Impact of macroeconomic variables on stock returns

Impact of macroeconomic factors on stock returns 1
Chapter # 1
Introduction

1.1 Introduction
Investigating the impact of macroeconomic factors on stock returns is one of
the most important areas of finance. Many studies have been conducted to find out the
influence which different factors can make on the stock returns including
macroeconomic variables. In this study, we have selected different variables i.e.
exchange rate, interest rate, oil prices, GDP, and FDI. Basically, while talking about
the small economies, stock market can play a vital role in organizing economic
resources within the country as well as outside the country to achieve better economic
condition. Because it is the market from which funds flows from individuals and
corporations across the globe to the investors exist in an economy. GDP is a primary
measure; it is the money value of services and goods produced with in a country in a
certain period. Exchange rate is the rate at which one currency can be exchanged for
another while the FDI is also an important source for economic development. The
discount rate is also a key variable of the economy and oil price plays significant role
in economy.
It is commonly believe that when macroeconomic variables fluctuate then it
also increases or decreases the returns of stock. As Chen, Agrusa, Krumwied and Lu
(2012) argue in their study that returns are influenced by the change in stock prices
and several macroeconomic variables. However, there are certain economic variables
which have strong or medium relationship with stock returns. Investors here look for
an accurate valuation of returns of their investment so they can earn maximum profit.
On the other hand the study will also useful for the planners, they can create more
opportunity to earn in a stock market after acknowledge that what variables have what
directions of effecting to returns. This study also can answer the gap between

theoretical concept and practical facts about the economic variables and stock returns
behavior.
1.2 Statement of problem
The stock Market return is one of the most important topics in the recent times
around the globe. Many studies have been in the recent years to find out the factors,
which affect the stock returns. The studis on individual exchanges like Istanbul Stock
Exchange (ISE) (Rjoub, Türsoy & Günsel, 2009), Karachi Stock Exchange(KSE)
Nazir, Nawaz, Anwar and Ahmed (2010a); Zafar, Urooj and Durani, 2008; Iqbal and
Javed (2012); Haque and Sarwar (2012), also on the multi exchanges like India and
China’s stock market index (Hosseini, Ahmad, & Lai,2011) USA, UK, Canada and
Australia (Karunanayake, Valadkhani, & O'Brien, 2012) and many more with the
number of different factors including several macroeconomic factors are examined in
the recent past.
So finding out the impact of the macro economic factors is important for both
the investors and financial analysts as to estimate the price and ROI.
So there is a need to fulfill the knowledge gap in the Pakistani financial sector.
As Özlen Ergun (2012) said “Developed countries’ financial markets are observed to
be more explained compared to the other financial markets. Therefore, the research is
needed in order to improve investment decisions by maximizing the expected value of
stock returns in developing economies” (p. 315) for the better insight of the Pakistani
as well and the foreign investors along with the policy makers to develop the strategy
for improving the investment in the stock market.

1.3 Researchquestion
 What are the effects of macroeconomic factors on stock returns in Pakistani
stock market?
1.4 Objective of the study
The objective of this work is to improve the current knowledge associated
with the influence of the several macroeconomic factors on the stock market returns
in the Pakistani context and to examine the relationship of these specific factors with
the stock returns. Furthermore the study tries to find out the empirical evidence of this
relationship.
1.5 Significance ofthe study
This study helps the investors for knowing the better inside of the impact of
macro-economic factors on stock returns. It also provides them, current knowledge of
the stocks returns. With the help of that study we can find the relationship between the
different factors of macro-economic with the stock return and also present that which
factor has more impact than another factor. Similarly, by knowing the impact of
macroeconomic factors on stock, investor’s capabilities will be enhanced which helps
in improving decision making.
1.6 Limitation and delimitation of the study
The research is limited to available data from 1960 to 2010 of Karachi Stock
Exchange (KSE) only. Variables are also limited that researchers analyze some
variables like inflation, interest rate, exchange rate, gross domestic product (GDP), oil
prices and foreign direct investment (FDI) due to shortage of time and budget.
Research is also limited to regression method.

