Chapter 1

INTRODUCTION

1.1 Background of the study

Stock market has a very great role in the economies of countries. It is a place where

the shares and stock of companies are traded with agreed listed prices. Companies

will have a tough time and so many difficulties if there were no stock markets in the

countries. To bring together investors and firms and to make transactions among them

easier Stock exchanges act as a role of intermediaries.

To raise money the best place for companies are the stock markets as they provide the

services to these companies to meet and take transactions. It became so easily feasible

for the investor to sell or buy their securities due to liquidity in stock markets.

Stock markets also are the indicators of economy, so countries having high

performance in stock markets are also considered as good position economy

countries. In Simple words the strong and good position of economy depends upon

the performance of stock markets. For instance if we take share price, If the share

prices increases it going to affect business, households, companies etc.

Before the times when stock market came to existence there were no rules and

regulations and no proper platform for the transitions between parties to take place

easily. Thus the place where transaction between buyer and seller would take place

that place was known as stock market.

1

Karachi Stock Exchange came to existence and was started to contribute to the

Pakistani economy in 1947 right soon after the Pakistan came to existence. It is one of

the major and well-functioning stock market in the world. KSE was at first started in

the beginning with stock listed of only five companies and their paid-up capital at that

time was about Rs. 37 million. Currently Karachi stock exchange is contributing to

the economy with having about 200 members and brokers to have fair dealing

between the parties. And the companies listed currently in this exchange are 651 (Six

hundred and fifty one).

For the first time in 2002 the KSE (Karachi stock exchange) was awarded as “Best

Performing Stock Market of the World” in the news as mentioned by “Business

week”. Foreign investors contributed a lot during the years 2006 and 2007.US$523

Million according to the STB (State bank of Pakistan) were invested in Pakistan

capital markets by the foreign participants.

1.2 Karachi Stock Exchange during the years 2008 and 2009:

During these years 2008 and 2009 Karachi stock exchange faced some great changes

in the market. For the first time KSE went to its highest peak during April can take

some steps further in its financial position for going up than 15000 to 15,737.32.

That’s why it was awarded as “the best performance” market for going up to 7 %.

During month of May the Karachi stock exchange faced a high Inflation due to which

interest rates were raised up by the State Bank of Pakistan. And that leaded Karachi

stock exchange to decrease in its position. During July it also faced some bad

situations due to Government involvement and engagement with Taliban Issues.

When Musharaf resigned during August the Karachi Stock Exchange rose up about

4%.

2

These are the variation in Karachi stock Exchange that attracted researchers to

investigate the main factors and reasons for these variations in stock prices.

In Pakistan after the Karachi Stock exchange others are “Lahore stock exchange,

Islamabad stock exchange”. In Pakistan the KSE-100 index is used as a standard and

Benchmark index having top hundred companies listed for researcher’s studies. Other

than KSE-100, there are also”KSE-30, KMI-30 and KSE all share indices”.

Current market capitalization and listed capital of Karachi Stock Exchange in US

dollars is 26.48 billion and 9.65 billion respectively.

KSE stock exchange faces strong changes since 2000, and scores a very good position

in the world market and many times was awarded as a world most successful stock

exchange. These high changes in KSE gained the attention of companies and

researchers to do research about what are the factors that can impact or having any

relationship with Stock Prices and returns. So many studies were conducted to

analyze to know the relationship between different variables (Especially macro-

economic variables) and Stock exchange. But different studies analyzed and

concluded different results. Nishat and Shaheen (2004) founded and made conclusion

that there is a relationship between micro-economic variables and Stock prices and

that the economic variables really do have an impact on Stock prices, but the study

(Ali, et al. 2010) founded different results and concluded no relationship between

macro-economic variable and stock prices, and that economic forces have no impact

on stock prices. The reason for this difference in results was presented that during the

period of 2005-2008 the stock exchange showed a highly good position without any

improvement in macro-economic variables that make the results of second study

different and opposite than the first study by Dr. Nishat.

3

This study will analyze the “relationship between macro-economic variables and

stock prices” for the period of 2005-2010.

1.2 Objectives of the Study

The objective of this study is to “determine the relationship and to find out the impact

between macro-economic variables (Consumer price index, Quantum index,

Exchange rate) and stock prices” in Pakistan market at Karachi stock exchange, and to

“investigate the determinants of Stock prices variations”. Pakistani market’s Stock

exchanges are not as mature as in e.g. America, United Kingdom and Japan etc. that’s

why there may be differences in results and variables or factors that have an impact or

having any relationship with Stock prices.

