high of 62.04%. Invariably, in all the

government owned companies, the FIIs are the second largest shareholders after the

government. The lowest FIIs shareholding are in Indian Oil and Steel Authority. In

both of these companies the government shareholding is above 80%. Further dilution

of equity will most probably improve the FIIs shareholding in these companies. Two

major financial institutions, ICICI Bank and HDFC, with no Indian promoters, have

majority shareholding of the FIIs. If we exclude the shares of the promoters and

consider only the possible floating stock then the percentage of FIIs holding would go

up substantially, and the chances of price influencing trades on these stocks would

also go up. The retail investors with their individual small trades would hardly affectthe market and the influence of the mutual funds and UTI would also possibly below.

The role of FIIs becomes important in influencing equity returns at the firm level,

especially in the government owned companies. It seems that FIIs are value investing


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in anticipation of further reforms that is driving up the equity returns. There is

volatility clustering in individual series but no transmission from one to another,

except for one key company. Therefore, their is very little destabilizing effect of FII

flows on individual equity returns of the firms during the period of study.

Methodology:

The present study attempts to analyze daily equity returns at the firm level with that

of FIIs net investments. As data on FIIs individual trades on specific firms are not

available publicly, the analysis is confined to the daily aggregate FIIs investments.

Even though the FIIs flows are taken in the aggregate it does give an overall picture

of the investment environment. The study has analyzed 36 firms listed on the NSE,

forming part of the NSE Nifty and they give a reasonable representation of the market

capitalization.

We conduct a Granger causality test between the FII and market returns (R) to see the

direction of causality at the firm level. For any time series analysis, all data series

must be stationary. Stationarity condition has been tested using Augmented Dickey

Fuller (ADF) and Phillips Perron tests (Dickey and Fuller, 1979, 1981; Enders, 1995;Gujarat, 2003; Phillips and Perron, 1988).

GARCH Model:

Volatility in individual series and spillover effect on each other has wider economic

implications. The volatility of individual series has been tested by applying GARCH

MODEL (Generalized ARCH).

Spillover effect of volatility:

In order to test the spillover effect of volatility of one series to another series, they

apply Granger causality test on residuals generated from GARCH mean equation.


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Collection of data:

The daily data was collected from August 2002 to August 2004.

Returns of 36 listed companies

Net FII flows

The analysis has been carried out to capture the lead lag dynamics between net equity

purchases by FIIs and equity returns at the firm.

Hypotheses:

Ho: Firm level returns do not Granger-cause FII flows.

Ho: FII flows do not Granger/cause Firm level returns.

Ho: there is no volatility in the individual series.

Ho: FII volatility does not influence volatility of Firm level returns.

Ho: Volatility of Firm level returns does not influence FII volatility.

Findings:

Existence of bi-directional causality between stock returns and FII flows and

vice-versa in 13 firms,

Uni-directional causality running from stock returns to FII flows in 21 firms.


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FOREIGN INSTITUTIONAL INVESTMENT IN THE INDIAN

EQUITY MARKET

(Paramita mukherjee, Suchismita bose and Dipankor coondoo)

This paper explores the relationship of foreign institutional investment (FII) flows to

the Indian equity market with its possible covariates based on a daily data-set for the

period January 1999 to May 2002. The set of possible covariates considered

comprises two types of variables. The first type includes variables reflecting daily

market return and its volatility in domestic and international equity markets as well as

measures of co-movement of returns in these markets (viz., relevant betas). The

second type of variables, on the their hand, are essentially macroeconomic ones like

exchange rate, short-term interest rate and index of industrial production (IIP)viz.,

variables that are likely to affect foreign investors expectation about return in Indian

equity market.

Methodology:

TO test for the causal relationship between two variables, the standard Granger(1969) test has been employed. This test states that, if past values of a variable Y

significantly contribute to forecast the value of another variable Xt+1 then Y is said to

Granger cause X and vice versa.