The several other models like EGARCH, GARCH, ADRL, DBEKK, VAR
and VECM can be used to delimit the study. However, more data can be analyzed to
get the better insight. In this regard, the data of Islamabad stock exchange (ISE) and
Lahore stock exchange (LSE) can be used. In addition, the more variables like money
supply (M1 & M2), gross national product (GNP), unemployment, budget deficit,
discount rate etc. can be the delimitation of the study.

Chapter # 2
Review of Related
Literature

2.1 Theoretical background
2.1.1 Financial market
Financial market tells about a platform where sellers and purchasers do their
business collectively. This market makes a difference in detail whereas the
highlighted differences are way of trading of shares, types of shares as well as who
are the dealers. Transactions are made like other market but the products are different
in this market that is shares and debt (Ross, Westerfield, & Jordan, 2001).
2.1.2 Primary versus secondary markets
There are two functions of financial market: primary market function and
secondary market function. Secondary market come into exist if there is any primary
market. In primary market corporations as well as government sells the securities in
other words first time they issue. When, these securities are sold again in the market
that market is called secondary market. Government just issues the debt securities
however corporations can issue debt securities as well as equity securities (Ross, et
al., 2001).
2.1.3 Stock market
The market as discussed before, where the securities are resale issued by the
various corporations. This is the market that financial managers are more concern
about and keep focus on. On the other side this is the market where the value of any
securities of corporation fluctuates and decided. Usually, in every country there are
stock markets according to its cities just like in Pakistan Karachi stock exchange,
Islamabad stock exchange, Lahore stock exchange. In India: Mumbai stock exchange,
in Nigeria: Nigeria stock exchange. Many investors invest with the portfolio

investment. So, a large company’s shares are purchased by different investors that
exceeds from 50 percentages of issued shares that company become a public company
(Brigham & Houston, 2009).
2.1.4 Stock market returns
The investors who invested in the market they know that there is some
expected return of their investment from the stock market. The returns, an investor get
from the market by investing in shares, is called stock market returns. When investor
analyses the return of stock, the return cannot be predetermined. The returns depend
upon the firms profit on the other hand profit and returns also depend upon many
factors i.e. macroeconomic variables: inflation, interest rate, GDP etc. that describe
the relationship and impact of multi factors of macroeconomic on returns (Brigham &
Houston, 2009).
2.2 Empirical studies
Kpanie and Vivian (2014) have conducted the research of Ghana stock market
with the selected variables of macroeconomics under the umbrella of ADF co-
integration analysis and error correction model. The data was collected on quarterly
basis. Selected variables were analyzed in which Money supply (MS), Treasury bills
(TB) (for interest rate proxy), inflation rate (INF), Exchange rate (ER) and oil prices
(OP) were included. Research findings acknowledge that OP and MS are significant
with respect to Ghana stock market by 1%. The research findings also show that there
are long term relationship among the Ghana stock market and some of the
independent variables. Further interest rate (TB), ER and INF show the negative
relationship with respect to Ghana stock market at both lagged. However, MS has
negative relationship at first lagged and significant positive on the second lagged.

Beside these, overall result also illustrate that there is co-integration among the all
independent variables.
Ullah, Hussain and Rau (2014) scrutinize the impacts of macro-economy on
stock market by scrutinizing the data from January 2008 to December 2012.
Exchange Rate (ER), Interest Rate (IR) and Inflation (Inf) has been considered in the
study while the Bound Test Approach has been used in it. The results show that stock
market of Pakistan has been negatively influenced by both the Exchange and Interest
Rate while the Inflation doesn’t have noteworthy impact on stock market. They
suggest that the government should closely monitor and use the Exchange and Interest
Rate to boost the Stock Market’s performance.
Chang (2013) investigated about whether there is any hedge against inflation
or not within the context of Japanese stock market. For this study, he used ADL
bounds test. Ten years of data has been used which is 2001M1 to 2011M7. On the
other hand one more study is investigated which is granger causality between inflation
and stock market returns. Japan is one of those countries who believe and lead people
that inflation is advantageous to the stock market. Many studies conducted on
relationship between inflation and stock returns. Most of them result that there is
positive relationship and approve the Fisher’s hypothesis where as some of the study
result the negative relationship. In last the result determines that there is inverse and
long term relationship of stock returns with inflation. While in the short term, the
change in stock return because of the inflation rate can be controlled within the three
months and can be constant more.
Ibrahim and Agbaje (2013) study the long-run relationships and dynamic
connections amid stock returns and inflation in Nigeria by using monthly data of all
share price index from Nigerian Stock Exchange (NSE) and Nigerian Consumers