1.3 Purpose of the Study

The purpose of conducting this research is to “determine the relationship between

macro-economic variables such as Consumer price Index (Inflation), Quantum Index

of manufacturing (Industrial production), Exchange rate and Stock prices” and the

impact of Independent variables on dependent variable, and to find out the factors that

can impact stock prices of KSE-100 index in Pakistan market.

1.4 Scope of the Study

For most researches related to Stock markets in Pakistan KSE-100 index that contains

top hundred companies of Pakistan is used as benchmark for Pakistani market and is

used mostly for their studies. The scope of this study is also limited to the “KSE

(Karachi Stock Exchange)” and the companies that can be influenced with such

changes of in macro-economic activities and their influence on Stock market.

4

Chapter-2

LITERATURE REVIEW

The purpose of this study is to “analyze and find out the relationship and impact of

macro-economic variables (Consumer price index, Quantum index, Exchange rate) on

Stock prices” for the period 2005- 2010. During this period there occur great changes

in these three indicators of macro-economic variables. The exchange rate went up to

85 (compared to dollar) in 2010 from 59 in 2005, which is a very big change in

Pakistan exchange rate. Similarly the Consumer price index goes very high during

2010, and some big changes were seen in quantum index (industrial production)

during the period. The purpose of this study is to analyze and investigate “whether

these macro-economic variables (Consumer price index, Quantum index of

manufacturing and Exchange rate) have relationship or having impact on stock

prices”.

Muhammad Akbar et al., (2011). conducted a study to find out the “relationship

between these four variables in Pakistan for period 1999- 2008”. Several studies were

conducted in recent years to analyze the relation between different “macro-economic

variables and stock prices”, They used “Granger causality, Co-integration, and error

correction tests” for the analysis of their data. (Akbar, Ali and Khan 2012)

Imran Ali et al. (2009) and Ali, et al. (2010). The study finds out that the

manufacturing production index has relationship with stock prices and there exists co-

integration between them, the inflation also has relationship with stock prices and that

is the negative relation exists between the two. In his study finds out that the

relationship or co integration exists between the “Inflation and Industrial production”

5

(Quantum index) with stock prices while there exists no relationship between

“Exchange rate and stock prices”.

Sohail and Hussain. (2011). investigated in this study that “Inflation, Real effective

exchange rate and Industrial production have positive impact on Stock prices of KSE

100 index”, while the variables “Money Supply and three months Treasury bill” had a

negative impact on the Stock prices of KSE 100 index. The study recommended that

by taking right monetary actions to control the Inflation the volatility in stock market

can be decreased and such rules and policies should be carried and followed which

make good position of capital market and sustain stock prices through increasing and

raising Industrial production. Also recommended that exchange rate should be dealt

carefully while keeping the variation in Imports and exports in view to develop and

keeping stability in the Pakistan stock market specially Karachi stock exchange. The

study also suggested that in order to prevent stock returns from affected adversely the

three months Treasury bill rate should be kept low.

Nishat and Shaheen, (2004). This study investigated the data for period during 1973-

2002. And study concluded that reverse causality was founded between Industrial

production and stock prices and it is the leading positive determinant of stock prices,

and Inflation was founded to be the biggest negative determinant of stock prices and

can have a great effect of any news about inflation on stock prices.

Mohammad S. et al., (2009). This study also studied the “relationship between

macro-economic variables and stock prices” and for that the variables taken for

macro-economic indicators were Industrial production Index, Wholesale price index,

Foreign exchange reserve, Gross fixed capital formation, Foreign exchange rate and

Broad money (M2).

6

The study concluded that due to the reforms and liberalization of stock market in

1991 the Exchange rate had a significant impact on stock prices. The study also

concluded that with increase in IPI (Industrial production index) the stock prices also

increases.

Sajjad I, et al. (2012). this study was conducted to find out “relation between

Inflation, Exchange rate, Interest rate and Treasury bills”. The main conclusion and

recommendation of this study for government of Pakistan was to focus more on the

promotion of Equity shares because the increase of treasury bills and inflation rate

have no impact on KSE. The study found bi-directional ganger causality between

KSE and exchange rate.

