FII Investment in India: A Study of Multiple Structural Breaks
Dr. Jayesh N. Desai
Mrunal Chetanbhai Joshi
In charge Director
Assistant Professor,
B.R.C.M. College of Business
B.R.C.M. College of Business
Administration, Surat
Administration, Surat
Contact: 09898132209
Contact: 09824434320
Email:
[email protected]
Email:
[email protected]
Abstract In India in 1990s in its major policy shift started allowing foreign investment in its financial markets. This led to Foreign Institutional Investors (FII) gradually investing in Indian stock market and starting of a new era in Indian stock markets. Today FIIs have emerged to be one of the most dominant groups of investors with ownership of significant component of traded securities. Nevertheless flow of FII investment in Indian stock market has not remained same throughout. In this context, this paper tries to study trend of FII investment over the period of time. It also tries to find out structural changes in the investment flow of FIIs. Investigation is also done to find if multiple structural breaks are present in FII investment flow over the period of time. Study also tries to identify growth in Investment flow of FII in Indian stock market since liberalisation and it’s impact on stock market return. Keywords: FII, Multiple Structural Breaks, Indian Stock Market
Introduction FII in India In India in 1990s in its major policy shift started allowing foreign investment in its financial markets. This led to Foreign Institutional Investors (FII) gradually investing in Indian stock market from 1992 and starting of a new era in Indian stock markets. From 1996-97 to 201314 CAGR of FII investment in Indian stock market was 21.62%. Thus, Today FIIs have emerged to be one of the most dominant groups of investors with ownership of significant
component of traded securities and became crucial for all emerging countries like India. FII investment flow in India is important element not only for stock market but also in maintenance of balance of payment related issue. FII flow is affected by various events occurring within the host country viz. political and economical as well as any other happenings throughout the globe like any crisis or developments. Whenever such even occur it may positively or negatively affect the flow. If such changes are temporary in nature we can neglect them, but if such events changes the slop of trend of FII investment flow, it really matters to predict of study them further. To study FII flow in India knowledge of econometrics could be handy. Econometrics is useful not only in forecasting but also in identifying major hurdles in forecasting and dealing with them. Structural Break Structural breaks are useful econometric tools to understand paradigm shift in trend and change in slop of any time-series data. A structural break appears when we see an unexpected shift in a time series data. It's called a structural break when a time series abruptly changes at a point in time. This change could involve a change in mean or a change in the other parameters of the process that produce the series("Tests for structural breaks in time-series data | Stata 14,"). This can lead to huge forecasting errors and unreliability of the model in general. This change could involve a change in mean or a change in the other parameters of the process that produce the series. Structural break tests help us to determine when and whether there is a significant change in our data("Tests for structural breaks in time-series data | Stata 14,"). Structural breaks can be studied in two ways firstly when we are aware about the events happened we can check whether it has some significant effect in trend and secondly when significant change happen which is identified earlier then find out the reason for it. Key Events decisive to Indian stock markets
1992 Harshad Mehta Scam
1994 Maxican Peso Crisis
1998 Asian Financial Crisis
2001 Ketan Parekh Scam
2003 P-Notes Issues
2006 FII limit related announcement in Budget
2007 Eurozone Crisis
2008 Subprime Crisis
2009 Bail-out program of Europe, Satyam Scam, End of Subprime in US
2012 Announcement of GAAR
2014 Petroleum Issue
2015 Declaration of MAT, Greece Crisis, Chinese Yuan devaluation
Lok Sabha Elections
Source: http://www.marketexpress.in/2013/11/fii-investments-stock-market-performance-around-generalelections.html
Out of the above major events few of them affected FII flow in Indian stock market. To understand various events, their effect on FII investment in Indian stock market and structural breaks following literature review is done.
