Influence of foreign portfolio investment on stock market indicators

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International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 5, Issue 10, October (2014), pp. 01-11 © IAEME
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ISSN 0976-6510 (Online)
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IJM
© I A E M E
INFLUENCE OF FOREIGN PORTFOLIO INVESTMENT
ON STOCK MARKET INDICATORS
Prof. Dr. Mahesh S. Halale
Dean (Academics), Sadhu Vaswani Institute of Management for Girls, Pune (Maharashtra) India
ABSTRACT
Whether fluids or funds, find and follow their slop invariably. Foreign Portfolio
Investment (FPI) is one such entity, which either boosts or impedes stock market movements and
investment sentiment with each of its passing breeze. When economy is in trouble, when
currency under depreciation pressure, current account in red, widening fiscal deficit then from a
country’s finance ministry to common retail investor in stocks market pray and wait eagerly for
financial institutional investors pouring in their funds in the stock market. In turn the foreign
portfolio investments raise the bar and motivate the performance of the corporate world. They
bring in paradigm shift in the focus of industry by enhancing the PE expectations. No doubt FPIs
do play miracles in the stock market but the question is how sustainable it is. In this paper an
attempt is made to understand the role of FPI and its degree of influence on stock market
indicators such as Price Earnings multiple(PE), Dividend Yield (DY), Book Value (BV) of
NIFTY.
Keywords: Foreign Portfolio Investment (FPI), National Stock Exchange’s benchmark index
(NIFTY), Price Earnings multiple (PE), Dividend Yield (DY), Book Value (BV).
1. INTRODUCTION
The economic reforms initiated in 1990, has opened greater and better avenues to attract
the foreign funds in the Indian stock market. SEBI acting as nodal point has smoothened the
process. RBI allowed SEBI registered FIIs/NRIs/PIOs/OCBs to invest in the primary and
secondary capital markets in India through the portfolio investment scheme. Eligible institutional
investors that can register as FIIs include asset management companies, pension funds, mutual
funds, banks, investment trusts, nominee companies, incorporated/institutional portfolio

2. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 5, Issue 10, October (2014), pp. 01-11 © IAEME
managers, power of attorney holders, university funds, endowment foundations, charitable trusts
and charitable societies. These bodies can invest in equity shares and convertible debentures of
the companies available for purchase under PIS. RBI has placed a ceiling of 24% on FIIs
(Foreign Institutional Investment a more popular acronym for FPI is used liberally in
forthcoming text) and 10% on NRIs/PIOs of the paid up capital of the Indian company and 20%
paid up capital of public sector banks. RBI provides that the ceiling of 24 and 10 per cent for FII
investment can be raised up to sectoral cap/statutory ceiling, subject to the approval of the board
and the general body of the company passing a special resolution to that effect. Presently there
are 89 companies in 24% cap category, 19 in 30% cap category, 14 in 40% cap category, 16 in
49% cap category. The biggest source through which FIIs invest is the issuance of Participatory
Notes (P-Notes), which are also known as Offshore Derivatives.
2
It is generally observed that the inflow of funds in stock market raises investment
sentiments and the stock indices. Portfolio investment being an instant phenomenon it displays
the stock market influence instantaneously. An attempt is being made in this paper to identify
the association amongst the foreign portfolio investment and its influence on stock market
indicators. To what extent these investments influence the market indicators under consideration.
More specifically an attempt is being made to understand the degree of its influence on stock
market indicators such as Price Earnings multiple (PE), Dividend Yield (DY), Book Value (BV)
of NIFTY. Also an attempt is made to find out whether this influence gets ironed out over a
period of time and brings sanity in stock index movements in long run.
2. PROBLEM STATEMENT
Foreign portfolio investment creates a positive sentiment in a stock market of a given
country. Apparently it is observed that such cash flows influences the stock market the
underlying market indicators. Often such inflows lead to spiky movements in stock market
indices. It is argued that this is kind of volatile source.