Mohammad S. et al. (2009) the purpose of this study was to “find out if there exists

any correlation between macro-economic variables and stock prices of KSE 100 index

for the period 1986-2008 in Pakistan”. Different macro-economic variables used for

this study were “Industrial production Index, Wholesale price index, Foreign

exchange reserve, Gross fixed capital formation, Foreign exchange rate and Broad

money (M2)”.

The results of the study found the significant impact of Foreign exchange reserve and

foreign exchange rate due to the reforms and liberalization of stock market in 1991,

while other variables affect stock prices insignificantly. The study also analyzed that

the internal factors (increase in production, capital formation) are insignificant while

external factors (M2 and foreign exchange) have a positive impact on stock prices.

The study showed 10 % and 9% significance of Exchange reserve and IPI

respectively, which suggests that stock prices increases with the increase in IPI and

7

exchange reserve. Interest rate and M2 were founded negatively related, which

suggests that stock prices fall as the M2 and interest rate increases.

Sajjad I. et al. (2012) this study was conducted to “determine & analyze the

relationship between macro-economic variables” (e.g. Exchange rate, interest rate,

inflation rate and treasury bills) and “Stock KSE (Karachi Stock Exchange)” for the

period 2005-2010. Two tests “co-integration test and Granger Casualty” were applied

to find out this relationship. The purpose of this study is to “find out how macro-

economic variables impact and exaggerate the KSE index”.

The study results and conclusions showed that “bi directional ganger causality was

founded between KSE and exchange rate”, while KSE and interest rate have one way

“Ganger casual relation”. Inflation rate and Treasury bills were founded no Ganger

causal relationship with KSE. The main conclusion and recommendation of this study

for government of Pakistan was to focus more on the promotion of Equity shares

because the increase of treasury bills and inflation rate have no impact on KSE.

Nishat and M. Saghir, (1991) this study analyzed the “relationship between macro-

economic variables and Stock prices for the period 1974-2004”, Using KSE 100 index

as a dependent variable and CPI (Consumer price index), Foreign exchange rate and

IPI (Industrial production index) were used as explanatory variables.

Causal relationship was founded in the results of this study; Stock prices were

founded significantly affected by Industrial Productions. Unit root technique and

Grange causality test were used to find out the correlation among Macro-economic

variables and stock prices. In results of Granger causality test it was founded that

stock prices are not ganger caused by interest rate.

8

Sohail and Hussain (2009) this study analyzed the Long run and short run relationship

between macro-economic variables (Inflation, money supply, industrial production

and exchange rate) and Stock Prices. Their data was used for the period 2002 – 2008.

Lahore stock Exchange was used as indicator for stock prices.

The results and conclusions shows that stock prices are negatively affected by

Inflation while positively affected by Industrial production, Money Supply and real

effective exchange rate.

Mallaris et al., (1991) this study was conducted “to analyze the relationship between

macro-economic variables and S&P 500 index”. The variables taken as indicator for

macro-economic variables are “interest rates and industrial production”.

The results of this study challenged that financial studies for relation between these

three variables results are not significant statistically. So the results of any study about

relation between these variables can be different time to time and can be analyzed

differently and there may be some other factors too that can effect stock prices. So it’s

more important to know whether macro-economic variables have any impact on stock

prices or equity market of Pakistan and how KSE and other stock exchanges respond

to macro-economic variables.

This Literature Review pointed out some important points to be noticed:

Stock Prices are not always affected by same variables, there are some other

factors and variables which must not be ignored and should also be

investigated.

9

Impact of macro-economic variables on stock prices is also based on some

other events taking place in the economy. That’s why the differences may

exist between studies conducted during different intervals of time.

This study is “to analyze the relationship of macro-economic variables such as

Consumer price index, Quantum index and Exchange rate with stock prices (KSE-100

index) and if there exists any impact of macro-economic variables on stock prices”.

The data that will be carefully analyzed to conduct this study will be for the time

period of 2005-2010.

10

2.2 Research Questions and Hypothesis

The literature review has been studied and investigated thoroughly and some finding

and ideas were taken for the further analysis of study on this area for the period 2005-

2010. After studying the literature and making a review some hypothesis are made on

the basis of literature review, these hypotheses will be discussed below.

This study is to investigate and analyze relationship between “macro-economic

variables (Consumer price index, Quantum index and Exchange rate) and stock

prices” to provide answer for the following Hypothesis:

H1: There is negative relationship between Consumer price index and stock prices.

