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\title{Trends and Patterns of FDI and FII in India-Implications for the Future}
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\begin{document}

             \author[1]{Mr.Tanu  Aggarwal}

             \affil[1]{  Amity University Noida}

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\date{\small \em Received: 15 December 2016 Accepted: 2 January 2017 Published: 15 January 2017}

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\begin{abstract}
        


Fiscal crisis in global markets have made the outlook of the Indian economic system more depressive but the idiosyncratic liberalization and globalization gave the emanation to the phenomena of the foreign investments i.e. FDI and FII in India. International economic integration plays vital role in economic development of the country. The foreign capital is one of the important means of the economic development of the country. FDI and FII are the two important investments in the global capital. The Karl Pearson Correlation and multiple Regressions are used to study the relation and impact of FDI, FII and BSE Sensex. The Correlation shows that there is strongly positive correlation between FDI and Sensex and weak negative correlation between FII and Sensex. On the other hand, Multiple Regressions shows that there is no impact of FII and FDI on BSE Sensex.

\end{abstract}


\keywords{foreign investment, FDI (foreign direct investment), FII (foreign institutional investment) and sensex.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
DI refers to the capital flows from the rest of the world which are invested in the production capacity of the economy. FDI facilitates international trade and transfer of knowledge skills and technology \hyperref[b3]{1} The FDI is preferred over FII since it is considered as the most important beneficial form foreign investment for economy as a whole. The direct investment augments the capacity to ensure that the capital inflows get translated into additional production. In the case of the foreign institutional investment that flows in the secondary markets affects the increase in capital availability in general and this money is considered as the hot money that comes and goes. Therefore FDI is considered as more stable than FII . On the other hand FII refers to the investor or investment fund which is registered in the country outside the one in which the investor is investing. . a) Routes of FDI \hyperref[b5]{3}  
\section[{Automatic Route}]{Automatic Route}\par
The FDI is allowed under the automatic route without the prior approval of the either the government or the Reserve bank of India related to all activities mentioned in the consolidated FDI policy issued by the Government of India from time to time. 
\section[{Government Route}]{Government Route}\par
The activities that are not covered under automatic route require the approval of the government which is considered in the foreign investment portfolio board (FIPB), Department of Economics Affairs, and Ministry of Finance. 
\section[{b) Routes of FII 4 Equity Investment}]{b) Routes of FII 4 Equity Investment}\par
The 100 percent investment is related to equity instrument or can be done through70 percent (Equity Investment). 
\section[{Percent Debt}]{Percent Debt}\par
The 100 percent investment has to be made in the debt instruments only (Debt Investment). 
\section[{c) Importance of FDI and FII}]{c) Importance of FDI and FII}\par
The need of the foreign capital is important in the form of the FDI and FII for the development of the infrastructure which includes railways, sea ports, roads and warehouses. The rapid industrialization also takes place from the period 1991 which further strengthened the need of foreign capital. Many of the developing countries suffer because of the problem of the infrastructure. In other countries the interest rate is around 1 to 3 \% but in India it is around 7 to 9 \% so the investors wants to invest in India where they get maximum return on their investments. 
\section[{Mr. Tanu Aggarwal}]{Mr. Tanu Aggarwal}\par
? \& Dr. Priya Solomon ? investment), Fii (foreign institutional investment) and sensex.\par
II. 
\section[{Review of Literature}]{Review of Literature}\par
Dr. Jasbir Singh, Ms. Sumita Chadha and Dr. Anupama Sharma (2012) focus on the role of the foreign direct investment in India: An Analytical Study. It shows that foreign investment is increasing in terms of FDI and FII and FDI has better performance which attracts maximum amount of foreign capital.\par
Dr. Syed Tabassum and Prof. S. Pradhasardhi (2012) have examined the impact of flows of FDI and FII on Indian Stock Exchange. The correlation analysis shows that there is strong relation between Sensex and Nifty. The correlation analysis shows that there is strong correlation between FDI, Sensex and Nifty and on the other hand there is moderate positive correlation between FII, Sensex and Nifty.\par
Vinay Kumar (2014) have precipitated the trend of FDI in India and its Impact on economic growth. The Karl Pearson correlation shows that FDI and FII have weak positive correlation between them and on the other hand FDI have positive correlation with Indian GDP.\par