Whether such inflow leads to sustainable and healthy pressure on the corporate to
perform? Whether such investments lead to improving the payout obligations in long run?
Whether this influence is instantaneous reaction or builds up sustainable investment environment
in long run? Hence in this paper these issues are being explored to understand to what extent the
foreign portfolio investment influences the stock markets and its indicators.
3. LITERATURE REVIEW
It has been observed that the day to day movements of stock market indices are quite
sensitive to foreign portfolio investments. Amongst other international factors, FII flow
influences the market sentiment very quickly and heavily.
A thorough analysis of the stock market during 2010-2013 shows that the stock market
touched its peak at 21000 but then crashed badly on account of reverse foreign institutional
investments flows; this leads one to infer that net FII investments influences the stock prices in
India (Rao, 1999). FII’s were a major portion of investments and their roles in determining the
movement of share price and indices is considerably high. The movement of indices in India
depends only on the trade done in a limited number of stocks. Thus, when the FII’s frequently
buy and sell stocks, it leads to volatility of the market. Recently it was observed that, when
global markets were bearish, the stock market performance has been the solely driven by FII

3. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 5, Issue 10, October (2014), pp. 01-11 © IAEME
flows, though monthly data in the pre-Asian crisis period suggests some reverse causality (Raj
Chaitanya, 2003). In a study conducted by Gordon and Gupta (2002) on the portfolio flows in
India and the influence of domestic fundamental factors, it was found that there exists a strong
impact of the domestic fundamentals on the investment flows into India. Mukherjee (2002)
examined the various probable determinants of FII and concluded that FII net inflow are
significantly affected by the performance of the Indian equity market and that the basic purpose
of FII is not diversification of their investment but returns from the exchange rate variation and
the fundamentals of the economy may have an impact on FII decisions, but such influence do not
prove to be strong enough. Rai, K. and N. Bhanumurthy (2004) examined the role of return, risk
and inflation as determinants of foreign institutional investors in the context of India. They found
that FII inflow depends on stock market returns, inflation rates (both domestic and foreign) and
ex-ante risk. In terms of magnitude, the impact of market returns and the ex-ante risk turned out
to be the major determinants of FII inflow. They have also found that there is a causative link
running from FII inflow to stock returns. They suggest that the stabilizing the stock market
volatility and minimizing the ex-ante risk would help to attract more FII, an inflow of which will
have a positive impact on the real economy. Kumar (2006) examined the role of institutional
investors in Indian stock markets and found that the market movement can be explained using
the direction of the funds flow from these investors. It is found that there is a unidirectional
casual relationship between market capitalization and stock market and between net FII
investment and stock market. FII inflow depends on stock market returns, inflation rates (both
domestic and foreign), and ex-ante risk. In terms of magnitude, the impact of stock market
returns and the ex-ante risk turned out to be the major determinants of FII inflow. (Kulwant
Bhanumurthy, 2004)
3
FIIs are strong forces driving the Indian Stock Market which is evident from top twenty
five crashes at BSE SENSEX as FIIs were the net sellers in all the leading market crashes. Indian
stock market and FIIs influence each other; however, their timing of influence is different
(Loomba, Jatinder, 2012, Rukhsana, et.al., 2009).
Figure 1: Monthly FII and DII investment and NIFTY movement
(Source: http://www.traderscockpit.com/)
FII
DII
Nifty

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4. METHODOLOGY
This research paper is based on secondary data. The data is collected from various data
repositories such as RBI, SEBI, moneycontrol.com and several other financial institutions sites.
The scope of the study is the FIIs investment in the Indian Stock market during 2003 to 2013.
The data analysis covers the assessing of the association amongst the stock market indicators and
FII investments for the corresponding period. The study is supported by information collected
from internet, books, magazines, journals. Inductive inferences have been drawn from the data
collected and analysed so. To be precise the study delves upon evaluating the role played by FII
investment in the stock market activity in particular.
