Research Article Open Access
The Factors Effecting Portfolio Investment in Pakistan
Muhammad Ramzan Mehar* and Ali Hasan
Lecturer, Head of Special Interest Group of Finance (SIG-Finance), Head of Entrepreneurs’ Society of Sialkot (ESOS), Registration Coordinator, University of Sialkot, Sialkot.
*Corresponding author: Muhammad Ramzan Mehar, Lecturer, Head of Special Interest Group of Finance (SIG-Finance), Head of Entrepreneurs’ Society of Sialkot (ESOS), Registration Coordinator, University of Sialkot, Sialkot, Pakistan, E-mail: @; @;
Received: June 04, 2018; Accepted: June 21, 2018; Published: June 29, 2018
Citation: Ramzan Mehar MD, Ali H (2018) The Factors Effecting Portfolio Investment in Pakistan. Int J Fam Busi Manag 2(1): 1-7.
Abstract
The research is about to inaugurate the factor that effect the portfolio investment in Pakistan. Portfolio investment is primary parts of private venture. Portfolio administration in this manner indicates to course of assets in such mix of various safeties in which the aggregate danger of portfolio is limited while supposing most extreme come back from it. Portfolio venture is useful to fill the hole amongst funds and interest in Pakistan. The time of 32 years from 1981-2012 cover for analysis. Trade openness, Market Capitalization, Foreign direct investment, Broad money M2, and weighted average return on deposite used as independent varibales and Net Portfolio Investment (NPI) taken as dependent variable. Augumanted Duky Fuller unit root test, Auto Regresive Distributive Lag (ARDL) and Granger Causilty test use for analysis purpose.Study find that weighted average return and foreign direct investment has negative effect on NPI while every single other variable are positively related with NPI.

Keywords: ADF; FDI; Net Portfolio Investment; Broad Money M2; Trade Openness;
Introduction
Background of the study
This study present new approach to found the factor that impacts the portfolio interest in Pakistan. Portfolio speculation is one of the fundamental parts of private venture. Portfolio venture is useful to fill the hole amongst sparing and interest in Pakistan.

Putting resources into corporate securities is gainful and in addition energizing. One ought not to overlook the component of dangers from putting resources into singular security. Hazard emerges when there is a plausibility of variety around expected come back from the security. As all securities pass on fluctuating characteristics of threats, hold more than one security at any given minute enables money related pro to spread his perils. The speculator trusts that regardless of the possibility that one security acquires a misfortune the rest will give some assurance from an outrageous misfortune. Hence, portfolios or blend of securities are supposed of as a device to spread hazard over numerous securities.

In past days, the traditional style managers of portfolio investments spread funds over securities of large number of companies only based on perception and intuition. They had no actual understanding of applying risk reduction. Meanwhile in 1950, a body of knowledge has been built up which quantifies the expected risk and also the riskiness of the portfolio. The theory of portfolio has been developed to deliver the organization a method to estimate the advantages and disadvantages of investment portfolio.

It is fundamental to realize what portfolio is if you want to have a superior comprehension of portfolio administration. Portfolio implies a mix of money related resources and physical resources. The money related resources are offers, debentures and different securities while physical resources incorporate gold, silver, genuine bequests, uncommon accumulations, and so on. The embodiment of portfolio is that advantages are held for venture devotions and not for utilization purposes Chaudhry I, et al. [8].

Portfolio speculations are latent ventures as they don’t include control of the issuing association or dynamic organization. Or, on the other hand possibly, the explanation behind the wander is solely money related benefit, rather than outside direct theory (FDI), which empowers an examiner to rehearse a particular level of regulatory control over an association. For worldwide exchanges, value ventures is what where the owner holds under 10% of an organization’s offers are named as portfolio speculations. These exchanges are also referred to as “portfolio streams” and are consider as a recorded in the money related record of an installments for nation’s adjustment.

