Keywords: ADF; FDI; Net Portfolio Investment; Broad Money M2; Trade Openness;
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]).
• 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.
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.
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.
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.
H2: Growth rate of broad money (M2) does have positive and significant effects on portfolio investment.
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.
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 |
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.
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 = -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
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.
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 |
Null Hypothesis |
F-Statistic |
Prob. |
Decision |
D(FDI) does not Granger Cause D(Portfolio) |
0.74583 |
0.4855 |
Accept |
D(M2) does not Granger Cause D(Portfolio) |
1.80584 |
0.1869 |
Accept |
D(Market Capitalization) does not Granger Caused(Portfolio) |
0.61338 |
0.5501 |
Accept |
2.85990 |
0.0778 |
Accept |
|
D(Trade Openness) does not Granger Cause D(Portfolio) |
0.80630 |
0.4605 |
Accept |
D(WAROD) does not Granger Cause D(Portfolio) |
0.01177 |
0.9883 |
Accept |
D(M2) does not Granger Cause D(FDI) |
0.64934 |
0.5307 |
Accept |
D(Market capitalization) does not Granger Cause D(FDI) |
0.34649 |
0.7104 |
Accept |
D(Trade Openness) does not Granger Cause D(FDI) |
0.37362 |
0.6923 |
Accept |
D(WAROD) does not Granger Cause D(FDI) |
0.01792 |
0.9823 |
Accept |
D(Market Capitalization) does not Granger Cause D(M2) |
0.54413 |
0.5868 |
Accept |
D(Trade openness) does not Granger CauseD(M2) |
0.25568 |
0.7766 |
Accept |
D(WAROD) does not Granger Cause D(M2) |
0.19651 |
0.8228 |
Accept |
D(Trade Openness) does not Granger Cause D(Market Cap.) |
0.53794 |
0.5911 |
Accept |
D(WAROD) does not Granger Cause D(Market Capitalization) |
0.18241 |
0.8343 |
Accept |
D(WAROD) does not Granger Cause D(Trade Openness) |
1.18855 |
0.3227 |
Accept |
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.
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.
- Ahmad YS, Cova P, Harrison R. Foreign Direct Investment versus Portfolio Investment: A Global Games Approach. Foreign Direct Investment Survey. 2004:1-24.
- Ahmed HZ. Trade Openness, Industrial value and Economic Growth in Pakistan. 2010.
- Alexeev V, Tapon F. Equity portfolio diversification: how many stocks are enough? Evidence from five developed markets. Tasmanian School of Business and Economics. 2013.
- Ali S, Waqas H, Asghar M, Mustafa M, Kalroo R. Analysis of Financial Development and Economic Growth in Pakistan. Journal of Basic and Applied Scientific Research. 2014;4(5):122-130.
- Atif, Aziz-ur-Rehman M. Impacts of Imports, Exports and Foreign Direct Investment on the Gross Domestic Product (GDP) Growth. Impacts of imports, exports. 2013:1-21.
- Awan AG, Ahmad W, Shahid P, Hassan J. Factors Affecting Foreign Direct Investment In Pakistan. International Journal of Business and Management Review. 2014;2(4):21-35.
- Bashir F. Determinant of Foreign Direct Investment in Pakistan. Journal of Economics and Sustainable Development. 2015;6(13):74-84.
- Chaudhry IS, Farooq F, Mushtaq A. Factors affecting Portfolio Investment In Pakistan: Evidence From Time Series Analysis. Pakistan Economic and Social Review. 2014;52(2):141-158.
- Sukanya R, Thimmarayappa R. Impact of Behavioural biases in Portfolio Investment Decision Making Process. International Journal of Commerce, Business and Management. 2015;4(4):2319-2828.
- Granger CWJ. Investigating Causal Relations by Econometric Models and Cross-spectral Methods. The Journal of Econometrics Society. 1969;37(3):424-438.
- Greene H. The Augmented Dickey-Fuller Test. Econometric Analysis. 1997.
- Kassim SH, Duasa J. Foreign Portfolio Investment and Economic Growth in Malaysia. The Pakistan Development Review. 2009;48(2):109-123.
- Hussain s, Hussain F. Determinants of Foreign Direct Investment in Pakistan: Is China crowding out FDI Inflows in Pakistan. Pakistan Development Review. 2017;56(4):1-27.
- Kassim S, Duasa J. Foreign Portfolio Investment and Economic Growth in Malaysia. The Pakistan Development Review. 2009;48(2):109-123.
- Khalid M, Altaf M, Majid M, Bagram M, hussain H. Long-Run Relationship of Macroeconomic Variables and Stock Returns: Evidence From Karachi Stock Exchange (Kse) 100 Index. The Journal of Commerce. 2014;4(3):2220-6043.
- Lagoarde-Segot T, Lucey BM. International portfolio diversification: Is there a role for the Middle East and North Africa. Journal of Multinational Financial Management. 2007:401-416.
- Mohebbi N, Ahmadi R. Trade Openness and Economic Growth in Iran. Journal of Basic and Applied Scientific Research. 2012;2(1):885-890.
- Arouri MEH, Nguyen DK. Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over the Last Decade. Energy Policy. 2010;38(8):4528-4539.
- Ramzan M, Asif M, Mustafa AM. Impact of Trade Openness and Macroeconomics Variables On GDP Growth Of Pakistan. A Research Journal of Commerce, Economics and Social Sciences. 2013:37-47.
- Saeed S. Macroeconomic Factors and Sectoral Indices: A Study of Karachi Stock Exchange (Pakistan). European Journal of Business and Management. 2012;4(17):132-152.
- Saeed S, Akhter N. Impact of Macroeconomic Factors on Banking Index in Pakistan. Interdisciplinary Journal of Contemporary Research in Business. 2012;4(6):1200-1218.
- Shahid MA, Kamran FF. Causal Relationship between Macroeconomic Factors and Stock Prices in Pakistan. International Journal of Management and Commerce Innovations. 2016;3(2):172-178.
- Sukanya R, Thimmarayappa R. Impact of Behavioural biases in Portfolio Investment Decision Making Process. International Journal of Commerce, Business and Management. 2015;4(4):2319-2828.
- Yamin S, Ahmad PC. Foreign Direct Investment versus Portfolio Investment. 2004:1-27.
- Zaighum Isma. Impact of Macroeconomic Factors on Non-financial Firms Stock Returns: Evidence from Sectorial Study of KSE-100 Index. Journal of Management Sciences. 2014;1(1):35-48.