In this paper they Used

Grangers causality test find out Direction of causation between FII flows and Return

in the Indian stock market

Multiple regression models had been used to find the relation between the FII flows

and other variables


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Collection of Data:

Daily data set for the period January 1999 to May 2002 collected for the following

variables:

Daily return in the Indian market calculated on the basis of day to day

variations in the value of BSE Sensex

Volatility of daily return in the Indian market calculated as the standard

deviation of previous 7/ 15/ 30 days daily returns based on the BSE Sensex

Daily return in the international equity market based on the day to day

variations in the value of the MSCI World Index

Daily return in the US equity market based on the day to day variations in theS&P500

Volatility of daily return in the international equity market calculated as the

standard deviation of previous 7/ 15/ 30 days daily returns based on MSCI

World index

Volatility of daily return in the US equity market calculated as the standard

deviation of previous 7/ 15/ 30 days daily returns based on the S&P500 index

Extent of co-movement of daily returns in Indian and International equity

markets as measured by the beta of returns from BSE Sensex and MSCI

World Index

Extent of co-movement of daily returns in Indian and the US equity markets

as measured by the beta of returns from BSE Sensex and S&P500 Index

Daily return from day to day variations in the RupeeUSD exchange rate

The second set, on the other hand, includes two macroeconomic variablesviz., the

index of industrial taken as a proxy for short run real income changes and the call

money rate henceforth denoted by CMR) taken as a proxy for short term interest rate.

These two variables, taken to reflect the short run variations in the fundamentals of


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the Indian economy, have been used together with the equity market-related variables

to see whether or not global investors take into account their expectations about the

state of the Indian economy. The sample period of the daily data set is January

1999May 2002, which wholly relates to the post- Asian crisis period. For a fuller

description of these variables and the sources of data on them,

Findings and conclusion:

Flows to and from the Indian market tend to be caused by return in the

domestic equity market and not the other way round;

Returns in the Indian equity market is indeed an important (and perhaps the

single most important) factor that influences FII flows into the country;

While FII sale and FII net inflow are significantly affected by the performance

of the Indian equity market, FII purchase is not responsive to this market

performance;

FII investors do not seem to use Indian equity market for the purpose of

diversification of their investment;

Return from exchange rate variation and fundamentals of the Indian economymay have

Influence on FII decisions, but such influence does not seem to be strong, and;

Daily FII flows are highly auto-correlated and this auto-correlation could not

be accounted for by the all or some of the covariates considered.


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3.1) INTRODUCTION:

Over the past ten years India has gradually emerged as an important destination of

global investors investment in emerging equity markets. Today India has a share of

about 20 per cent in the total global investment in all emerging equity markets

together and the outstanding FII investment in India stood around Rs.86, 287crore,as

on end march, 2002.FII investments as a percentage of market capitalization

increased from7.06 per cent in 1999-00,to 13.5per cent in 2000-01 and further to 14.1

per cent in 2001-02.Given this growing importance of FII for the Indian economy and

in year 2005 only FII are invested more than 47000 crs, It is apparent that the nature

and causation of such fund flows deserve careful examination.

3.2) PROBLEM STATEMENT:

Stock markets become more receptive to foreign investment as the economy liberalizes.

The process of liberalization leads to stock price appreciation followed by in flows from

foreign investors. A concern with the entry of FIIs is that they are positive feedback

traders, buying when the market increases and selling when the market falls. This could be

destabilizing as the sales would lead the stock market to fall and buys would make the

stock market go up. These traders could possibly push the stock prices away from the

fundamentals. Gray area of the study is analyze the relationship between the FII net flow

and return from the stock market and what extent they are correlated with each other.


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3.3) OBJECTIVE OF THE STUDY:

The present study has been undertaken to meet the following specific

objectives,

To Check the impact of Net FII Flows And also Purchase made by the

FII (i.e. only inflow) to stock market

To examine the empirical relationship between FII net flows and Stock

market return (S&P CNX nifty)

To examine the empirical co-movements between the FII net flows and

Stock market return (S&P CNX nifty)

3.4) METHODOLOY:

The present study deals with the analyses of relation between two variables

namely FII net flows and Stock market return; to study the relationship between these

two variables we are conducting the Grangers causality test.

For conduct Grangers causality test the time series must be stationary, to calculate

stationarity condition has been tested using augmented dickey fuller test.

Augmented dickey fuller test is based on the following regression:

The following are the methodology to check for Stationarity,

Stationarity:

Ho: = 0

H1: < 1.


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If the null hypothesis of only a unit root cannot be rejected, then the stock prices

follow a random walk.