This investigation shows the factors that empower or demoralize portfolio venture. To investigate the long run and short run relationship between net portfolio speculation, , Market capitalization, Deposit rate, Broad cash (M2), remote direct venture and Trade receptiveness. These factors are solid for determining the conduct of considering economy in an all-around mannered way (Sukanya and Thimmarayappa R, [9], Kassim H, [12]).
Research Problem
The problem which is concentrated by researcher in this particular study to know about the factor effecting portfolio investment in Pakistan. Portfolio venture is a bundle of budgetary speculation instruments. These budgetary instruments are anything but difficult to exchange and are less unending. These tools are not inevitably a portrayal of long-run intrigue. This sort of venture gives the financial specialists profit installments, conceivable voting rights and responsibility for part of the organization. This sort of venture speaks to generally here and now enthusiasm as it is viewed as more unstable and dubious. This money related resources, Portfolio Speculation, are profoundly liquid in countryside and simple to change over into cash in whenever. Speculators would sale be able to their budgetary instruments from portfolios whenever, portfolio venture also effected by foreign direct investments, trade openness, market capitalization, growth rate of broad money (M2) and weighted average on deposit. Unfortunately these listed variables are not only factor that effect portfolio investment in Pakistan. Despite of these variables return on equity, growth rate, macroeconomic factor, foreign portfolio investment lead to strong capital assembly of firm values and increase incentives. Portfolio investment will lead to improve the economy of the country by providing employment opportunities, through increasing investment in market. So this is need emerges to analyze the factor affecting portfolio investment in Pakistan consequently we proposed this study.
Research Objectives
This research study generally focuses to analyses the factor effecting portfolio investment in Pakistan. So our research study specific objectives are;

• To compare the impact of market capitalization on portfolio investment.

• To calculate the impact of trade openness on portfolio investment.

• To find out the effect foreign direct investment on portfolio investment.

• To explain the impact weighted average return on deposit on portfolio investment

• To analyses the effect of growth rate of broad money (M2) on portfolio investment.

• To determine the factor effecting portfolio investment in Pakistan.
Significance of study
The study focuses on the factor effecting portfolio investment in Pakistan and its impact on investment companies in Pakistan. Government rules and portfolio speculation are prevalent, significant and frequently positive effect on trade atmosphere and financial growth of any industrial state, likely help in structure of taxes, technology development, and help in physical infrastructure and human capital etc. So, this study equally important to provide information for the individual investor, institutional investors, investment bankers, mutual fund companies and government of Pakistan. The investors, through portfolio administration, effort to exploit their expected return reliable with separately acceptable group of risk.
Review of Literature
Diverse examinations have been accessible on the workings of portfolio wander. Huge section of these examinations has been coordinated all around. Guardianship in observe the noteworthiness of Portfolio Speculation, examiner show the analysis of critical examinations.
Market Capitilzation, Trade Openness, FDI and Portfolio Investement
Awan PD, et al. [6] and Atif, et al. [5] said in their study showed that factor effecting foreign direct investment, import and export on the Gross Domestic Product (GDP) growth in Pakistan; researchers include external debt, goods and services export import, gross national income, gross capital formation military expenditures as independent variables, FDI and GDP as dependent variables in these studies. The multiple ordinary least square method of linear regressions model is applied to find out the association between explanatory variables and dependent variables. The studies concluded as exports, GNI and gross capital formation have significant and positive effect on Pakistan FDI inflows. On the other side, external debt also significantly effects on dependent variable. As for as GDP calculation, used all goods and services produced during a year.

There are many other similar studies were conducted by various researchers with different topics, in all these researches aimed to calculate the factor effecting portfolio investment in different countries. Thimmarayappa, [9]; Kassim, [14] and Nguyen, et al. [18] said in their study that the impact of behavioral biases on foreign portfolio investment. oil prices, stock market and economic growth of Malaysia took as explanatory variables and behavioral finance and portfolio investment as dependent variable. A purely descriptive research named as, the study analyses the relationship between FPI and real Gross Domestic Product (GDP) by Toda and Yamamoto’s (1995). They are using the widely adopted ADF Unit root tests, Descriptive statistics of return series and Granger Causality tests for analysis purpose. The results propose that economic performance is the major appealing factor in inviting FPI into the country. So, conclusion of the studies suggested that for confirming the Malaysian economy remains on a strong and sustainable growth path if you create and maintain confidence in your investors. The overall finding said that the general and behavioral factors affecting investment decisions of investors and it should help to design an appropriate portfolio of investments.

