FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET: A CASUALTY ANALYSIS During the early phases of post-independence, Government of India initiated different steps to ensure self-reliance of the economy through promoting import substitution. It stressed upon financing its current account deficit through international debts and other official assistance. But in 1990, policy makers realised the need to review their decisions particularly for circumscribing yoke international debts. To reanimate the fatally poised system Indian economy unclogged the route of foreign investment. Approval of foreign investment in the form of direct as well as institutional investment revamped entire financial system of India. However, there is a usual debate regarding the cause and effect relationship between foreign investment particularly institutional investments and performance of capital market, i.e. whether foreign institutional investments are allured by good stock return or the same leads to better performance of stock market. INTRODUCTION DURING the 1990s Government of India realised the need to rethink its policy of being self-reliant, promoting import substitution and financing its current account deficit through international debts and other official assistance. The innovative thinking of that period paved new avenues for lowering the cost of capital, access of cheap global credit by allowing foreign investment in domestic market. Inflow of foreign capital in any form of investment surely leads to international economic integration and stimulation. The trans-national investment of funds by non-residents may be in two forms, viz. Foreign Direct Investment (FDI)
FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET / 277 Foreign Institutional Investment (FII) Inflow of FDI creates an augmented capacity that not only provides access to funds but also facilitates more employment opportunities, greater productivity, complementary skills and transfer of technology. Such investment is usually treated to be a long term investment having a significant influence and control over the sector / unit in which investment is made. On the contrary, FII is hot money pumped in by foreign institutions established / incorporated outside India. Such investment is made in Indian securities and ensures inflow only for a shorter period. Initially due to stricter norms the inflow of FII was restricted. But increment in ceiling for overall investment, augmentation in limits of government securities and simplification of registration norms dramatically increased net investment of FIIs. Portfolio of foreign institutional investors may comprise of following financial instruments: Shares / debentures / warrants of companies listed or to be listed on a recognised stock exchange Dated government securities Units of domestic mutual funds Units floated under collective investment schemes Derivatives traded on a recognised stock exchange Commercial paper Security receipt Figure 1 on the following page depicts the trend of net FDI and net portfolio investment (Net PI) from 2000-01 to 2012-13. As depicted in the Fig. 1 foreign investment registered remarkable growth from 2000-01 to 2012-13. But Net PI has always been more volatile and also vulnerable to global risk. Net inflow of PI was even negative during 2008-09. Besides the year 2002-03 and 2011-12 also experienced downfall in net flow of PI. That is the reason why such investment is treated as hot investment and exerts strong influence on the total inflows into the economy. Portfolio investment by foreign institutional investors acts as trigger as well as catalyst for the market performance. FII boosts the production, improve corporate governance, enhance efficiency of financial market and promote financial innovation. It also assists in alignment of assets prices to fundamentals and hereby stabilise financial markets. However, some researchers are of the opinion that instead of stabilising the economy FII causes volatility in the market. They argue that investment through FII brings huge liquidity to the capital market. But as these investors are active
278 / INDIAN JOURNAL OF PUBLIC ADMINISTRATION 278 / VOL. LX, NO. 2, APRIL-JUNE 2014 FIG. 1: NET INFLOW OF FOREIGN DIRECT INVESTMENT AND FOREIGN PORTFOLIO INVESTMENT SOURCE: Reserve Bank of India therefore they frequently change their portfolio and this leads to volatility in the stock market. There is also a debate on the casualty effect of FII, i.e. whether there is uni-directional relationship of FII with stock return or is it bi-directional? Some researchers believe that foreign institutional investors park their money in an economy in anticipation of earning good returns. Therefore it is return of the stock that allures them to make investment in any other economy. On the contrary the other group of researchers advocate that market moves in tune with the movements of FII, i.e. it is the FII that leads to changes in stock market. The inflow / outflow of FII bring changes in stock prices. The study of Gordon and Gupta (2003) also highlighted the contradictory findings regarding the casual relationship between FII and stock market performance. The study emphasised upon the need to investigate whether FIIs are the cause or effect of stock market fluctuations. In this context the present article attempts to explore the cause and effect relationship between net inflow of FII and stock return. REVIEW OF RELATED LITERATURE A wide range of studies have been undertaken to dissect the determinants of foreign investment inflow and its pros and cons to the economy. Recent global oscillations adduced to be responsible for the increased attention of researchers to the concept of casualty of foreign investment inflow. Some of the prominent works done in the context of FII have been outlined in the following paragraphs. Bohn and Tesar (1996) established a positive relation between equity flows and stock returns using monthly data for Mexico. Choe et al. (1998)
FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET / 279 investigated the impact of foreign investment on Korean stock market. The study analysed daily data from November 1996 to the end of 1997 and reported that before Asian crisis there was a positive feedback trading but during crisis period the effect disappeared. Further no destabilising effect of trade by foreign investors has been observed by the researchers. The study pointed out that large sales by foreign investors have not been followed by negative abnormal returns as market adjusted itself quickly and efficiently. Chakrabarti (2001) observed the difference in the nature of flow of FII during pre-crisis and post-crisis period. In post-crisis period Bombay Stock Exchange returns become sole driving force behind FII inflow. The study established correlation between FII and contemporaneous returns in capital market. It also highlighted that high correlation doesn t necessarily evidenced FII flows, which causes price pressure. Kumar (2001) analysed the monthly data of SENSEX BSE index and net inflow of FII into India from January 1993 to December 1997. The study inferred that investment by foreign institutions is mainly driven through fundamental factors rather than technical or short-term factors. The study used regression analysis to establish relationship between lagged values of SENSEX to net FII. The results indicated bi-directional casualty from FII to sensex and also from sensex to net FII. However, Mukherjee et al. (2002) found that investment flow in an economy is caused by return from investment in equity market and other way round does not exist for Indian capital market. Mazumdar (2004) analysed the impact of flow of FII on Indian stock market. The study focused upon liquidity and volatility aspects and established positive relationship between FII and liquidity of Indian stock market. However, no evidence of increased volatility of equity returns could be set out by the results. Ekeocha (2008) remarked that foreign portfolio investment, though volatile in nature is yet very crucial to bridge the gap between savings and investment and to support investment in the economy. The study covered a period of around 20 years from 1986 to 2006 and investigated long term determinants of foreign portfolio investment in Nigerian economy. The result set out positive relation of foreign investment with real rate of return on investments in the capital market, real interest rate, and investment. However foreign investment was found to be negatively associated with real exchange rate, market capitalisation, trade degree of openness and institutional quality in Nigeria. Prasanna (2008) investigated the relation of FII with some specific characteristics of corporate entities including ownership structure, financial
280 / INDIAN JOURNAL OF PUBLIC ADMINISTRATION 280 / VOL. LX, NO. 2, APRIL-JUNE 2014 performance and stock performance. The study found that investment decisions of foreign investors are highly affected by share prices and earnings per share. The study also noted the preference of foreign investors in favour of companies having voluminous ownership of general public and lesser family shareholding of promoters. Mishra et al. (2009) remarked positive correlation between inflow of FII and return of stock market represented by monthly return of BSE. The study covered a period of 17 years from 1993 to 2009. It further pointed out that the effect on Indian capital market is fairly explained by net inflows of FIIs. Singh and Singh (2012) examined the role of FII in the growth of Indian capital market from 1992-93 to 2010-11. The study applied correlation, OLS regression and independent sample t test to the data. The results indicated there is significant impact of FIIs on NSE index: CNX-Nifty. A moderate impact of FIIs has been noted on the fluctuations of the market. Though there is an availability of literature on FIIs inflow but its casualty with Indian capital market has not been much envisaged. In this context the present article attempts to examine the cause and effect relationship between FII and return of Indian stock market. RESEARCH METHODOLOGY Data The present article investigates the relationship between FII (net) and Indian capital market, i.e. whether FII s net inflows is due to good return from Indian capital market or Indian stock prices boom due to net inflow of FIIs in the economy. The data used in the study is primarily secondary data and has been taken from Reserve Bank of India. To capture the minor issues, monthly data has been considered for the study. The study covers a period of around 20 years from April 1993 to July 2013 and therefore comprises of 244 3 = 732 observations. Indian capital market is proxy by logarithm return calculated for two indices, viz.: Sensex: Index of Bombay stock exchange which is Asia s first stock exchange CNX Nifty Index: India s other leading exchanges, i.e. National stock exchange. Returns have been calculated on the basis of closing value of index through following value.
FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET / 281 Where, P is the closing value of index and t denotes the time and t-1 denotes the closing value in previous month. Return calculated for BSE has been represented by BR and Return calculated for NSE has been represented by NR. Analysis of Data A) Test of Normality and Unit Root: At the outset the normality of data has been checked through Jarqueberra test. As the data is suitable for further analysis only when it is stationary in nature therefore Augmented Dickey Fuller (ADF) test has been conducted to check the absence of unit root in data. The test checks the following null hypothesis: Null Hypothesis There is unit root in the series. In other words, the data is not stationary in nature. Alternate Hypothesis There is no unit root in the series, i.e. data is stationary in nature. B) Test of Co-integration After confirming the absence of unit root, Johansen s unrestricted cointegration rank test has been administered to check the possibility of any long-term relationship between FII (net) and return. On the basis of two statistics, viz., trace test statistics and maximum Eigen value test statistics the co-integration test accepts / rejects following null hypotheses. Null Hypothesis (Trace test) Number of distinct co-integrating vector(s) is less than or equal to number of co-integration relations. Null Hypothesis (Maximum Eigen value) There is exactly r number of co-integrating relations against the alternative of r+1 co integrating relations. C) Test of Casualty To investigate the direction of relationship between the studied variables Granger casualty test has been applied. The test is helpful in ascertaining whether there is uni-directional or bi-directional relationship between two variables. The test also assess whether one time series is useful in forecasting another or not.