Literature Review To test the equality between sets of coefficients in two linear regressions, Chow (1960) obtained the sum of squares of the residuals assuming the equality, and the sum of squares without assuming the equality. The ratio of the difference between these two sums to the latter sum, adjusted for the corresponding degrees of freedom, distributed as the F ratio under the null hypothesis. Latter sum of squares computed only from the first sample of n observations when the second sample was not large enough for computing a separate regression. They attempted to show the application of the theory of general linear hypotheses in the prediction interval and the analysis of covariance are related to each other. While dealing with the comparison of coefficients in only two regressions he founded that it could obviously be generalized to the case of many regressions. Bai and Perron (1998) had considered issues related to multiple structural changes, occurring at un-known dates, in the linear regression model estimated by least squares. The
main aspects were the properties of the estimators, including the estimates of the break dates, and the construction of tests that allow inference to be made about the presence of structural change and the number of breaks. They considered the general case of a partial structural change model where not all parameters were subject to shifts. They studied both fixed and shrinking magnitudes of shifts and obtain the rates of convergence for the estimated break fractions. Bai and Perron (2003) supplemented the set of critical values to check multiple structural breaks. M. Singh (2007) observed that while market capitalization of the large Indian stock exchanges is presently about 100 percent of GDP (around $1.3 trillion), FIIs hold about 25 percent of the market if cumulative dividends that are rolled over are included. However, market sources suggest that around 50 percent of FII flows have been via participatory notes (PNs). PNs, which are an offshore instrument against underlying Indian securities, can be issued as derivatives or cash. Schätz (2010) supplied empirical evidence of the dynamic interactions between international macroeconomic determinants and 10 emerging market sector indices. Due to several economic and monetary crises, they found structural breaks in 9 of the 10 sectors. For that they applied a two-stage test procedure to verify the stability of the regression coefficients over time and to ensure the identification of structural breaks. First, the time series were checked for the existence of structural breaks by means of CUSUM and CUSUMQ tests. Second, the Chow test verified the dates which were deter-mined by those test procedures. Solanki and Kachhwaha (2010) mentioned that as the stock markets collapsed in Eurozone, there was panic in the Indian stock markets. The foreign institutional investors (FIIs) who had invested in Mumbai stock market suddenly withdrew their investment. This naturally dipped the BSE Sensex. The value of Sensex dropped by more than 600 points in early trade on 29th June 2015, but managed to recoup some loses later on selective buying in the beaten-down counters and settled the day lower by 167 points at 27,645.15. Bajpai (2011) studied that the initial effect of the subprime crisis was, in fact, positive, as the country received accelerated Foreign Institutional Investment (FII) flows during September 2007 to January 2008. But as the global crisis intensified and spread to the emerging economies through capital and current account of the balance of payments. The net portfolio flows to India soon turned negative as Foreign Institutional Investors rushed to sell equity stakes in a bid to replenish overseas cash balances. This had a knock-on effect on the stock
market and the exchange rates through creating the supply demand imbalance in the foreign exchange market. Narayan, Narayan, and Mishra (2013) have studied that structural break has slowed down the growth rate of the US, UK and Japanese stock markets. For this study they have used the common structural break test suggested by Bai et al. (1998). They have studied various aspects affecting stock markets such as the asset price bubble when housing prices and stock prices in Japan reached a peak in 1988/1989, the early 1990s recession in the UK, the business cycle peak of July 1990, the August 1990 Iraqi invasion of Kuwait and the March 1991 business cycle trough. Choudhury (2014) in his study took a comprehensive investigation into India’s service sector, the main growth engine for Indian economy over during past two decades. First, delt with the endogenous multiple structural break developed by Bai Perron (1998, 2003). He also applied both the models of pure and partial structural breaks propounded by Bai and Perron are considered. Joshi and Desai (2015) have studied the trend of FII flow and Sensex value from the year 1992 to 2014. In that study they have found bullish trend and bearish trend and correlation during those periods. Trend
Period
Correlation Co-efficient
Bullish
Jun 2004 – Dec 2007
0.986967
Bearish
Dec 2007 – Feb 2009
0.983528
Bullish
Feb 2009 – Dec 2010
0.888427
Bearish
Dec 2010 – Dec 2011
0.206862
Their study showed that FII Investment and Sensex are having strong positive correlation during bullish trend than correlation during bearish trend. Thus, FII may have more positive role during long term bullish trend rather than negative role during long term bearish trend. Vardhan and Sinha (2016) examined the influence of foreign institutional investments on the Indian stock market and its role in integration with the United States (US) equity market. They have used structural breaks to create sub-periods to employ different vector autoregression models. The stability of two parameters has been tested by the Chow test. From the above literature review we could determined out following objective.