The existence of unit roots is firstly tested using the Augmented Dickey-Fuller test

(ADF) (Dickey and Fuller, 1981) through the following relationship:

St = + T + St-1 + St-1 + t

Where tS = t S t1 S,t S is the index of the spot market, and kis chosen so that

the deviations t u to be white noise. The same relationship is used to determine the

order of the futures price index (t F). The null and the alternative hypothesis for theexistence of unit root in t S and t Fis

Once the Stationarity has been tested and if the series are Stationarity then we can test

the Grangers causality test, to test the causation between two series,

The test is based on the following regression:

Where Yt and Xt are the variables to be tested, and ut & vt are mutually uncorrelated

white noise errors, and t denotes the time period and kand lare the number of

lags.The null hypothesis is = = 0 for all ls versus the alternative hypothesis that

0 and 0 for at least some ls. If the coefficient s arestatistically significant

but s are not, then X causes Y. In the reverse case, Y causes X. But if both and

are Significant, then causality runs both ways.


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In our study for Gangers causality test hypotheses would be:

TEST1 H0: FII net flows does not cause S&P CNX Nifty return,

H1: FII net flows cause S&P CNX Nifty return.

TEST 2 H0: S&P CNX Nifty return does not cause FII net flows.H1: S&P CNX Nifty return cause FII net flows.

3.5) SCOPE OF THE STUDY:

In this study we are analyzing the causation between FII and Nifty return, but from

this single study we cant come to the conclusion that FII flows affecting the Indian

market return or Indian market return affect the FII flows, Because there are so many

factors (Internal and external) are affecting both

For eg: Exchange rate, Inflation, Growth, Savings, Interest rate etc,

Therefore our study is limited to analyze the relationship between the FII and Nifty

return with the help of Grangers causality test.

3.6) SAMPLE SIZE OF THE STUDY:

Daily FII net flow (Purchase sale) from 1 April 2001 to 31 March 2006.

Daily Nifty return from the 1 April 2001 to 31 March 2006.

3.7) DATABASE:

Data pertaining to the FII flows are taken from www.moneycontrol.com.

Data regarding Nifty return will be taken from www.nseindia.com.
http://www.nseindia.com/http://www.moneycontrol.com/


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4 DATA ANLYSIS:

ADF Test of FII Net flows:

ADF Test Statistic -24.80915 1% Critical Value* -2.5674

5% Critical Value -1.9396


*MacKinnon critical values for rejection of hypothesis of a unit root.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D (NETFLOWS)

Method: Least SquaresDate: 06/05/06 Time: 19:59

Sample (adjusted): 1/02/2001 10/24/2005

Included observations: 1255 after adjusting endpoints

Variable Coefficient Std. Error t-Statistic Prob.

NETFLOWS (-1) -0.659129 0.026568 -24.80915 0.0000

R-squared 0.329230 Mean dependent var 0.274502

Adjusted R-squared 0.329230 S.D. dependent var 406.9663

S.E. of regression 333.3076 Akaike info criterion 14.45681

Sum squared resid 1.39E+08 Schwarz criterion 14.46090

Log likelihood -9070.645 Durbin-Watson stat 2.133951

Interpretation:

ADF Test statistic of net FII flows (Purchase-sale) would be 24.80915,

Whereas Critical Value at 1% level is -2.5674

5% level is -1.9396

10% level is 1.6517

Since the ADF Test statistic result would be the greater than the Critical value,

therefore null hypothesis is rejected it means that data i.e. net FII flows is Stationary.


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ADF Test of Nifty Daily Return:


5% Critical Value -1.939610% Critical Value -1.6157


Augmented Dickey-Fuller Test EquationDependent Variable: D (NIFTY)Method: Least SquaresDate: 06/05/06 Time: 20:00Sample (adjusted): 1/02/2001 10/25/2005Included observations: 1256 after adjusting endpoints


NIFTY (-1) -0.876014 0.028006 -31.27959 0.0000

R-squared 0.438080 Mean dependent var 5.28E-07Adjusted R-squared 0.438080 S.D. dependent var 0.002426

S.E. of regression 0.001819 Akaike info criterion -9.780489

Sum squared resid 0.004152 Schwarz criterion -9.776400

Log likelihood 6143.147 Durbin-Watson stat 1.969839

Interpretation:

ADF Test statistic of Nifty return would be 31.27959


5% level is -1.9396

10% level is -1.6157

Since the ADF Test statistic result would be the greater than the Critical value,

therefore null hypothesis is rejected it means that data i.e. Nifty return is Stationary.