282 / INDIAN JOURNAL OF PUBLIC ADMINISTRATION 282 / VOL. LX, NO. 2, APRIL-JUNE 2014 Null Hypotheses The present article applied Granger test to confirm following six hypotheses: BR does not Granger Cause FII (net). FII (net) does not Granger Cause BR. NR does not Granger Cause FII (net). FII (net) does not Granger Cause NR. NR does not Granger Cause BR. BR does not Granger Cause NR. The hypothesis will be accepted only when the probability of F statistics is more than five per cent and will be rejected if the same is found to be less than five per cent. FINDING AND ANALYSIS Foreign investment by institutional investors has been observed as highly volatile during the study period. The returns at BSE seems to be more volatile as compared to NSE. The descriptive statistics of net inflow of FII, BR and NR have been depicted in Table 1 and Fig. 2. TABLE 1: DESCRIPTIVE STATISTICS Particulars Net FII BR NR Mean 27.2297 0.0086 0.0087 Maximum 295.0691 0.1931 0.1815 Minimum -134.6139-0.2789-0.2703 Standard Deviation 63.1163 0.0655 0.0650 Skewness 1.5637-0.3614-0.3343 Kurtosis 6.8455 4.2336 4.0615 Jarque-berra Test Statistics 249.7845 20.7828 15.9987 Probability 0.0000 0.0000 0.0003 Number of Observations 244 244 244 SOURCE: Author s calculation. Further, the results of Jarque-berra test reject the possibility of normality of data and the present data may be assumed to be non-normal in nature. However, normality of data is not usually observed in financial data therefore we may ignore the problem and could further proceed to check whether the data is stationary in nature or not.
FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET / 283 300 FII 200 100 0-100 -200 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 BR.2.1.0 -.1 -.2 -.3 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 NR.2.1.0 -.1 -.2 -.3 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 SOURCE: Author s calculation.
284 / INDIAN JOURNAL OF PUBLIC ADMINISTRATION 284 / VOL. LX, NO. 2, APRIL-JUNE 2014 The data is assumed to be stationary if it does not have unit root. To check the possibility of unit root ADF test has been conducted (Table 2). The test presumes the null hypothesis of presence of unit root in the data. Null hypothesis of ADF test can be accepted only when the statistics of test is less than the critical value at five per cent level of significance, i.e. the value of probability is more than 0.05. TABLE 2: RESULTS OF ADF TEST Particulars ADF Statistics Critical Value Probability Null Hypothesis FII (net) -9.44-2.8732 0.0000 Rejected BR -12.13-2.8732 0.0000 Rejected NR -12.06-2.8732 0.0000 Rejected SOURCE: Author s calculation. The comparison of ADF statistics with critical value at five per cent level of significance for all the three variables demonstrates that the absolute statistics is more than the absolute critical value. Therefore we cannot accept the null hypothesis and reject the possibility of unit root among variables. In other words the studied data is stationary in nature and eligible of being further tested without any conversion to difference order. As stated earlier before examining casualty of FII (net) with returns we will try to catechize the possibility of presence of any co-integrated equation (s). This has been done through Johansen co-integration test. The test examines the co-integration of time series. Table 3 represents the results of the test. TABLE 3: RESULTS OF JOHANSEN CO-INTEGRATION TEST Hypothesised Eigen Trace Max Eigen Critical Probability No. of Co- Value Statistics Value Value integrated Statistics equations None 0.1662 99.6251 43.4357 29.7971 0.0000 At most 1 0.1441 56.1894 37.1958 15.4947 0.0000 At most 2 0.0764 18.9936 18.9936 3.8415 0.0000 SOURCE: Author s calculation. The statistics of Trace and Max Eigen value are more than the critical value at five per cent level of significance which indicates the nonacceptability of null hypothesis. The probabilities for different levels of number of co-integrated equations also confirm the rejection of null