Objectives: To study major structural breaks in FII invest in India.
Research Methodology Research Design: Descriptive Design is used to describe various events affecting FII flow significantly and causing the structural breaks in investment of FII in India. Data: For the study we used monthly data of net flow of FII investment in equity segment of India. We have collected secondary data from the Security Exchange Board of India (SEBI) website. Time period for the data collected is from March 1997 to April 2016. Tools and Techniques used in Analysis: Unit root test - Dickey-Fuller test to check stationary time-series data, Durbin Watson for autocorrelation in time-series data and JarqueBera test for normality of time-series data are used before analyzing structural break in monthly data of FII investment in equity market. Then, Chow test applied to check various structural breaks at identified time period. Chow test is a statistical and econometric test of whether the coefficients in two linear regressions on different data sets are equal. Bai-Perron test applied to detect multiple structural breaks in available data. Bai and Perron (2003) test is test to find multiple structural breaks automatically from data.
Data Analysis Unit Root Test: To test whether in our time-series data is stationary i.e. unit root does not exist, following null hypothesis can be tested. Null Hypothesis: FII_IN_EQUITY has a unit root Augmented Dickey-Fuller test t-Statistic
Prob.*
Augmented Dickey-Fuller test statistic -10.07802
0.0000
Test critical values:
1% level
-3.458845
5% level
-2.873974
10% level
-2.573472
*MacKinnon (1996) one-sided p-values.
As our p-value is less than 0.05, we can not accept our null hypothesis. Hence we can say that our time series data of FII investment in Indian stock market is stationary. Durbin-Watson (DW) stat is 2.078373. As DW stat is very near to 2, it shows that there is no auto correlation problem found in the data series of FII net flow in Indian stock market. Bell-shape of the data and Jarque-Bera test are useful to check whether the data is normally distributed or not. Following diagram and statistics checks the normality. 80
Series: FII_IN_EQUITY Sample 1997M03 2016M04 Observations 230
70 60 50 40 30 20 10
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis
3425.048 1110.000 28562.90 -16877.00 7548.597 0.833189 4.311801
Jarque-Bera Probability
43.10236 0.000000
0 -10000
0
10000
20000
30000
From the above figure and result of descriptive test we can see that P-value of Jarque-Bera is very small, which is less than 0.05. Thus we can not accept the null hypothesis of normally distributed data. But for sample sizes that are sufficiently large, violation of the normality assumption is virtually inconsequential (Brooks, 2008). Here we have monthly data of 19 years i.e. data from the initiation of FII investment in Indian stock market separately made accessible by SEBI. Appealing to a central limit theorem, the test statistics will asymptotically follow the appropriate distributions even in the absence of error normality1.
Major Significant Structural Breaks in FII Investment India In order to identify structural breaks in FII investment in Indian stock market we have applied two types of tests. A. Major events were identified and applied Chow Test to check structural break at specified period; and 1
The law of large numbers states that the average of a sample (which is a random variable) will converge to the population mean (which is fixed), and the central limit theorem states that the sample mean converges to a normal distribution.
B. In order to ensure that no structural break is missed out Bai-Perron Test was applied, as it helped to identify multi structural breaks in our data.