The interesting studies were conducted by Ramzan, et al. [19] and Mohebbi, et al. [17] that shown the impact of trade openness and macroeconomic variables on GDP growth and economic growth of Pakistan and Iran. Trade openness, exchange rate, employment rate, inflation rate and FDItaken as explanatoryvaribales and Gross Domestic Product (GDP) growth as explained variable. Augumanted Duky Fuller (ADF) unit root test,Multiple regression, Ordinary Least Square Method (OLS) and Co-integration technique teachniques for analysis and for this, they have used an empirical growth model by collecting data of said variables covering period from 1971-2008. Estimation results indicate that the trade openness, exchange rate,employment rate and Foreign Direct Investment (FDI) has significant and positive reltationship with economic growth and inflation rate has significantly negative effect on economic growth of pakistan and Iran.

Bashir, et al. [7], Hussain, et al. [13], Zaighum, et al. [25] and Ali, et al. [4] shown the study impact of macroeconomic factors on financial and non-financial development of firm stock returns and economic growth in Pakistan; researchers took consumer price index, demand deposit, foreign direct investment, domestic saving as percentage of GDP, stock return as independent variables and dependent variable as real GDP. The annual time series data covering the time period from 1972 to 2011 is used for the analysis and it was important to test the order of integration of the time series included in the model. Augmented Dickey-Fuller (ADF) test has been employed to test the stationary property of the time series. In the present analysis, for the purpose of the estimation of ADF test statistic regression analysis and other test including descriptive statistics and Granger causality test have been used. Empirical result shows that Integration techniques and Granger causality test based on the block exogeneity (Wald test) has been applied for the analysis. The integration test confirmed the long run association among the inflation, credit to private sector, deposits, FDI, domestic savings and economic growth and the overall results of this study have shown that there are important implications of results of this study for the equity investors and policy makers.
Research Hypothesis
H1: Market capitalization does have positive and significant effects on portfolio investment.

H2: Trade openness does have positive and significant effects on portfolio investment.

H3: Foreign direct investment does have positive and significant effects on portfolio investment.
Weighted Average Return, Growth Rate of Broad Money (M2) and Portfolio Investement
Khalida, et al. [15], Shahid, et al. [22], Alexeev, et al. [3] and Lagoarde-Segot, et al. [16] shown that there is a long run and casual relationship between macroeconomic factors and in stock prices of Pakistan. T-bill, Exchange rate, Inflation, stock price and PPI took as independent variables and equity market return, gold price and silver price as dependent variables. The study for the purpose of analysis used Augmented Dickey Fuller test to check stationary of data, Johansen’s Co-integration test for finding long-term relation and Ganger’s causality tests has been used to calculate the causal relationship between stock prices and selected macro-economic variables. Co-integration test is used for the purpose to finding the long run co-movement between different series. The data was not stationary at ADF & PP level but at first difference data become stationary. The result of this test shown that there is no co-movement exists between variables and KSE return. Correlation results depict that there is insignificant positive correlation between T-Bill and inflation and T-bill & X-Rate. The direction of flow of information investigates by using Granger causality test and its result shows that X-rated granger causes the RM. The conclusion said that the stock prices are co-integrated with macro-economic variables in long term. Moreover, macroeconomic variables like, PPI, Inflation, Gold price and Exports have long term causal relationship with stock prices in Pakistan.