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Phillips-Perron Test:

PP Test of FII net flows:

PP Test Statistic -24.81731 1% Critical Value* -2.56745% Critical Value -1.9396



Lag0 truncation for Bartlett kernel: (Newey-West suggests: 7)Residual variance with no correction 110930.8

Residual variance with correction 110930.8

Phillips-Perron Test EquationDependent Variable: D (NETFLOWS)

Method: Least SquaresDate: 06/06/06 Time: 19:34Sample (adjusted): 1/02/2001 10/25/2005



NETFLOWS (-1) -0.659124 0.026559 -24.81731 0.0000

R-squared 0.329199 Mean dependent var 0.375398Adjusted R-squared 0.329199 S.D. dependent var 406.8198

S.E. of regression 333.1954 Akaike info criterion 14.45613Sum squared resid 1.39E+08 Schwarz criterion 14.46022Log likelihood -9077.450 Durbin-Watson stat 2.133734

Interpretation

PP Test statistic of net FII flows would be -24.81731


5% level is -1.9396

10% level is -1.6157

Since the PP Test statistic result would be the greater than the Critical value, therefore

null hypothesis is rejected it means that data i.e. Nifty return is Stationary.


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PP Test of Daily Nifty return:

PP Test Statistic -11.27146 1% Critical Value* -2.5674

5% Critical Value -1.939610% Critical Value -1.6157


Lag0 truncation for Bartlett kernel: (Newey-West suggests: 7)

Residual variance with no correction 2.06E-05

Residual variance with correction 2.06E-05

Phillips-Perron Test Equation

Dependent Variable: D (NIFTY)

Method: Least Squares

Date: 06/06/06 Time: 19:35

Sample (adjusted): 1/02/2001 10/27/2005



NIFTY (-1) -0.787887 0.069901 -11.27146 0.0000



S.E. of regression 0.004543 Akaike info criterion -7.949561

Sum squared resid 0.025946 Schwarz criterion -7.945477Log likelihood 5001.274 Durbin-Watson stat 1.151407

Interpretation

PP Test statistic of Nifty return would be -11.27146


5% level is -1.9396

10% level is -1.6157

Since the PP Test statistic result would be the greater than the Critical value, therefore

null hypothesis is rejected it means that data i.e. Nifty return is Stationary.


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ADF TEST FOR RESIDUALS (FII DEPEDENT AND INDEPENDENTNIFTY RESUIDALS)






Dependent Variable: D(FII)


Date: 06/11/06 Time: 13:40

Sample(adjusted): 1/02/2001 10/24/2005Included observations: 1255 after adjusting endpoints


FII(-1) -0.017736 0.005357 -3.310602 0.0010

R-squared 0.008661 Mean dependent var -0.760080



Sum squared resid 2.06E+08 Schwarz criterion 14.85386


Interpretation:

To calculate the ADF test for residuals, first we have to find out Residuals of

variables, For that we drew the regression analysis with each other by taking the FII

dependent first after that Nifty dependent, with help of results we got from the

regression i.e. Alpha and Beta, we are calculated the residuals,


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Calculation of residuals for Dependent variable i.e. FII :

+ * Nifty (Independent)

Calculation of residuals for Dependent variable i.e. Nifty:

+ * FII flows (Independent)

Since the ADF Unit root value is -3.310602 less than MacKinnon critical values@ 1% Critical Value* is -2.5674@ 5% Critical Value is -1.9396@ 10% Critical Value is -1.6157

Therefore Null hypothesis is rejected that means Residuals of FII are

stationary


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ADF TEST FOR RESIDUALS (NIFTY DEPEDENT ANDINDEPENDENT FII RESUIDALS)

ADF Test Statistic -10.98859 1% Critical Value* -2.56745% Critical Value -1.9396




Dependent Variable: D(NIFTY)


Date: 06/11/06 Time: 13:42

Sample(adjusted): 1/02/2001 10/24/2005



NIFTY(-1) -0.175622 0.015982 -10.98859 0.0000




Sum squared resid 3710110. Schwarz criterion 10.83524


Interpretation:

Since the ADF Unit root value is -10.98859 less than MacKinnon critical values@ 1% Critical Value* is -2.5674@ 5% Critical Value is -1.9396@ 10% Critical Value is -1.6157

Therefore Null hypothesis is rejected that means Residuals of Nifty are stationary.