SPSS 16 has been used for data analysis. Pearson Correlation coefficient has been
computed to understand the relationship between FII investment and CNX Nifty. Monthly
average has been taken of both the data so as to iron out the spikes/jerky momentum reactions of
FII investment on the stock market captured in to CNX Nifty. 133 Data pairs of month’s average
of CNX Nifty and Net FII investment for the period from January 2003 to December 2013 have
been taken in to consideration for computation of Pearson Correlation coefficient.
Secondly SPSS is used to compute Pearson’s correlation coefficient to understand the
relationship between FII investment and other dependent (?) variables such as CNX
NIFTY(annual), NIFTY PE, NIFTY BV and NIFTY DY. For this analysis 11 sets of annual
average data for CNX Nifty, NIFTY PE, NIFTY BV and NIFTY DY have been considered for
the period from 2003 to 2013.
5. OBJECTIVES
a. To crystallize association between the FII and stock market indicators
b. To analyse the extent to which FII influences the stock movements
c. To critically analyze the role played by FIIs in Indian stock market
6. SCOPE OF THE STUDY
The study focuses on the data of monthly NIFTY index movement for the period Jan
2003 to December 2013 and corresponding data for net cash flows on account of FII investment.
Secondly to throw light on the other market indicators such as NIFTY index, NIFTY’s price-earnings
multiple (PE), dividend yield (DY), book value (BV) annual data is being used for the
period Jan 1999 to Jan 2014.
7. HYPOTHESIS
The hypotheses set for study are as under:
H0: The FII investment does not influence the stock market movements i.e. CNX Nifty (monthly
data)
H00: The FII investment does not influence market indicators CNX Nifty, Nifty BV, Nifty PE
and Nifty DY (annual data).

5. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
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8. DATA COLLECTION
Table 1: Monthly Net FII activity v/s and CNX Nifty level from Jan 2003 to Dec 2013
MONTHS FII Net NIFTY contd…. contd…. contd….
Jan-03 1,065.50 1041.9 Oct-05 -3,805.60 -3,805.60 Jul-08 -1,012.90 4333 Apr-11 7,018.50 5749.5
Feb-03 405.2 1063.4 Nov-05 4,448.60 2652.3 Aug-08 -2,065.80 4360 May-11 -5,158.20 5560.2
Mar-03 252.7 978.2 Dec-05 9,465.20 2836.6 Sep-08 -7,937.00 3921 Jun-11 3,172.10 5647.4
Apr-03 549.9 934.05 Jan-06 3,220.70 3001.1 Oct-08 -14,248.60 2886 Jul-11 7,411.10 5482
May-03 1,208.40 1006.8 Feb-06 7,571.90 3074.7 Nov-08 -2,820.30 2755 Aug-11 -10,214.60 5001
Jun-03 2,611.70 1134.2 Mar-06 6,532.30 3402.6 Dec-08 1,330.90 2959 Sep-11 -1,147.00 4943.3