Similar studies were conducted by various researchers with different topics, in all these studies aimed to calculate the comparative analysis of the socio economic determinants of foreign direct investment versus portfolio investment by Rehman(2016), Ahmad, et al. [1], Saeed, et al. [21] and Saeed, et al. [20] taken foreign direct investment , Portfolio Investment as independent variables and Global Games Financial Transparency and socio economic as dependent variables to conduct these proposed research; the researcher collected data for all the said variables except political rights and corruption from official website of World Development Indicator (WDI) for the period 1984-2015. The data for other two variables (corruption and political) are obtained from International Country Risk Guide (ICRG), and Freedom House Index respectively. The research methodology used as ADF Unit Root Test, Johansen Co-integration Test, Estimation of Vector Error Correction Model (VECM)and results of these tests shown that the study suggests that in order to attract FDI, foreign exchange control needs to be relaxed and foreign investors may be allowed to participate in local projects on the bases of 100% equity. Likewise, it express that the role of social factors in attracting short run and long run FDI is relatively important in Pakistan.
Research Hypothesis
H1: Weighted average return on deposited does have positive and significant effects on portfolio investment.

H2: Growth rate of broad money (M2) does have positive and significant effects on portfolio investment.
Research Design and Methodology
In this research study, research design is quantitative nature that is particularized following head. The primary theme is to detecting the econometric techniques and methodology.
Time Period, Nature and source of Data
The study considers yearly data for all variables covering time period from 1981 to 2014. In the event that the correct procedures are connected for investigation then we get precise outcomes from examination. So for this purpose secondary data extracting from official website of from World Development Indicators and State Bank of Pakistan (Handbook of Statistics on Pakistan’s Economy) and for the period 1981 to 2014.
Unit of Analysis
A standout amongst the most vital thoughts in an examination venture is the unit of investigation. The unit of investigation is the real substance that you are breaking down in your research. The accessible works gives a total clarification of variables disturbing net portfolio investment. In order to analyze the determinants of portfolio investment in Pakistan we include five related variables, one of which is dependent variable such as Portfolio Investment (PI) and trade openness, market capitalization, broad money(M2), foreign direct investment and weighted average return on deposit used as independent variables to measure net portfolio investment in Pakistan. The net portfolio investment, WAROD, and trade openness used as a percentage further for market capitalization, FDI and broad money M2 data taken in million dollars.
Methodology
This research is utilized to recognize the connection between different factors and net portfolio investment in Pakistan. First of all we used Augmented Dickey Fuller Test (ADFT) by Fuller (1979) and Greene, [11] for checking stationary of data. The next step is to check the Granger Causality test by Granger, [10] to reslove the causality with refrences to factors in the inner connection. Therefor this procedure will be utilized to identify the genuine causal connection between factors. If all variables are not stationary at same levet then Auto Regressive Detributive Lag (ARDL) used to checkconnecteion between variables. So this investigation utilize ARDL model of Analysis on the grounds that variables are not staionary at same levels.
Analysis and Interpretations
Unit Root Test
Unit root test is used to check the stationary of data. It measures the stationary or non-stationary of data of time series at level or at trend. The existence of unit root in autoregressive model is measured by applying Augmented Dickey-Fuller (ADF) test. This test is generally used in unit root test to fit an autoregressive (AR) model, it examines null hypothesis of Autoregressive Integrated Moving average (ARIM) process against the stationary of data (Cheung & Lai, 1995).

Calculations are carried out with the help of E-Views 9.5(Quantitative software). Table-1 displays the aftereffects of ADF test directed on net portfolio speculation. Unit Root test permit affirming whether a course of action is stationary or not. If the value of probability is less than 0.05 then we reject our null hypothesis that the series has unit root problem. Table-1 shows the result of unit root test that all the variables has unit root problems at level except trade openness which means that most of variables are not stationary at level. As overall result of unit root shows that some variables are stationary at 1st difference and some are stationary at 2ns difference. So literature suggests that if variables are not stationary at same level then we use ARDL for checking long-term relationship between variables.
Table 1: Unit Root Test

Unit Root Tests

Variables

T-Statistic

Prob.

Critical Value

1%

5%

10%

Broad Money M2

At Level

8.5373

1.0000

3.6463

-2.954

-2.6158

1st Diff.

0.5069

0.9841

-3.6701

-2.9639

-2.621

-7.1897

0.0000

-3.6701

-2.9639

-2.621

Market capitalization

At Level

3.0655

1.0000

-3.7114

-2.98103

-2.6299

1st Diff.