Mohmmad Iftekhar Khan and Amit Banerji(2014) conducted the study on drivers, impact and pattern of foreign direct investment in India. The unit root test and times series analysis shows that FPI and FDI are non-stationary.\par
Sirisha S and Malayadri I(  {\ref 2015}) have investigated the study on changing trends in flow of FDI. The CAGR(Compounded Annual Growth Rate) percentage is used to show that Luxemberg has highest inflows of FDI and on the other hand communication and manufacturing sector has the highest level inflows of foreign direct investment.\par
The analytical study of trend of FDI in India has been conducted by Naveen Sood(2015). The correlation and regression shows that FDI and FII is insignificant and on the other hand association and dependence of GDP in India is found to be statistically insignificant.\par
IV. 
\section[{Data Collection and Research Methodology}]{Data Collection and Research Methodology}\par
The quantitative approach is used which shows that the research design for the current study is descriptive 6 cum exploratory \hyperref[b9]{7} V. 
\section[{Hypothesis}]{Hypothesis}\par
. The study is based on the secondary sources. The required data related to FDI and FII have been collected from the various sources that is the bulletins of the Reserve bank of India, publications from the Ministry of the Commerce, Government of India. The closing index value of each year is taken from the BSE website. The Karl Pearson coefficient of correlation and Multiple Regression is used to know the relation and impact of FDI and FII on BSE Sensex. 
\section[{8}]{8} 
\section[{FDI of the Study}]{FDI of the Study}Ho 9 
\section[{H1}]{H1}\par
There is no significant impact of FDI on BSE Sensex. 10 H1 There is significant impact of FII on BSE Sensex.\par
There is significant impact of FDI on BSE Sensex. FII Ho There is no significant impact of FII on BSE Sensex.  
\section[{Objectives of the Study}]{Objectives of the Study}\par
? To study the trends and pattern of foreign capital (FDI and FII) flow to India. 
\section[{? To study the correlation between FDI, FII and}]{? To study the correlation between FDI, FII and}\par
Sensex. ? To study the impact of FDI and FII on Sensex. Kanta Rani and Sanjiv Kumar (2015) analyze the dynamic interaction between foreign investment and Indian Stock Market. The Karl Pearson correlation shows that FDI have high correlation with Sensex and Nifty. Trends and Patterns of FDI and FII in India-Implications for the Future 
\section[{Interpretation}]{Interpretation}\par
The table \hyperref[tab_0]{1} and Graph 1 presents the amount of flow of the FDI and FII in terms of US\$ million. The flow of the FDI has shown an upward trend during the considered period but during the period 2015-2016 and 2011-2012 the flow of FDI is highest that is 55456 and 46555. The flow of FII has shown the mixed trend, during the period of 2008-09 and 2015-2016 it is negative that is (-) 3515 and (-) 15016. When the flow of the FDI and FII are compared the flow of the FII is less than flow of the FDI in India.   
\section[{Interpretation}]{Interpretation}\par
The Karl Pearson 11 is applied to the study of the relationship of the FDI, FII and BSE Sensex. There is a strong positive correlation between FDI and Sensex and FDI and FII. When it comes to the FII there is a weak negative correlation between FII and FDI and FII and Sensex. 
\section[{VI. Multiple Regressions of Fdi, Fii and Bse Sensex}]{VI. Multiple Regressions of Fdi, Fii and Bse Sensex}\par
In case of multiple regressions there are more than two independent variables and the multiple regression models would look like: BSE Sensex= bo + b1 (FDI) + b2 (FII) So now it is easy to predict about the BSE Sensex on the basis of these models. The b-values tell that what degree of each dependent variable affects the independent variable if all other independent variables are held constant.   
\section[{Interpretation}]{Interpretation}\par
The model summary helps to know the strength of the relationship between the model and the dependent variable. R (Multiple correlation coefficients) shows that correlation between the observed and the model predicted values of the dependent variable. Its small values shows the weak relationship. R, square the coefficients of determination is .406, it shows that the model explains 40.6 \% variation. In other words the independent variables FDI and FII are able to explain around 40.6 \% of the dependent variable Sensex.  
\section[{Interpretation}]{Interpretation}\par
The ANOVA shows the acceptability of the model from a statistical perspective. The Regression row displays information about the variation accounted for by the model. The residual row displays information about the variation that has not been accounted by the model. The regression sum of squares is less than residual sum of squares which indicates 40.6\% variation in Sensex is explained by the model. According to the F-Statistic (.125) is greater than .05 which is found insignificant.  
\section[{Interpretation FII}]{Interpretation FII}\par
The p-value related to FII in Table \hyperref[tab_6]{7} is .179 which is greater than .05 so null hypothesis related to FII is accepted (there is no significant impact of FII on Sensex) and alternate hypothesis is rejected. 