Grangers causality test:


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Grangers causality test: At lag 2

Pair wise Granger Causality Tests

Date: 06/06/06 Time: 19:37Sample: 1/01/2001 12/29/2006

Lags: 2

Null Hypothesis: Obs F-Statistic Probability

NIFTY does not Granger Cause FII 1255 4.25025 0.01447

FII does not Granger Cause NIFTY 13.1296 2.3E-06



Date: 06/06/06 Time: 19:37

Sample: 1/01/2001 12/29/2006

Lags: 3



FII does not Granger Cause NIFTY 7.60004 4.9E-05



Date: 06/06/06 Time: 19:38

Sample: 1/01/2001 12/29/2006

Lags: 4



FII does not Granger Cause NIFTY 5.41595 0.00025


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Date: 06/06/06 Time: 19:39Sample: 1/01/2001 12/29/2006

Lags: 5






F distribution critical value would be 1.0000 @ 5% significance level

F distribution critical value would be 1.0000 @ 1% significance level


Date: 06/06/06 Time: 19:39

Sample: 1/01/2001 12/29/2006

Lags: 6





Date: 06/06/06 Time: 19:40

Sample: 1/01/2001 12/29/2006

Lags: 7

Null Hypothesis: F-Statistic Probability

NIFTY does not Granger Cause FII 1.87508 0.07012FII does not Granger Cause NIFTY 3.52561 0.00094


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Interpretation:

Since in all the lags F-Statistic value would be the greater than F distribution table

therefore

Null hypothesis i.e. NIFTY does not Granger Cause FII

FII does not Granger Cause NIFTY rejected

It means that Nifty return does cause FII and Nifty return has impact on net FII flows.

And also net FII flows does cause Nifty return.

There is Bi-directional relationship existence between the FII Flows and Nifty return .


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Findings and conclusion:

The results reveal that FII have been Attracted to India as an Important investment

destination. FII investment in certain Indian companies shows majority shareholding,

the flow FII seems to be attracted by the Indian equity returns.

The relationship between the FII investment and the Indian market return still remains

highly debatable, the our test for casual relationship between the FII and Nifty return

Existence of bi-directional causality between Nifty return and FII flows

FII flows are correlated with contemporaneous returns in the Indian markets.

This high correlation is not necessarily evidence of FII flows causing price

Pressure if anything, the causality is likely to be the other way around.

A collection of domestic and international variables likely to affect both flows and

Returns fail to diminish the importance of contemporaneous returns in explaining

FII flows.

Since the US and world returns are not significant in explaining the FII flows,


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Limitation of the study:

Since the our research topic is Impact of FII on Nifty return, in this we are tried to

analyze the relationship between the FII and Nifty and Impact by each other But

Practically numbers of variables are affected to the market like company related

information, economic factors, external factors etc, so we cant say that or cant

conclude that FII flows only determine the Nifty return, this is major hurdle for our

project and other limitation for our project is time constraint and Historical

availability of data, Because we are taking Daily FII net flows and nifty return


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Bibliography:

Books:Modern econometric model by Pindic

Journals:

ICFAI journal of applied Finance

ICRA journal Money and Finance

Websites:

www.nseindia.comwww.rbi.org.in

www.moneycontrol.com

www.valuenotes.com
http://www.valuenotes.com/http://www.moneycontrol.com/http://www.rbi.org.in/http://www.nseindia.com/


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EXECUTIVE SUMMARY

Over the past ten years India has gradually emerged as an important destination of

global investors investment in emerging equity markets.Today India has a share of

about 20 per cent in the total global investment in all emerging equity markets

together and the outstanding FII investment in India stood around Rs.86, 287crore,as

on end march, 2002.FII investments as a percentage of market capitalization

increased from7.06 per cent in 1999-00,to 13.5per cent in 2000-01 and further to 14.1

per cent in 2001-02.Given this growing importance of FII for the Indian economy and

in year 2005 only FII are invested more than 47000 crs, It is apparent that the nature

and causation of such fund flows deserve careful examination.

A concern with the entry of FIIs is that they are positive feedback traders, buying when

the market increases and selling when the market falls. This could be destabilizing as the

sales would lead the stock market to fall and buys would make the stock market go up.

These traders could possibly push the stock prices away from the fundamentals. Gray area

of the study is to analyze the relationship between the FII net flow and return from the

stock market and what extent they are correlated with each other.

The present study deals with the analyses of relation between two variables namely

FII net flows and Stock market return; to study the relationship between these two

variables we are conducted the Grangers causality test. To conduct Grangers causality

test the time series must be stationary, to calculate stationarity condition has been

tested using augmented dickey fuller test and Philips peron test. For that Daily Net

FII flows and NIFTY returns are collected from 1-april-2001 to 31-march-2006

From the empirical research we can conclude that there is Bi-directional causal

relationship between Net FII flows and Nifty return.


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relationship between fii flows and nifty index

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