A. Major events were identified and applied Chow Test to check structural break at specified period To check whether various events did affect FII flow in Indian stock market, we have applied chow test with null hypothesis: No breaks at specified breakpoints. For this purpose time period considered is from March 1997 to April 2016 for which data is collected. We have found following events were significant to cause structural break in FII investment in Indian stock market. Oct 1999: 13th Lok Sabha Election On Oct 6,1999 , Vajpayee got majority market was rising before election results were out and once it was officially declared Market reacted with 5% move on election date and rising almost 12% before top was made on 14 Oct (Bramesh, 2014).
(Source: http://www.brameshtechanalysis.com/wp-content/uploads/2014/04/19991.png) Following table shows result of test of chow test applied to check significant of structural break during November 1999 due to result of 13th Lok Sabha Election. Chow Breakpoint Test: 1999M11 F-statistic
6.724896
Prob. F(1,228)
0.0101
Log likelihood ratio
6.685765
Prob. Chi-Square(1)
0.0097
Wald Statistic
6.724896
Prob. Chi-Square(1)
0.0095
Feb 2001: Ketan Parekh Scam Ketan Parekh scam created a historical impact on financial status of Bombay Stock Exchange and also on faith of investors in its working. Securities and Exchange Board of India (SEBI) was highly criticized as being reactive rather than proactive. The market regulator was blamed for being lax in handling the issue of unusual price movement and
tremendous volatility in shares over an 18-month period prior to February 2001(T. Singh, 2010). Following table shows result of test of chow test applied to check significant of structural break during February 2001 due to Ketan Parekh rig the Indian stock market. Chow Breakpoint Test: 2001M02 F-statistic
9.493513
Prob. F(1,228)
0.0023
Log likelihood ratio
9.382776
Prob. Chi-Square(1)
0.0022
Wald Statistic
9.493513
Prob. Chi-Square(1)
0.0021
May 2003: Significant role of P-Notes: India allowed FIIs to invest in Indian capital market since 1992. As the Know-YourInvestor or Know-Your-Client (KYC) norms were applicable for these foreign funds, the FIIs started to issue P-Notes, which helped the beneficiary (end-user) to remain anonymous. P-Notes are, in essence, overseas derivatives instruments (ODIs), which have Indian stocks and derivatives as their underlying securities ("P-Notes require more stringent monitoring," 2015). The investments through P-Notes were legitimised by SEBI in 2002, when D. R. Mehta was the Chairman of the capital market regulator. Total foreign institutional investors inflow of Rs 10,097 crore in October and November 2003, Rs 5,756 crore came through participatory notes. Also, what has stoked concerns is that most of the investment in 2003 through participatory notes started from May. Before April, such funds were to the tune of Rs 2,000 crore ("What are participatory notes?," 2004). Following table shows result of test of chow test applied to check significant of structural break during May 2003 due to heavy inflow through P-note Chow Breakpoint Test: 2003M05 F-statistic
17.92295
Prob. F(1,228)
0.0000
Log likelihood ratio
17.40471
Prob. Chi-Square(1)
0.0000
Wald Statistic
17.92295
Prob. Chi-Square(1)
0.0000
May 2004: 14th Lok Sabha Election The influence of FIIs on the movement of the Sensex became apparent after the 2004 general elections in India when the sudden reversal of FII flows triggered a panic reaction which resulted in very high volatility in the Indian stock market. During this period, the
Sensex experienced the worst single-day decline in its history. In the three months between April and June 2004, the index declined by about 17 per cent (Pal, 2005). Following table shows result of test of chow test applied to check significant of structural break during May 2005 due to results of 14th Lok Sabha Election. Chow Breakpoint Test: 2004M05 F-statistic
15.64600
Prob. F(1,228)
0.0001
Log likelihood ratio
15.26526
Prob. Chi-Square(1)
0.0001
Wald Statistic
15.64600
Prob. Chi-Square(1)