\section[{FDI}]{FDI}\par
The p-value related to FDI is .072 which is greater than .05 so null hypothesis related to FDI is accepted (there is no significant impact of FDI on BSE Sensex) and alternate hypothesis is rejected. 
\section[{VII.}]{VII.} 
\section[{Conclusion}]{Conclusion}\par
The FDI and FII helps to develop the Indian economy and also gives the advantages to the Indian industry for the technological up gradation, helps in the utilization of the human and the natural resources with greater efficiency. Since the FDI is consider as the central for the India's integration into global production chains. The current study shows that there is a strongly positive correlation between FDI and Sensex and weak negative correlation between FII and Sensex. Using the multiple regressions the results depicts that there is there is no significant impact of FII and FDI on BSE Sensex.\par
As the FDI has strongly positive correlation between FDI and Sensex so the government should emphasize on FDI more as it leads to the high economic growth and employment opportunities in the country. In case of FII, the foreign investors can exit from the Indian Market whenever they want as it has been proved that there is no impact of FII on BSE Sensex. So for the developing country like India, FDI is considered as the most beneficial form of foreign investment for the economy as a whole and is of long-term nature.  \begin{figure}[htbp]
\noindent\textbf{1} \par 
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\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{7}{l}{FDI(FOREIGN DIRECT}\tabcellsep \tabcellsep FII(FOREIGN INSTITUTIONAL\\
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\multicolumn{2}{l}{2006-2007}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{22825}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 3224\\
\multicolumn{2}{l}{2007-2008}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{34842}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 20327\\
\multicolumn{2}{l}{2008-2009}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{41872}\tabcellsep \tabcellsep \tabcellsep \tabcellsep (-)15016\\
\multicolumn{2}{l}{2009-2010}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{37744}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 29047\\
\multicolumn{2}{l}{2010-2011}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{34846}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 29421\\
\multicolumn{2}{l}{2011-2012}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{46555}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 16811\\
\multicolumn{2}{l}{2012-2013}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{34297}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 27581\\
\multicolumn{2}{l}{2013-2014}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{36045}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 5008\\
\multicolumn{2}{l}{2014-2015}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{45147}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 40922\\
\multicolumn{2}{l}{2015-2016}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{55456}\tabcellsep \tabcellsep \tabcellsep \tabcellsep (-)3515\\
\multicolumn{4}{l}{2016-2017(TILL DECEMBER}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{48031}\tabcellsep \tabcellsep \tabcellsep \tabcellsep (-)3377\\
\tabcellsep 2016)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{TOTAL}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{437671}\tabcellsep \tabcellsep \tabcellsep \tabcellsep 150438\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Source: RBI Bulletin February 2017\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Graph 1}\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \multicolumn{12}{l}{Trends of FDI and FII(US \$ Million)}\\
\tabcellsep 60000\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep 50000\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
FDI/FII\tabcellsep 20000 30000 40000\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep FDI(FOREIGN DIRECT\\
\tabcellsep 10000\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep INVESTMENT) FLOWS( US \$\\
\tabcellsep 0\tabcellsep 2006-2007\tabcellsep 2007-2008\tabcellsep 2008-2009\tabcellsep 2009-2010\tabcellsep 2010-2011\tabcellsep 2011-2012\tabcellsep 2012-2013\tabcellsep 2013-2014\tabcellsep 2014-2015\tabcellsep 2015-2016\tabcellsep ? 2016-2017(TILL\tabcellsep MILLION) FII(FOREIGN INSTITUTIONAL INVESTMENT FUND(US \$ MILLION)\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{YEARS}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.2023062730627306\textwidth}P{0.17721402214022142\textwidth}P{0.28385608856088557\textwidth}P{0.18662361623616236\textwidth}}
Years\tabcellsep FDI(Foreign Direct Investment) Flows (Us \$ Million)\tabcellsep FII (Foreign Institutional Investment Fund (Us \$ Million)\tabcellsep Sensex (Closing Values)\\
2006-2007\tabcellsep 22825\tabcellsep 3224\tabcellsep 13786.91\\
2007-2008\tabcellsep 34842\tabcellsep 20327\tabcellsep 20286.99\\
2008-2009\tabcellsep 41872\tabcellsep (-)15016\tabcellsep 9647.31\\
2009-2010\tabcellsep 37744\tabcellsep 29047\tabcellsep 17464.81\\