Jul-03 2,428.20 1185.9 Apr-06 589.2 3557.6 Jan-09 -3,009.50 2875 Oct-11 2,468.80 5326.6
Aug-03 2,026.60 1356.6 May-06 -8,247.20 3071.1 Feb-09 -2,690.50 2764 Nov-11 -3,946.60 4832.1
Sep-03 3,936.10 1417.1 Jun-06 1,418.20 3128.2 Mar-09 269 3021 Dec-11 -128.5 4624.3
Oct-03 6,862.60 1555.9 Jul-06 1,447.90 3143.2 Apr-09 7,384.20 3474 Jan-12 12,967.20 5199.3
Nov-03 3,195.30 1615.3 Aug-06 4,774.00 3413.9 May-09 20,606.90 4449 Feb-12 25,217.40 5385.2
Dec-03 5,411.00 1879.8 Sep-06 6,231.70 3588.4 Jun-09 3,224.90 4291 Mar-12 8,832.90 5295.6
Jan-04 2,374.10 1809.8 Oct-06 4,578.54 3744.1 Jul-09 11,625.30 4637 Apr-12 -1,865.60 5248.2
Feb-04 3,271.90 1800.3 Nov-06 6,574.74 3954.5 Aug-09 4,028.70 4662 May-12 -1,522.80 4924.3
Mar-04 8,769.00 1771.9 Dec-06 -3,410.90 3966.4 Sep-09 19,939.50 5084 Jun-12 133.5 5278.9
Apr-04 4,173.00 1796.1 Jan-07 94.45 4082.7 Oct-09 8,304.10 4712 Jul-12 10,346.40 5229
May-04 -3,250.50 1483.6 Feb-07 6,065.00 3745.3 Nov-09 5,317.80 5033 Aug-12 9,729.60 5258.5
Jun-04 310.6 1505.6 Mar-07 1,403.30 3821.6 Dec-09 10,367.20 5201 Sep-12 20,769.00 5703.3
Jul-04 1,183.30 1632.3 Apr-07 5,431.80 4087.9 Jan-10 5,902.40 4882 Oct-12 10,272.90 5619.7
Aug-04 2,811.20 1631.8 May-07 4,574.50 4295.8 Feb-10 2,113.50 4922 Nov-12 10,967.10 5879.9
Sep-04 2,784.30 1745.5 Jun-07 7,939.60 4318.3 Mar-10 18,833.60 5249 Dec-12 24,299.20 5905.1
Oct-04 4,042.40 1786.9 Jul-07 18,132.80 4528.9 Apr-10 9,764.50 5278 Jan-13 22,673.90 6034.8
Nov-04 6,412.40 1958.8 Aug-07 -7,526.80 4464 May-10 -8,629.90 5086 Feb-13 21,122.40 5693.1
Dec-04 5,806.70 2080.5 Sep-07 18,948.50 5021.4 Jun-10 10,244.60 5313 Mar-13 11,660.50 5682.6
Jan-05 -281.7 2057.6 Oct-07 15,577.60 5900.7 Jul-10 17,120.60 5368 Apr-13 5,145.30 5930.2
Feb-05 7,695.00 2103.3 Nov-07 -4,597.40 5762.8 Aug-10 11,185.30 5402 May-13 21,267.70 5986
Mar-05 7,649.30 2035.7 Dec-07 4,896.70 6138.6 Sep-10 29,195.80 6030 Jun-13 -9,318.70 5842.2
Apr-05 -1,047.10 1902.5 Jan-08 -17,326.30 5137.5 Oct-10 24,770.80 6018 Jul-13 -7,120.20 5742
May-05 -807.6 2087.6 Feb-08 5,419.90 5223.5 Nov-10 18,519.90 5863 Aug-13 -6,200.00 5471.8
Jun-05 5,762.10 2220.6 Mar-08 124.4 4734.5 Dec-10 1,476.10 6135 Sep-13 12,632.90 5735.3
Jul-05 8,212.20 2312.3 Apr-08 979 5165.9 Jan-11 -6,330.20 5506 Oct-13 18,012.80 6299.2
Aug-05 4,412.60 2384.7 May-08 -4,917.30 4870.1 Feb-11 -3,754.50 5333 Nov-13 7,079.40 6176.1
Sep-05 4,122.60 2601.4 Jun-08 -10,577.70 4040.6 Mar-11 6,966.70 5834 Dec-13 15,425.60 6304
Source: www.moneycontrol.com
Data compiled on the basis of reports submitted to SEBI by custodians and constitutes
trades conducted by FIIs on and upto the last trading day of that month.