0.0001
Oct 2007: P-Note Crisis, Subprime Crises and Financial Crisis of 2007-08 On the 16th of October, 2007, SEBI (Securities & Exchange Board of India) proposed curbs on participatory notes which accounted for roughly 50% of FII investment in 2007. SEBI was not happy with P-Notes because it is not possible to know who owns the underlying securities and hedge funds acting through PNs might therefore cause volatility in the Indian markets. However the proposals of SEBI were not clear and this led to a knee-jerk crash when the markets opened on the following day (October 17, 2007). Within a minute of opening trade, the Sensex crashed by 1744 points or about 9% of its value - the biggest intra-day fall in Indian stock-markets in absolute terms. ("Participatory note," 2016) According to the US National Bureau of Economic Research (the official arbiter of US recessions) the recession, as experienced in that country, began in December 2007 and ended in June 2009, thus extending over 19 months. The Great Recession was related to the financial crisis of 2007–08 and U.S. subprime mortgage crisis of 2007–09. The Great Recession has resulted in the scarcity of valuable assets in the market economy and the collapse of the financial sector in the world economy. Following table shows result of test of chow test applied to check significant of structural break during October and December 2007 due to P-Note Crisis, Subprime Crisis and Financial Crisis of 2007-08
Chow Breakpoint Test: 2007M10 and 2007M12 2007M10
2007M12
2007M10
2007M12
F-statistic
12.68882
11.69479 Prob. F(1,228)
0.0004
0.0007
Log likelihood ratio
12.45663
11.50478 Prob. Chi-Square(1)
0.0004
0.0007
Wald Statistic
12.68882
11.69479 Prob. Chi-Square(1)
0.0004
0.0006
Satyam Scam, Lok Sabha Election, Bailout Program of Europe and End of Subprime Crisis of US In first week of January 2009, B Ramalinga Raju, founder and chairman of SCSL, confesses to fudging of accounts to the extent of about Rs 7,000-crore in a letter to the board (PTI, 2015). For the first time in the history of Indian stock markets, trading was halted at the upper circuit one minute after trading began on Monday in reaction to the United Progressive Alliance's impressive victory in the general elections (IST, 2009). When, as a negative repercussion of the Great Recession, the relatively fragile banking sector had suffered large capital losses, most states in Europe had to bail out several of their most affected banks with some supporting recapitalization loans, because of the strong linkage between their survival and the financial stability of the economy. As of January 2009, a group of 10 central and eastern European banks had already asked for a bailout. According to the US National Bureau of Economic Research the recession ended in June 2009 after 19 months subprime crisis. Following table shows result of test of chow test applied to check significant of structural break during January and June 2009. Chow Breakpoint Test: 2009M01 and 2009M06 2009M01
2009M06
2009M01
2009M06
F-statistic
28.77026
28.76981
Prob. F(1,228)
0.0000
0.0000
Log likelihood ratio
27.33230
27.33191
Prob. Chi-Square(1)
0.0000
0.0000
Wald Statistic
28.77026
28.76981
Prob. Chi-Square(1)
0.0000
0.0000
Announcement of GAAR General anti avoidance rules of taxation (GAAR) was introduced by the finance minister Pranab Mukherjee in his budget speech in March 2012. On 16th March 2012 Finance Minister, Pranab Mukherjee takes a tough stand and announces that the government will crack down on tax avoidance effective from fiscal year 2012–13 ("General anti-avoidance rule (India)," 2016). Following table shows result of test of chow test applied to check significant of structural break during March 2012 due to GAAR announcement. Chow Breakpoint Test: 2012M03 F-statistic
12.42577
Prob. F(1,228)
0.0005
Log likelihood ratio
12.20513
Prob. Chi-Square(1)
0.0005
Wald Statistic
12.42577
Prob. Chi-Square(1)
0.0004