2010-2011\tabcellsep 34846\tabcellsep 29421\tabcellsep 20509.09\\
2011-2012\tabcellsep 46555\tabcellsep 16811\tabcellsep 15454.92\\
2012-2013\tabcellsep 34297\tabcellsep 27581\tabcellsep 19426.71\\
2013-2014\tabcellsep 36045\tabcellsep 5008\tabcellsep 21170.68\\
2014-2015\tabcellsep 45147\tabcellsep 40922\tabcellsep 27499.42\\
2015-2016\tabcellsep 55456\tabcellsep (-)3515\tabcellsep 26117.54\\
2016-2017(TILL DECEMBER 2016)\tabcellsep 48031\tabcellsep (-)3377\tabcellsep 26626.46\\
TOTAL\tabcellsep 437671\tabcellsep 150438\tabcellsep 217990.84\\
\tabcellsep \tabcellsep \multicolumn{2}{l}{Source: RBI Bulletin February 2017, BSE SENSEX}\\
\tabcellsep \tabcellsep Correlation\tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.38407407407407407\textwidth}P{0.17629629629629628\textwidth}P{0.24555555555555553\textwidth}P{0.04407407407407407\textwidth}}
\tabcellsep Mean\tabcellsep Std. Deviation\tabcellsep N\\
FDI\tabcellsep 39788.27\tabcellsep 8816.214\tabcellsep 11\\
FII\tabcellsep 13676.18\tabcellsep 17516.069\tabcellsep 11\\
SENSEX\tabcellsep 19817.35\tabcellsep 5586.724\tabcellsep 11\\
\multicolumn{2}{l}{Authors own compilation from various data sources}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2125\textwidth}P{0.2125\textwidth}P{0.425\textwidth}}
FDI\tabcellsep FII\tabcellsep SENSEX\end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.5780000000000001\textwidth}P{0.13114285714285714\textwidth}P{0.08742857142857142\textwidth}P{0.05342857142857143\textwidth}}
Model\tabcellsep Variables Entered\tabcellsep Variables Removed\tabcellsep Method\\
1\tabcellsep FII, FDI b\tabcellsep .\tabcellsep Enter\\
\multicolumn{2}{l}{a. Dependent Variable: SENSEX}\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. All requested variables entered.}\tabcellsep \\
\multicolumn{2}{l}{Authors own compilation from various data sources}\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.46646341463414637\textwidth}P{0.03628048780487805\textwidth}P{0.062195121951219505\textwidth}P{0.10884146341463415\textwidth}P{0.17621951219512194\textwidth}}
Model\tabcellsep R\tabcellsep R Square\tabcellsep Adjusted R Square\tabcellsep Std. Error of the Estimate\\
1\tabcellsep .637 a\tabcellsep .406\tabcellsep .257\tabcellsep 4815.368\\
\multicolumn{3}{l}{a. Predictors: (Constant), FII, FDI}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Authors own compilation from various data sources}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.3845238095238095\textwidth}P{0.09444444444444444\textwidth}P{0.17876984126984127\textwidth}P{0.020238095238095236\textwidth}P{0.11805555555555555\textwidth}P{0.020238095238095236\textwidth}P{0.03373015873015873\textwidth}}
\tabcellsep Model\tabcellsep Sum of Squares\tabcellsep df\tabcellsep Mean Square\tabcellsep F\tabcellsep Sig.\\
1\tabcellsep Regression\tabcellsep 126612724.066\tabcellsep 2\tabcellsep 63306362.033\tabcellsep 2.730\tabcellsep .125 b\\
\tabcellsep Residual\tabcellsep 185502176.254\tabcellsep 8\tabcellsep 23187772.032\tabcellsep \tabcellsep \\
\tabcellsep Total\tabcellsep 312114900.320\tabcellsep 10\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{a. Dependent Variable: SENSEX}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{b. Predictors: (Constant), FII, FDI}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Authors own compilation from various data sources}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.4492857142857143\textwidth}P{0.09714285714285714\textwidth}P{0.04371428571428571\textwidth}P{0.04614285714285714\textwidth}P{0.21371428571428572\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Year\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Volume XVII Issue III Version I\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep ( )\\
Model (Constant) FDI FII a. Dependent Variable: Sensex Unstandardized Coefficients B Std. Error 1 3474.215 7499.573 .366 .176 .131 .089 Authors own compilation from various data sources\tabcellsep Standardized Coefficients Beta .577 .409\tabcellsep t .463 2.075 1.471\tabcellsep Sig. .656 .072 .179\tabcellsep Global Journal of Management and Business Research\end{longtable} \par
  {\small\itshape [Note: 2017B© 20 17 Global Journals Inc. (US)]} 
\caption{\label{tab_7}Table 8 :}\end{figure}
 			\footnote{Descriptive Research is used to describe the characteristics of the population or phenomena being studied.\hyperref[b9]{7} Exploratory research helps to define the best research design and data collection methods and in selection of subjects.\hyperref[b0]{8} A hypothesis is a statement created by researchers when they speculate on outcome or experiment.\hyperref[b1]{9} Null Hypothesis (It shows there is no observed relationship between two measured phenomena.)\hyperref[b2]{10} Alternate Hypothesis(It states that the population parameter is different than the value of the population parameter in Null Hypothesis.} 			\footnote{A Statistical technique that are used to analyze the strength and direction of relationship between two quantitative variables.} 			\footnote{Trends and Patterns of FDI and FII in India-Implications for the Future © 2017 Global Journals Inc. (US) 1} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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