H2: There is positive relationship between Quantum Index and Stock prices.

H3: There is negative relationship between Exchange rate and stock prices.

This study will analyze the five years monthly data from 2005 to 2010 is

selected and analyzed for all variables.

11

2.3 Theoretical framework

Independent Variable Dependent Variable

To find out the relation between the variables “Unit root test and Co-Integration test

will be used”. To check the stationary in the data we use the E-views software and

apply “Unit root test”. Co-integration will be used to “investigate the long term

relationship”. And in last Regression will be used to analyze any impact of

independent variables on dependent variables.

12

Stock Prices

KSE-100 Index

CPI (Consumer Price Index)

Quantum Index (Industrial Production)

Exchange Rate

Chapter 3

METHODOLOGY

3.1 Sample Methodology

For the analysis of this study five years of monthly data will be taken from 2005-

2010. The data used in this study is for four variables- “Consumer Price Index,

Quantum Index, Exchange rate and Stock Prices”.

Consumer Price Index: is taken and represented by Inflation. Consumer Price Index or

CPI is an indicator of macro-economic variables.

Quantum Index of manufacturing is an indicator of Industrial Production

(Manufacturing). For the real economic activity the Quantum Index of Manufacturing

or Industrial production is considered as a proxy.

Exchange Rate: refers to the Foreign Exchange rate or FX rate in terms of Dollars. It’s

also one of the main indicators of macro-economic variables.

KSE-100 Stock Prices: Finally Data for stock prices is taken for KSE-100 index.KSE-

100 index is the representative of Pakistan Stock market and shows average of all

stocks in Pakistan stock market. In Pakistan the KSE-100 index is used as a

Benchmark index having top hundred companies listed.

13

3.2 Sources of Data

The monthly data for this study that is been taken for the period of 2005-2010. The

sources used for monthly data of four variables are different. Data for Consumer Price

Index, Quantum Index of Manufacturing and Exchange rate were taken from monthly

statistical Bulletin of State Bank of Pakistan and Economic survey of Pakistan for

relevant years. The data for Historical stock prices of KSE-100 index was taken from

Yahoo financial services.

3.3 Statistical tools

For data analysis and to answer the hypothesis given above “Unit root test, Co-

integration test and Regression analysis” will be used.

In research studies some of the time series data is non-stationary. To check whether

data is stationary or non-stationary study will use Unit root test. After the data is

analyzed with Unit root test and the stationary of data is investigated the next step will

be to analyze the long-term relationship between the variables, for this study will use

the “Co-integration test”. Furthermore to check whether there is any impact of

Independent variables on dependent variables Regression analysis will be used.

14

Chapter 4

RESULTS AND DISCUSSION

4.1 Unit root test analysis

In macro- economic some of the time series data are non- stationary. The non-

stationary time series data can create error in analysis and results. To check whether

the data is stationary or non-stationary “Unit root test” is used. If two results are

shown as I (1) then Co-integration test is used to see any long run relationship

between the variables if the long run relationship is founded between the variables I

(1) then it’s said to be Co-integrated. Now the study will first discuss the “Unit root

test” results.

I(0)

CPI

Table-1

t-Statistic   Prob.*

“Augmented Dickey-Fuller test statistic” -5.066650  0.0005

Test critical values: 1% level -4.096614

5% level -3.476275

10% level -3.165610

15

I(1)

ER

Table-2

t-Statistic   Prob.*

“Augmented Dickey-Fuller test statistic” -3.296694  0.0188

Test critical values: 1% level -3.528515

5% level -2.904198

10% level -2.589562

I(0)

QI

Table- 3

t-Statistic   Prob.*

“Augmented Dickey-Fuller test statistic” -4.014702  0.0024

Test critical values: 1% level -3.530030

5% level -2.904848

10% level -2.589907

16

I(1)

SP

Table- 4

t-Statistic Prob.*

“Augmented Dickey-Fuller test statistic” -7.554316 0.0000

Test critical values: 1% level -3.527045

5% level -2.903566

10% level -2.589227

“Unit root test” mean that we have to check the stationary of the data. The probability

value of CPI is less than 0.05 on level which means the data for Consumer Price

Index is stationary. The p value of the exchange rate is less than 0.05 at 1st difference

which means that the data is at 1st difference. When the data is found to be less than

0.05 at 1st difference then we have to check whether there is really a relationship

between the variables, for that we have to apply the co-integration test to check the

long relationship.