Effect of Policy Announcement related FII Revision in framework for qualified foreign investors’ investment in equity shares and mutual fund schemes (SEBI Circular dated June 7, 2012): Vide the SEBI circulars dated August 09, 2011 and January 13, 2012, QFIs were allowed to invest in the schemes of Indian mutual funds and Indian equity shares, subject to the terms and conditions mentioned therein. Subsequently, vide the SEBI circular dated January 25, 2012, the eligibility criteria for a qualified DP were revised. Following table shows result of test of chow test applied to check significant of structural break during June 2012 due to circular of SEBI regarding QFIs allowed to invest in mutual funds. Chow Breakpoint Test: 2012M06 F-statistic
13.6108
Prob. F(1,228)
0.00028
Log likelihood ratio
13.3360
Prob. Chi-Square(1)
0.00026
Wald Statistic
13.6108
Prob. Chi-Square(1)
0.00022
Declaration of Minimum Alternate Tax Net outflows till April 27 have been Rs 817 crore. FII outflows come in the wake of recent tax notices demanding tax at 20 per cent on interest income, as opposed to five per cent without minimum alternate tax (Reporter, 2015). Following table shows result of test
of chow test applied to check significant of structural break during May 2015 due to declaration about MAT. Chow Breakpoint Test: 2015M05 F-statistic
5.395515
Prob. F(1,228)
0.0211
Log likelihood ratio
5.379441
Prob. Chi-Square(1)
0.0204
Wald Statistic
5.395515
Prob. Chi-Square(1)
0.0202
Greece Crisis June 2015: In the first week of June 2015 Greece asks the IMF to postpone the installment due until the end of the month. In the last week of June the prime minister, Alexis Tsipras announced that Greek banks will remain closed for a while; he also announced the imposition of capital controls (€60/day withdrawal limit; most foreign transfers banned). At the end of June month Greece misses a payment on an IMF loan and falls into arrears. August 2015: In the first week of August 2015 the Greek Stock Exchange reopened after being closed since June 25 and fell more than 16% with bank stocks losing an average of 30% in a single day's trading. In the last week the Chinese stock market crash affects Greece and the Greek Stock Exchange fell 10.54%. On 11th August China slashes the yuan’s fixing by a record 1.9 percent, sparking the biggest selloff since 1994("A Timeline: The Chinese Yuan's Journey to Global Reserve Status - Bloomberg," 2015). Following table shows result of test of chow test applied to check significant of structural break during July and August 2015 due to Greece Crisis Chow Breakpoint Test: 2015M07 and 2015M08 2015M07
2015M08
2015M07
2015M08
F-statistic
4.141958
4.073771
Prob. F(1,228)
0.0430
0.0447
Log likelihood ratio
4.140792
4.073225
Prob. Chi-Square(1)
0.0419
0.0436
Wald Statistic
4.141958
4.073771
Prob. Chi-Square(1)
0.0418
0.0436
B. Identification of multi structural breaks, in order to ensure that no structural break is missed out applying Bai-Perron Test. To perform the Bai-Perron tests of l globally optimized breaks the null is no structural breaks, along with the corresponding UDmax and WDmax tests. Multiple breakpoint tests Bai-Perron tests of 1 to M globally determined breaks Break test options: Trimming 0.15, Max. breaks 5, Sig. level 0.05 Allow heterogeneous error distributions across breaks
Sequential F-statistic determined breaks:
5
Significant F-statistic largest breaks:
5
UDmax determined breaks:
1
WDmax determined breaks:
5
Scaled
Weighted
Critical
F-statistic
F-statistic
F-statistic
Value
1*
23.688
23.688
23.688
8.580
2*
14.126
14.126
16.787
7.220
3*
15.210
15.210
21.897
5.960
4*
18.611
18.611
32.000
4.990
5*
15.841
15.841
34.762
3.910
Breaks
UDMax statistic*
23.688
UDMax critical value**
8.880
WDMax statistic*
34.762
WDMax critical value**
9.910
* Significant at the 0.05 level. ** Bai and Perron (2003) critical values. In both cases, the multiple breakpoint test indicates that there are 5 breaks. The UDmax and WDmax results show the number of breakpoints as determined by application of the unweighted and weighted maximized statistics. As both of the maximized statistics values exceed critical values and they are significant, both indicate the presence of multiple breaks.