FOREIGN INSTITUTIONAL INVESTMENT AND INDIAN CAPITAL MARKET / 285 hypothesis. Therefore we can reject the null hypothesis and may infer that there is a presence of even more than two co-integrated equation(s) among the three variables, i.e. FII (net), BR and NR. To explore the direction of relationship, i.e. whether one way relationship exists between variables or if there is two way directional relationship between variables, Granger casualty test has been conducted. The test investigates casualty between two variables (net FII and BR or net FII and NR or BR and NR). Table 4 exhibits the results of Granger casualty test. TABLE 4: RESULTS OF GRANGER CASUALTY TEST Null Hypothesis F-Statistic Probability Result 1. BSE Return does not Granger 0.45498 0.6350 Accepted Cause FII (net) 2. FII (net) does not Granger 3.77208 0.0244 Rejected Cause BSE Return 3. NSE Return does not 0.63182 0.5325 Accepted Granger Cause FII (net) 4. FII (net) does not Granger 4.32226 0.0143 Rejected Cause NSE Return 5. NSE Return does not Granger 2.60176 0.0763 Accepted Cause BSE Return 6. BSE Return does not Granger 2.03642 0.1328 Accepted Cause NSE Return SOURCE: Author s calculation. The results of Granger casualty test exhibit rejection of all null hypotheses except second and fourth. It indicates absence of any casualty between return of two stock exchanges, i.e. return of BSE and return of NSE. However, in respect of FII (net) and returns uni-directional relationship has been evidenced. The probability of F statistics rejects the second and fourth null hypotheses. Therefore we have sufficient evidence to conclude that investment by foreign institutional investors Granger cause return of leading stock exchanges of India, i.e. BSE and NSE. But stock return is not a significant alluring factor to foreign investors. CONCLUSION The study analysed monthly data of FII (net) and attempted to establish its relationship with the returns calculated on the basis of two leading Indian stock exchanges, i.e. BSE and NSE for a period of around 20 years
286 / INDIAN JOURNAL OF PUBLIC ADMINISTRATION 286 / VOL. LX, NO. 2, APRIL-JUNE 2014 from April 1993 to July 2013. The results of co-integration indicate the possibility of more than two co-integrated equations among three variables, i.e. Net FII, BR and NR. Granger casualty test confirms uni-directional relation between FII (net) and return. The study found that investment by foreign institutional investors Granger cause return of leading stock exchanges of India, i.e. BSE and NSE. However, the volatility or trend of return does not have significant impact upon the net inflow of FII into India. Therefore the policy framework for liberalising/immobilising FII investment should be formulated with due consideration to its impact upon the Indian capital market. A SELECT READINGS Bohn, H., and Tesar L. U. S. Equity Investment in Foreign Markets: Portfolio Rebalancing or Return Chasing? American Economic Review, 86 (2), 77-81, 1996. Chakrabarti R. FII Flows to India: Nature and Causes, Money and Finance, 2 (7): 61-81, 2011. http://www.icra.in/files/moneyfinance/octdec2001fii.pdf Choe et., al. (1998), Do Foreign Investors Destabilize Stock Markets?: The Korean Experience in 1997", NBER Working Paper 6661, NBER Cambridge M A. Retrieved from http://www.nber.org/papers/w6661.pdf Ekeocha, P. C. Modelling the Long Run Determinants of Foreign Portfolio Investment in an Emerging Market: Evidence from Nigeria, International Conference on Applied Economics ICOAE 2008. Retrieved from http://kastoria.teikoz.gr/icoae2/wordpress/ wp-content/uploads/articles/2011/10/034-2008.pdf Gordon, J. and Gupta, P., Portfolio Flows into India: Do Domestic Fundamentals Matter, IMF Working Paper Number: WP/03/02, 2003. Kumar, S. Does the Indian Stock Market Play to the tune of FII Investments?: An Empirical Investigation, ICFAI Journal of Applied Finance, 7 (3): 36-44, 2001. Mazumdar, T. FII Inflows to India; Their effect on stock market liquidity, ICFAI Journal of Applied Finance, 10 (7): 5-20, 2004. Mishra et. al. Role of FIIs in Indian Capital Market, The Research Network, 4(2): 30-34, 2009. Mukherjee et. al. Foreign Institutional Investment in the Indian Equity Market: An Analysis of Daily Flows during January 1999-May 2002. ICRA Bulletin on Money & Finance, April-September 2002, pp. 21-51. Retrieved from http://www.icra.in/files/ MoneyFinance/aprsep2002equity.pdf Prasanna, P.K. Foreign Institutional Investors: Investment preferences in India, JOAAG, 3 (2), 2008. Retrieved from http://joaag.com/uploads/4_prasannafinal3_2_.pdf. Singh K B and Singh S K. Impact of FII s Investment on the Indian Capital Market, IJRCM, 3 (12), pp. 61-63, 2012. Retrieved from ijrcm.org.in/ download.php?name=ijrcm-1-vol-3_issue-12-art-13.pdf