-0.9009

1.0000

-3.7378

-2.99187

-2.6355

2nd Diff.

-1.7594

0.3903

-3.7378

-2.9918

-2.635

Trade Openness

At Level

-5.4351

0.0000

-0.6701

-2.9639

-2.6207

1st Diff.

-10.409

0.0000

-3.6793

-2.9677

-2.6229

WAROD

At Level

-1.6228

0.46

-3.6463

-2.95402

-2.6158

1st Diff.

-6.56

0.0000

-3.6537

-2.95711

-2.6174

Portfolio

At Level

-2.6011

0.1035

-3.6616

-2.96041

-2.619

1st Diff.

-9.263

0.0000

-3.653

-2.9571

-2.617

FDI

At Level

-2.8189

0.0668

-3.6537

-2.9571

-2.6174

1st Diff.

-4.1074

0.0032

-3.6537

-2.9571

-2.6174

Auto Regressive Distributive Lag (ARDL)
Autoregressive Distributed Lag (ARDL) Estimates is a test to calculate long-term association between variables if your variables are not stationary at same level. So researcher propose an ARDL displaying for univariate Co-integration test, where the Net portfolio speculation is thought to be the dependent variable and the best slack circulation of the independent variables, trade openness, broad money M2, market capitalization, FDI and weighted average return on deposit was appeared.

In these outcomes, fist column shows the name of variables and its coefficient values shows in second column, next column shows standard error, T-statistic and probability value respectively. Researcher can see that Dependent variable. The D values with variables’ name express the difference I, II, and III respectively.

The consequence of table 2 demonstrates that estimation of R square and Adjusted R square’s value being 0.699870 and 0.533130 respectively demonstrates that the greater part of variation in NPI is clarified by five independent variable in model. As per we specific examination the estimation of R squares is 0.69 which is equivalent to 69% and this variance demonstrate that the variation in NPI almost explain by included independent variables and remaining rate which is 31% demonstrate the other independent variables which is not include this study. With respect to estimation of F. statistics probability appeared as table if the estimation of probability value f-Statistics is under 0.05 then the model is good fit. Our Prob. F. statistics value is 0.004044 this demonstrates significant of model.
Table 2: Autoregressive Distributed Lag (ARDL) Estimates

Variable

Coefficient

Std. Error

T-Statistic

Prob.

D(Portfolio(-1))

-0.53817

0.170958

-3.14795

0.0056

D(FDI(-1))

234757.5

245093.8

0.957827

0.3508

D(M2(-1))

-422.727

595.6979

-0.70963

0.487

D(M2(-2))

-748.688

639.801

-1.17019

0.2572

D(Market Cap( -1))

-182.301

421.1744

-0.43284

0.6703

D(Market Cap( -2))

1007.507

895.4891

1.125091

0.2753

D(Market Cap( -3))

1738.116

440.3424

3.947192

0.0009

D(AWROD(-1))

2.15E+10

1.17E+08

1.83527

0.083

D(TO(-1))

-2.2E+07

22540023

-0.983

0.3386

D(TO(-2))

-4.3E+07

24493623

-1.77114

0.0935

C

-5.2E+07

1.94E+08

-0.26568

0.7935

R-squared

0.69987

Durbin-Weston stat

1.774605

F-statistics

4.197391

Prob. (F-stat)

0.004044

Portfolio Investment = C(1)*D(Portfolio(-1))+ C(2)*D(FDI(-1))+ C(3)*D(M2(-1)) + C(4)*D(M2(-2))+ C(5)* D(Market Cap(-1)) + C(6)*D(Market Cap(-2))+ C(7)* + D(MarketCap(-3))C(8)* D(AWROD(-1)) + C(9)* D(TO(-1)) + C(10)* D(TO(-2))+ C(11)

Portfolio Investment = -0.538169*D(Portfolio(-1))+ 234757.5*D(FDI(-1)) 422.7266*D(M2(-1)) -748.6880*D(M2(-2) -182.3009*D(Market Cap(-1))+ 1007.507*D(Market Cap(-2)) -1738.116*D(Market Cap(-3))+ 215E+ 08*D(AWROD(-1)) -22156801*D(TO(-1)) -43381715* D(TO(-2)) -51607973
ARDL Error Correction Regression
ARDL error Correction Representation of above long run relationship is accounted for in table 3 which catches the short-run flow of relationship among subordinate factors and free factors. The blunder redress demonstrate in light of ARDL approach sets up that progressions in Net portfolio venture and change autonomous factors as exchange receptiveness, FDI, Broad cash M2,WAROD and market capitalization have critical.