Estimated break dates (A, B, C, D and E shown in figure): 1: 2009M04 (A) 2: 2009M04(A), 2013M06 (B) 3: 2003M06 (C), 2009M04(A), 2013M06 (B) 4: 2003M06 (C), 2006M04 (D), 2009M04 (A), 2013M06 (B) 5: 2000M02 (E), 2003M06 (C), 2006M04 (D), 2009M04 (A), 2013M06 (B) The above points show the global optimizers for the breakpoints for each number of breaks.
Cum_FII_Eq 900,000
E
C
D
A
B
800,000 700,000 600,000 500,000 400,000 300,000 200,000 100,000 0 1998
2000
2002
2004
2006
2008
2010
2012
2014
A. April 2009: Upward trend started. End of Subprime in US and Bailout program of Europe. B. June 2013: Downward Trend: Reduction in P-Notes flow due to time to time action of SEBI to regulate it (IST, 2013). C. June 2003: Up trend started. Using P-Notes FII could pump huge amount of funds in Indian stock market. D. April 2006: Downward Trend Started: As government increased debt limit from US $1.75 billion to US $2 billion and US $0.5 billion to US $1.5 billion for FII/Sub
Account
investments
in
Government
securities
and
Corporate
Debt,
respectively(Uchil, 2006). E. February 2000: Upward Trend: Ketan Prekh rig the market using K-10 stocks (he dealt in such securities having low liquidity)
Conclusion Since opening of Indian economy there has been continuous flow of Foreign Institutional Investors found in Indian stock market. Today FIIs have emerged to be one of the most dominant groups of investors with ownership of significant component of traded. Though due to numerous events at national and international level affected FII flow. In this study we analysed when and why various structural breaks happen in FII investment flow in Indian stock market due to such national and international events viz. regulatory measures related to FII in India, Lok Sabha election, various scams in Indian stock market, global crisis and their remedial actions i.e. bail-outs affected FII investment in Indian stock market significantly using chow test. We could also found various time-periods using multiple structural breaks through Bai-Perron test. Such structural breaks we could not spot referring trend of FII investment in Indian stock market as well as various national and international events. Such events which we could identified through multiple structural beaks are rigging of market by Ketan Parekh affected FII investment in Indian stock market. Thus, chow test and bai-Perron test both have their own use and benefits to apply to study structural break and multiple structural breaks respectively. Thus, using Chow Test and Bai-Perron test we have identified various events which were major causes for structural breaks in FII investment in Indian stock market.
References Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 47-78. Bai, J., & Perron, P. (2003). Critical values for multiple structural change tests. The Econometrics Journal, 6(1), 72-78. Bajpai, N. (2011). Global financial crisis, its impact on India and the policy response. Columbia Global Centers/South Asia, Columbia University.
Bramesh. (2014, 19 Apr 2014). Nifty reaction to Lok Sabha election results. Retrieved from http://www.brameshtechanalysis.com/2014/04/how-nifty-would-react-after-electionresults/ Brooks, C. (2008). Introductory Econometrics for Finance. Cambridge CB2 8RU, UK: Cambridge University Press. Choudhury, P. R. (2014). Multiple Structural Breaks in India’s GDP: Evidence from India’s Service Sector. Paper presented at the 10th Annual Conference on Economic Growth and
Development,
Indian
Statistical
Institute,
New
Delhi.