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Table 2: NIFTY PE BV DY(Jan1999-Jan2014)
Time NIFTY PE NIFTY BV NIFTY Div Yield
Jan-99 11.62 2.7 1.81
Jan-00 25.16 4.76 0.95
01-Jan 20.85 4.16 1.25
02-Jan 16.09 2.54 1.52
03-Jan 14.82 2.43 2.41
04-Jan 21.09 4.19 1.41
05-Jan 14.96 3.52 1.89
06-Jan 17.58 4.44 1.56
07-Jan 21.38 5.12 1.2
08-Jan 28.23 6.53 0.82
09-Jan 13.3 2.58 1.82
10-Jan 23.31 3.67 0.93
11-Jan 23.56 3.83 1.01
12-Jan 17.26 2.8 1.6
13-Jan 18.89 3.16 1.39
14-Jan 18.68 2.98 1.49
Source: http://craytheon.com/charts
9. DATA ANALYSIS
9.1 Correlation between Monthly Net FII flow v/s and CNX Nifty from Jan 2000 to
Dec 2013
Correlations
FII_Net_Mthly CNX_NIFTY_Mthly
FII_Net_Mthly Pearson Correlation 1 .311**
Sig. (2-tailed) .000
N 132 132
CNX_NIFTY_Mthly Pearson Correlation .311** 1
Sig. (2-tailed) .000
N 132 133
**. Correlation is significant at the 0.01 level (2-tailed).
It is observed that value of r is 0.311 and the correlation between FII net inflows and
CNX NIFTY is moderate but positive. The statistical significance value at 0.01 level comes out
to be 0.000, hence the Correlation is statistically significant.

7. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
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Figure 2: Scatter plot of Net FII inflows V/s Benchmark Index NIFTY
Test inference of the first null hypothesis H0 is:
The FII investment does not influence the stock market movements (CNX Nifty) is not true.
Thus we conclude that FII influence the stock market movement which is captured in NIFTY
index. The correlation is moderate (0.311) but positive.
9.2 Correlation between Yearly Net FII activity v/s Market Indicators
a) CNX Nifty
b) Nifty PE
c) Nifty BV
d) Nifty DY
During the period from Jan 2000 to Dec 2013
Correlation Between
Pearson Correlation:
r Value
Significance at 0.01
level
FII Net and NIFTY PE 0.076 0.823
FII Net and NIFTY BV -0.313 0.349
FII Net and NIFTY DY -0.227 0.501
FII Net and CNX NIFTY index
(Annual) 0.411 0.020

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The value of r Person’s correlation coefficient for FII Net and NIFTY PE works out to
be .076 and the statistical significance at confidence level 0.01 comes greater than 0.05. It shows
that there is no sound relationship between FII inflows and Price Earnings multiple.
Secondly the value of r Person’s correlation coefficient for FII Net and NIFTY BV
works out to be -0.313 and the statistical significance at confidence level 0.01 comes greater than
0.05. It shows that there is moderate and inverse relationship between the FII flows and book
value of the NIFTY.
Thirdly the value of r Person’s correlation coefficient for FII Net and NIFTY DY works
out to be -0.227 and the statistical significance at confidence level 0.01 comes greater than 0.05.
It shows that there is moderate and inverse relationship between the FII flows and of the NIFTY
dividend yield.
Lastly the value of r Person’s correlation coefficient for FII Net and CNX
NIFTY(annual) works out to be 0.411 and the statistical significance at confidence level 0.01
comes less than 0.05. It shows that there is sound and statistically significant positive
relationship between the FII flows and of the CNX NIFTY index.
Thus we can say that the null hypothesis
Test inference of the first null hypothesis H00 is:
The FII investment does not influence market indicators CNX Nifty, Nifty BV, Nifty PE
and Nifty index is not proved i.e. all the market indicator under consideration are (though not
highly but) moderately influenced by FII net cash flows in the Indian stock market.
10. INTERPRETATION
10.1 CNX NIFTY Index
The market index has been tested twice on monthly basis also on yearly data basis. It
was observed that the FII inflows do influence the market activity and thereby the index (0.311
and 0.411). However the FII inflow appears to display the momentary reaction on the index
movement. And over a period of time say a week, month and year the effect gets smoothened
over. Simply the effect gets discounted and digested by the market in longer run than a day’s
movement. And because of this phenomenon the influence of the FII on the index movement
ranges from high to moderate to low. The correlation coefficient calculated for different periods
support the conclusion i.e. on the monthly data basis the r shows quite stronger relationship than
annual data basis.