As indicated in above listed table the coefficient value of Broad cash M2, Market Capitalization and Trade transparency are - 422.7266 , - 182.3009, and - 22156 separately. It merits specifying that these flexibilities are much lower than long run flexibilities. It is additionally watched that portfolio venture isn’t critical in long rum yet it is measurably noteworthy in here and now. ECM (- 1) is one period slack estimation of error terms that are gotten from the long-run relationship of significant worth - 1.538169. The coefficient of ECM(- 1) demonstrates the amount of the disequilibrium in the short-run will be settled (wiped out) in the long run.

Not surprisingly, the mistake redress variable ECM (- 1) has been discovered negative and furthermore factually critical. The aftereffect of table 3 demonstrates that estimation of R square esteem being 0.876772 individually demonstrates that the majority of variation in NPI is explained by five independent variable in display. According to Researcher particular study the estimation of R squares is 0.87 which is equivalent to 87% and this fluctuation demonstrate the dependent variable and remaining rate which is 13% demonstrate the other independent variables. In above listed table investigation the estimation of Durbin – Watson is 1.7746 that demonstrates there is no any auto connection between the factors.
Table 3: ARDL Error Correction Regression

Variable

Coefficient

Std. Error

t-Statistic

Prob.

D(M2(-1),2)

-422.727

382.1478

-1.10619

0.2832

D (Market Cap...

-182.301

205.1496

-0.88862

0.3859

D (Market Cap

-1738.12

231.2719

-7.51547

0.0000

D (Trade Open..

-22156.8

5996832

0.000000

0.0000

ECM(-1)*

-1.53817

0.129359

-11.8907

0.0000

R-square

0.876772

Durbin-Westonstat

1.774605

Result of Granger Causality Test
Researchers test any concentrate between two factors, to check the causal relation between variables Granger Causality test is applied. (Granger, 1969) Says when two factors are cointegrated, then causal connection happen between variables in one direction or both. Granger Causality between factors can be clarified as follows; when one variable is independent [x] and other variable is dependent variable [y]. Changes in independent factors caused change in dependent variable it is called unidirectional relationship between variables. Bidirectional relationship happens at the point when independent variable [x] cause dependent [y] variable and dependent [y] cause independent variable [x]. (Table 4)
Table 4: Pairwise Granger Causality Test

Null Hypothesis

F-Statistic

Prob.

Decision

D(FDI) does not Granger Cause D(Portfolio)
D(Portfolio) does not Granger Cause D(FDI)

0.74583
5.53787

0.4855
0.0109

Accept
Reject

D(M2) does not Granger Cause D(Portfolio)
D(Portfolio) does not Granger Cause D(M2)

1.80584
0.76919

0.1869
0.4749

Accept
Accept

D(Market Capitalization) does not Granger Caused(Portfolio)
D(Portfolio) does not Granger Cause D(Market Capitalization)

0.61338

0.5501

Accept

2.85990

0.0778

Accept

D(Trade Openness) does not Granger Cause D(Portfolio)
D(Portfolio) does not Granger Cause D(Trade Openness)

0.80630
0.04621

0.4605
0.9549

Accept
Accept

D(WAROD) does not Granger Cause D(Portfolio)
D(Portfolio) does not Granger Cause D(WAROD)

0.01177
0.42053

0.9883
0.6616

Accept
Accept

D(M2) does not Granger Cause D(FDI)
D(FDI) does not Granger Cause D(M2)

0.64934
0.15688

0.5307
0.8556

Accept
Accept

D(Market capitalization) does not Granger Cause D(FDI)
D(FDI) does not Granger Cause(Market capitalization)