http://www.isid.ac.in/~epu/acegd2014/papers/PurbaRoyChoudhury.pdf Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica: Journal of the Econometric Society, 591-605. General anti-avoidance rule (India). (2016) Wikipedia, the free encyclopedia. IST. (2009, 18 May 2009). Sensex skyrockets, trading halted on UPA victory. business.rediff.com. from http://business.rediff.com/slide-show/2009/may/18/slideshow-1-sensex-rockets-on-upa-victory.htm IST. (2013, 19 Aug 2013). FII sell-off: assets under custody drops to 8-month low at $ 206 bn. The Hindu. Retrieved from http://www.thehindu.com/business/Economy/fiiselloff-assets-under-custody-drops-to-8month-low-at-206-bn/article5038459.ece Joshi, M. C., & Desai, J. N. (2015). Role of Foreign Institutional Investors In India: An Investigation. International Journal Of Research In Commerce, Economics & Management, 5(10), 1-5. Narayan, P. K., Narayan, S., & Mishra, S. (2013). Has the structural break slowed down growth rates of stock markets? Economic Modelling, 30, 595-601. P-Notes require more stringent monitoring. (2015, 8 Aug 2015). The Hindu. Retrieved from http://www.thehindu.com/business/Economy/pnotes-require-more-stringentmonitoring/article7516608.ece Pal, P. (2005). Volatility in the Stock Market in India and Foreign Institutional Investors. Economic and Political Weekly, 40(8), 7-8. Participatory note. (2016) Wikipedia, the free encyclopedia. PTI. (2015, 10 Apr 2015). Satyam Computer scam: Chronology of events. The Financial Express. Retrieved from http://www.financialexpress.com/article/companies/satyamcomputer-scam-chronology-of-events/62394/ Reporter, B. S. (2015, 27 Apr 2015). MAT effect: FIIs seen taking a step back from India. Business
Standard.
Retrieved
from
http://www.business-
standard.com/article/markets/mat-effect-fiis-set-to-break-15-month-buying-streak-inindian-debt-115042700226_1.html Schätz, A. (2010). Macroeconomic Effects on Emerging Market Sector Indices. Journal of Emerging Market Finance, 9(2), 131-169. doi: 10.1177/097265271000900202 Singh, M. (2007). Use of Participatory Notes in Indian stock markets and Recent Regulatory Changes. WP/07/291. Working Paper. International Monetary Fund. Singh, T. (2010, 5 Sep 2010). Ketan Parekh Scam: The Stock and Bull Story. Retrieved from http://kaleidoscopeonline.blogspot.com/2010/09/ketan-parekh-scam-stock-and-bullstory.html Solanki, D., & Kachhwaha, K. (2010). An Analysis: Impact of Greece Economic Crisis on Indian Economy. Financial Times. Tests for structural breaks in time-series data | Stata 14. Tests for structural breaks in timeseries data. Retrieved June, 2016, from http://www.stata.com/new-in-stata/structuralbreaks/ A Timeline: The Chinese Yuan's Journey to Global Reserve Status - Bloomberg. (2015, 30 Nov
2015).
Bloomberg.
Retrieved
from
http://www.bloomberg.com/news/articles/2015-11-30/a-timeline-the-chinese-yuan-sjourney-to-global-reserve-status Uchil,
S.
(2006).
FII
Investments
in
Debt
Securities.
SEBI
Retrieved
from
http://www.sebi.gov.in/circulars/2006/fii2006.pdf. Vardhan, H., & Sinha, P. (2016). Influence of Foreign Institutional Investments (FIIs) on the Indian Stock Market: An Insight by VAR Models. Journal of Emerging Market Finance, 15(1), 49-83. doi: 10.1177/0972652715623677 What are participatory notes? (2004, 26 Jan 2004). The Economic Times. Retrieved from http://articles.economictimes.indiatimes.com/2004-0126/news/27414054_1_participatory-notes-overseas-corporate-bodies-india-basedforeign-brokerages