The probability value of “Quantum Index of manufacturing” is less than 0.05 on level

which means the data is stationary.

The p value of the Stock Prices is less than 0.05 at 1 st difference which means that the

data is stationary at first difference. Now we will have to check the relationship

between, for that we have to apply the co-integration test to check the long run

relationship.

17

The results of Unit root test shows that two variables shown as I(0) are stationary at

level and two variables shown as I(1) (Exchange rate & Stock prices) are at 1st

difference. When two variables are found to be stationary at first difference then we

have to check the long run relationship between the variables, now to check the long

term relationship we will analyze the results of Co-integration test.

4.2 Co- integration Analysis:

As earlier discussed in the study that If the variables are found to be at 1st difference

or I(1) then we have to check the long run relationship between these variables for

that we use Co-integration to know that if there exists any Co-integration among the

variables.

Co-integration Rank Test (Trace)

Table- 5

Hypothesized Trace 0.05

No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.395272  65.51245  47.85613  0.0005

At most 1 *  0.294777  32.81902  29.79707  0.0218

At most 2  0.120901  10.11836  15.49471  0.2718

At most 3  0.026453  1.742598  3.841466  0.1868

18

Co integration Rank Test (Maximum Eigenvalue)”

Table- 6

Hypothesized Max-Eigen 0.05

No. of CE(s) Eigenvalue Statistic Critical Value Prob.**

None *  0.395272  32.69343  27.58434  0.0101

At most 1 *  0.294777  22.70066  21.13162  0.0298

At most 2  0.120901  8.375761  14.26460  0.3418

At most 3  0.026453  1.742598  3.841466  0.1868

Co-integration: We run co-integration test to know the relationship between the

variables. In co-integration test analysis the Max-eigen value test shows that there are

two co-integrated equation exists which shows the long run relationship among the

variable. Now as the study analyzed that there exists the relationship, so for further

analysis we will run the Regression analysis to check whether if there is impact of

independent variables on dependent variable.

19

4.3 Regression Results

In Co-integration analysis we founded that there is co-integration among the variables

and founded “two co integrating eqn at the 0.05 level”. Now we will examine the

impact of independent variables on dependent variables, for that the study uses

Regression analysis. Following results will be discussed for Regression analysis.

Table- 7““Variable Coefficient Std. Error t-Statistic Prob.”

C 15446.90 3084.478 5.007945 0.0000

EX -584.6708 74.99754 -7.795867 0.0000

QI 45.48292 10.96709 4.147219 0.0001

CPI(-2) 12.13034 6.553671 1.850923 0.0692

CPI(-3) 406.6812 102.6258 3.962757 0.0002

CPI(-4) -261.3841 103.4649 -2.526307 0.0142

“R-squared 0.715254 Mean dependent var 10116.90

Adjusted R-squared 0.691123 S.D. dependent var 2243.805

S.E. of regression 1247.034 Akaike info criterion 17.18269

Sum squared resid 91750529 Schwarz criterion 17.38340

Log likelihood -552.4374 F-statistic 29.64038

Durbin-Watson stat 0.832180 Prob(F-statistic) 0.000000”

“

20

The p value of exchange rate is less than 0.05 which means that it is significant but

the co efficient value is negative so it shows that Exchange rate have a negative

relationship with Stock prices, Hence the Hypothesis “H3” is excepted. The P- Value

of Quantum Index of manufacturing is also less than 0.05 and is having a positive

significant impact on stock prices; hence “H2” hypothesis is also accepted. The p-

value of CPI has different impacts according to 2, 3 and 4 months. For two months

CPI have no impact on stock prices so the hypothesis “H3” will be rejected in that

case. while after four months inflation (CPI) or any news about Inflation have

negative impact on Stock prices, So we can say that any news about Inflation can

bring change or impact stock prices after the duration of two months but before this

time it have no such significant impact on stock prices. From this analysis we

conclude that hypothesis H1 and H2 are accepted for this study while H3 have no

such significant before two months of time but after the period of four months the

hypothesis H3 is also accepted because it have a negative impact on stock prices.