10.2 FII Net and NIFTY PE
The computation shows that the market indicator NIFTY PE moves with FII net inflows.
It shows that as the FII inflows gets built up and invested in to the market, it enhances the market
value. The price earnings multiple goes up, because the demand for the stock goes up and which
pushes up its price and there by the PE multiple. It needs to be noted that though this relation is
obvious but it is not significant. This is because the PE multiple of NIFTTY which comprises of
number stocks, and PE of each of the stock is dependent on number of financial and non
financial factors. These factors could be economic condition, growth rate, profir margins,
business cycle, regulatory policies etc. Amongst them one factor is FII. Therefore the collective
effect of all such factors influence the NIFTY PE, hence the impact gets moderated.

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10.3 FII Net and NIFTY BV
It is found that the book value of the NIFTY displayed moderate and inverse relationship
with FII cash flows. Also the relationship is not statistically significant. This market indicators
appears to be less influenced by the FII cash flows.
10.4 FII Net and NIFTY DY
It is found that the dividend yield of the NIFTY displayed moderate and inverse
relationship with FII cash flows. Also the relationship is not statistically significant. The obvious
reason appears to be that as the FII inflows enhance the market price of the stock. It also
enhances investors’ expectations from the company. When the expectations are met (i.e. the
dividend payments are in line with expectations) dividend yield remains in tune with price of the
stock. Otherwise if the expectations are not met with it leads to increase in denominator only and
thereby the dividend yield ratio get adversely affected. The immediate effect of FII inflows on
stock price and lagging effect FII inflows on earnings performance, clearly displays and support
the inverse relationship observed in our study.
11. CONCLUSION
FII plays very significant role in driving the stock market. It becomes imperative for a
country like India, where there is huge potential to grow but bleak environment to propel that
growth. Especially when the stock markets all over the globe are bearish it paves an obvious way
to markets like India.
It is observed that the day to day influence of FII flow on the stock market indicator i.e.
NIFTY index is very vivid and significant. However over a period of time say week/months/year
the influence gets ironed out. At times the reverse movement of FII softens/nullifies the earlier
effect on index and/or over a time as the influence gets discounted in to price and the index starts
behaving rationally. Therefore the influence of net monthly data FII on NIFTY index is higher
than the annual data. In line with this argument and which do not need much proof, it can be seen
that daily FII inflows or outflows influence more vividly on the day’s index level. Secondly the
market indicators such as price earnings multiple, book value and dividend yield of NIFTY
shows the indirect and lagging effect of FII. Unlike NIFTY Index these indicators are reflect the
FII activity over a period of time, and get sufficient time to absorb the information and reflect the
change. The time lag effect gives these indicators a breather to accommodate the effect of other
financial and even non financial factors simultaneously. The indicator like Dividend Yield
discounts number of other factors and gets substantially more time (a year or so) to
accommodate the influence of FII flows, therefore such indicators appears sometimes as if they
are inert to the FII activity. However the influence of FII flows though subdued on some
indicators and it vivid on other, one can argue on degree and timing but one cannot deny the
influence of FII activity in the stock market.
12. LIMITATIONS OF STUDY
This paper concentrates on Indian Stock market and foreign portfolio investment over a
decade of Jan 2003 to Dec 2013. The data about index and underlying market indicators such as
PE multiple, DY and BV limited to fifty underlying scrips of India’s National Stock Exchange’s

10. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
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benchmark index NIFTY. Also there are number other factors which influence the stock market
movements. Since FPI being a very vivid and major factor, influence other factors ignored.