0.34649
0.51562

0.7104
0.6031

Accept
Accept

D(Trade Openness) does not Granger Cause D(FDI)
D(FDI) does not Granger Cause D(Trade Openness)

0.37362
7.17228

0.6923
0.0038

Accept
Reject

D(WAROD) does not Granger Cause D(FDI)
D(FDI) does not Granger Cause D(WAROD)

0.01792
2.61006

0.9823
0.0927

Accept
Accept

D(Market Capitalization) does not Granger Cause D(M2)
D(M2) does not Granger Caused(Market Capitalization)

0.54413
5.44455

0.5868
0.0106

Accept
Reject

D(Trade openness) does not Granger CauseD(M2)
D(M2) does not Granger Cause D(Trade Openness)

0.25568
1.7602

0.7766
0.1944

Accept
Accept

D(WAROD) does not Granger Cause D(M2)
D(M2) does not Granger Cause D(WAROD)

0.19651
0.70177

0.8228
0.5049

Accept
Accept

D(Trade Openness) does not Granger Cause D(Market Cap.)
D(Market Cap.) does not Granger Cause D(Trade Openness)

0.53794
0.94157

0.5911
0.4045

Accept
Accept

D(WAROD) does not Granger Cause D(Market Capitalization)
D(Market Capitalization) does not Granger Cause D(WAROD)

0.18241
0.44806

0.8343
0.6437

Accept
Accept

D(WAROD) does not Granger Cause D(Trade Openness)
D(Trade Openness) does not Granger Cause D(WAROD)

1.18855
0.13491

0.3227
0.8745

Accept
Accept

Granger causality test is used determining whether one time series is suitable in estimating for another. Granger causality test shows that X granger causes the y. Similarly FDI granger causes the NPI. It shows that flow of information or relationship exists between variables.

Granger causality test is used to determine short run causal relationship between variables. If the probability value of null hypothesis is less than 0.05 then it indicates to reject the null hypothesis of casual relationship between variables. In our study there are 30 null hypothesis in which only three rejected due to causal relationship in granger casualty of D(portfolio) does have granger cause of foreign direct investment with value 0.0109 then null hypothesis rejected; further foreign direct investment does have granger cause to trade openness with value 0.0038 then null hypothesis rejected and broad money M2 does have granger casualty to Market capitalization with value 0.0106 then null hypothesis rejected and further more in conduct study conclude that 27 null hypothesis are Accepted at the significant level of 0.05.
Conclusions and Suggestions
This investigation is an attempt to check the relationship among dependent and independent variables. Study investigates the factor that effects the Portfolio Investment in Pakistan. Net Portfolio Investment has been taken as dependent variable while Weighted Average Rate of Return on Deposit, Growth rate of Broad Money, Trade Openness, Foreign Direct Investment and Market Capitalization has been taken independent variable. Independent variables have been taken by their relative importance in literature review. ADF unit root test, ARDL and granger casualty test were used to test relations. As Researcher clear that in unit Root test firstly depict that Broad Money M2 in which is output of the study that second difference the value is less than the decide probability which show that the data is stationary at value of 0.0000 in ADFT. So in our case some variables are stationary at level, some are at 1st and 2nd difference. That’s why study use ARDL test for long-run analysis of variables.

In Granger Casualty there are 30 hypothesis in which 3 are rejected and 27 are accepted under the significant level 0.05.

Aftereffects of the examination clarify that market capitalization, broad money M2 and trade openness have negative effect on net portfolio investment yet these are discovered insignificant factors in light of the fact that in Pakistan. There is absence of straightforward and serene monetary and money related atmosphere.

On the other hand, weighted average rate of return on deposit and foreign direct investment (GDP %) have positive influence on net portfolio investment. On the premise of results, researcher proposes that additional security ought to be given to foreign investors by the government of Pakistan. Psychological coercion should to be defeated to prosper advertise capitalization and additionally to enhance budgetary organizations in Pakistan. Administration of Pakistan ought to give inviting environment to the remote speculators. Financing cost on store in Pakistan should to for attracting NPI.
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