R square value show the significance of the model 71% change due to explained

variables which are included in the model and 29% due to unexplained variables

(Some other factors), R square value shows that the model is strong. The Durbin

Watson value must be 2 which show that there is no auto correlation but here in the

above table we have the value 0.83 which is less than 2 which show that there is auto

correlation in the data but because LM Test is used in this analysis that’s why “Durbin

Watson” value have no such impact on analysis.

21

“Breusch-Godfrey Serial Correlation LM Test:”

F-statistic 17.49087     Probability 0.000001

Obs*R-squared 24.72027     Probability 0.000004

LM test show the serial correlation of the data. The Obs* R- squared value is less than

0.05 which means that it is significant shows that there is serial correlation in the data.

22

Chapter 5

CONCLUSION

This study used data for the period 2005-2010 to analyze “the relationship between

macro-economic variables such as consumer price Index (CPI), Quantum Index of

manufacturing (Industrial Production), Exchange Rate and Stock prices of KSE-100

Index”. The study used “Augmented Dickey-Fuller test” to know whether the data is

stationary and founds that two variables shown as “I (0) (Consumer Price Index &

Quantum Index)”are stationary at level and two variables shown as “I (1) (Exchange

rate & Stock prices) are stationary at first difference”.

The p value of the exchange rate and Stock prices is less than 0.05 at 1 st difference

which means that the data is stationary at first difference. When the data is found to

be less than 0.05 at 1st difference then we have to check whether there is really a

relationship between the variables, for that the study applied “co-integration test to

check the long run relationship”.

The Co-integration test results show that two co-integrated Equations exists in the

Variables. That means the Co-integration exists among the variables. So the study

analyzed that the relationship exists between the variables. But to check whether one

variable have impact or effect the dependent variable we analyzed the Regression

analysis.

The Conclusions of the Regression analysis for this study are that 71% impact on

stock prices is due to the explained variables and other remaining impact is due to

other factors or variables. The Exchange rate is negatively significant with stock

23

Prices so have a negative impact on stock prices. It means that as Exchange rate rises

the stock prices start to decrease in Pakistani market. So the investors, companies and

banks etc. must look for any positive or negative change in Exchange rates to respond

to the market. The Quantum Index of Manufacturing is positively significant to the

stock prices. That means the “Quantum Index (Industrial production) have a positive

impact on stock prices”, As there come any change or news about industrial

production Quantum Index the Stock prices shows positive feedback to the news

about such changes.

CPI was founded having different impacts on Stock prices that are the one unit

Change in CPI before 2 months and three months have positive impact on stock

prices, and one unit change in CPI before four months have negative impact on stock

prices. That concludes that stock prices don’t react to inflation in two or three months

of times, but react negatively to inflation after four months of time.

24

REFERENCES

Akbar, Muhammad, Shahid Ali, Muhammad Faisal Khan. "The relationship of stock

prices and macroeconomic." African Journal of Business Management, 2012:

1315-1322.

Ali, Imaran, Kashif Rehman, Ayse Kucuk Yilmaz, Muhammd Aslam khan, Hasan

Afzal. "Causal relationship between maro-economic indicators and stock

exchange price in Pakistan." African Journal Of Business Management 4, no.

3 (2010): 312-319.

Imran Ali, Kashif Ur Rehman, Ayse KucukYilmaz, Muhammad Aslam Khan,

HasanAfzal. "Impact ." Jouranl of business , 2010.

Mallaris, A.G. Urrutia, J.L., 1991, An empirical investigation among real, monetary,

and financial variable, Economic Letters, 37, 151-158.

Mohammad, Sulaiman, Adnan Hussain, Anwar Jalil, Adnan Ali. "Impact of

Macroeconomics Variables on Stock." European Journal of Scientific

Research, 2009.

Nishat, Muhammad, Rozina Shaheen. "MACROECONOMIC FACTORS AND

PAKISTANI EQUITY MARKET." 2004.

Nishat M, Saghir M, (1991). The stock Market and Pakistan Economy, Savings and

Development 15:2. 131- 145

25

Sajjad , Shafi, Jan , Saddat, Rehman I, (2012). “Exploring the Nexus; Stock Market, T.

Bills, Inflation, Interest Rate and Exchange Rate” Journal of Economics and

Behavioral Studies Vol. 4, No. 7, pp. 384-389.

Sohail, Nadeem, Zakir Hussain. "The Macroeconomic Variables and Stock Returns

in." International Research Journal of Finance and Economics, no. 80(2011)

(2011).

26