Also this period under consideration may not be all inclusive as it contains most volatile
monetary and fiscal situation all over the world. The decade under considerations has seen most
volatile period in financial markets, including 2008 US crises. Therefore this study carries these
obvious shortcomings.
BSE: Bombay Stock Exchange
BV: Book Value
CNX NIFTY/NIFTY: National Stock Exchange’s benchmark index, India
DII: Domestic Institutional Investment
DY: Dividend Yield
FII: Foreign Institutional Investment
FPI: Foreign Portfolio Investment
NRI: Non Resident Indian
OCB: Overseas Corporate Bodies
PE: Price Earnings multiple
PIO: Person of Indian Origin
PIS: Portfolio Investment Scheme
PN: Participatory Notes (P-Notes)
RBI: Reserve Bank of India
SEBI: Security Exchange Board of India
SENSEX: Bombay Stock Exchange’s benchmark index
10
Abbreviations
REFERENCES
[1] Gordon and Gupta (2002). Determinants of Foreign Institutional Investment in India,
Journal of Institutional Investors. Vol 15. Emerald Group Publishing Limited.
[2] Kulwant and Bhanumurthy. (2004). Determinants of Foreign Institutional Investment in
India-The role of return, risk and inflation. The Developing Economies, XLII-4,
December, pp. 479-93
[3] Kumar Saji (2006). FIIs Vs. SENSEX: An Emerging Paradigm. Treasury Management,
ICFAI University Press, February 2006.
[4] Loomba, Jatinder (2012). Do FIIs Impact Volatility of Indian Stock Market?.
International Journal of Marketing, Financial Services Management Research, Vol.1
Issue 7, pp. 80-93.
[5] Mukherjee (2002). Taking Stock of Foreign Institutional Investors. Economic and
Political Weekly. June 11, 2005.
[6] Rao (1999). On the dynamic relation between stock prices and FIIs. Journal of ICFAI,
Vol: 25. Publisher: MCB UP Ltd.
[7] Raj Chaitanya (2003). Foreign Institutional Investments, Money and Finance .Vol. 2, No.
7, October-December, pages 61-81.

11. International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 5, Issue 10, October (2014), pp. 01-11 © IAEME
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[8] Rai, K. and N. Bhanumurthy (2004). Role of return, risk and inflation as determinants of
foreign institutional investors in India. Journal of Institutional Investors. Vol 17. Emerald
Group Publishing Limited.
[9] Rukhsana, Kalim and Shahbaz, Mohammad (2009), “Impact of Foreign Direct
Investment on Stock Market Development: the case of Pakistan”, 9th Global Conference
on Business Economics
[10] http://www.traderscockpit.com/
[11] http://craytheon.com/charts
[12] http://www.moneycontrol.com/india/stockmarket/foreigninstitutionalinvestors/10/25/acti
vity/FII.
[13] Rajesh V. Argiddi and Sulabha S. Apte, “An Evolutionary Fragment Mining Approach to
Extract Stock Market Behavior for Investment Portfolio”, International Journal of
Computer Engineering Technology (IJCET), Volume 4, Issue 5, 2013, pp. 138 - 146,
ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
[14] R.Karthik and Dr.N.Kannan, “Impact of Foreign Direct Investment on Stock Market
Development: A Study with Reference to India”, International Journal of Management
(IJM), Volume 2, Issue 2, 2011, pp. 75 - 92, ISSN Print: 0976-6502, ISSN Online:
0976-6510.
[15] Dr.B.Ponnuswamy, “Trends in Foreign Direct Investment in Automobile Industry-A
Case Study”, International Journal of Management (IJM), Volume 3, Issue 1, 2012,
pp. 121 - 125, ISSN Print: 0976-6502, ISSN Online: 0976-6510.
[16] A. Ramaraju, “Impact of FDI on Stock Market Development: An Empirical
Investigation”, International Journal of Management (IJM), Volume 2, Issue 1, 2011,
pp. 142 - 148, ISSN Print: 0976-6502, ISSN Online: 0976-6510.