Price Index by using data from January 1997 to 2010.A key thing consider in this
study is capital market stock that is The Stock market. Buying and selling of listed
stock in Nigeria is done in Nigerian Stock Exchange (NSE). Listed stocks in Nigeria
are trade on floor of the Nigerian Stock Exchange (NSE) whereas Securities and
Exchange Commission (SEC) is supreme regulatory and supervise activities and
dealings of the foremost players on floor of Stock Exchange.
Variables used for the study; are stock return, co-integration, and inflation also
includes Nigerian Stock Exchange (NSE). The study uses the analytical technique
which was proposed by Pesaran and Pesaran (as cited in Ibrahim & Agbaje, 2013)
Autoregressive Distributed Lag (ARDL) for co-integration and to know relationship
between other variables researchers give estimation model in which one is represent
all share indexes (ASI) and other is for consumer price indexes (CPI). Results indicate
that both ASI and CPI are co-integrated and there is long run relationship among
inflation and stock returns, projected coefficient of inflation have important and
positive impact on stock and casual relationship in-between inflation and stock
returns. This study also verifies a Fisherian hypothesis and declared a positive result
of inflation on stock returns.
Zafar (2013) investigated the performance of stock market determinants
through macroeconomic variables for Pakistan. The data of 20 years, 1988 to 2008,
was used. The institutional variables were not examined because absence of precise
data that is why macroeconomic factors were used which are: domestic credit issued
by banking sector, real interest rate, value traded and foreign direct investment as a
rate of gross domestic product. Quantitative technique was used by regression.
The outcomes are not conflicting with academic extrapolations which show
that there is strong positive linkage among FDI and stock market performance. Stock

market performance as a rate of gross domestic product would be growing by 6.78%
if the FDI as a rate of gross domestic product grow by 1%. On the other hand real
interest rate and stock market show adequate negative linkage. The condition is that
stock market performance as a rate of gross domestic product declines by 1.218% if
the real interest rate as a rate of gross domestic product grows by 1%. Further there is
a progressive moderate linkage among stock market performance and value traded as
a rate of gross domestic product. In last, stock market have insignificant relationship
with intermediaries.
Chen et al. (2012) analyze the effect of eight macroeconomics variables in the
context of Japan’s hotel stock returns. The variables are changes in discount rate
(DSCHG), consumer price index (CPI), money supply (MS), unemployment rate
(UP), and industrial production (IP), but these are the variables which are usually
studied by different authors. Chen et.al further added three more variables which are
yen-dollar exchange rate (EXCH), change in oil price (OILP) and total trade (TTR).
For the research six companies of Japan have been selected with 30 years of data from
January 1976 till June 2006 about stock prices.
Returns are influence if there is a change in stock market value and several
macroeconomic variables. Chen et.al look at study which is conducted in Taiwan that
shows only changes in unemployment rate and growth rate of money supply can be
the determinants of hotel stock returns. Beside that Chen et.al also investigate that
what relation exist between macroeconomics variables and stock return in a
developed country through vector auto regression (VAR) model. The hypotheses were
that DR, UP, CPI and OILP have a significant and negative impact on hotel stock
returns whereas MS, IP, EXCH and TTR have a significant but positive impact. Chen
et.al used the Granger causality procedure based on VAR model to find the result.

Their findings were that DSCHG, UPCHG and change in OILP, out of the eight
variables, can significantly cause the hotel stock returns in Japan on the other hand
DSCHG, growth rate of MS, change in OILP and change in TTR can Granger cause
the market returns. Hence, there are two variables which are common in both returns
that are DSCHG and change in OILP (Chen et. al, 2012).
Hassan and Rifai (2012) focus on the study that if there is any effect of macro-
economic factors on equity returns in both underdeveloped and developed stock
market. They see the long term relationship among equity return and macroeconomics
variables in Jordan. General to specific (GETS) and Autoregressive distributed lag
(ARDL) both are used to specify the results. There are several researches that have
been examined the relationship among the economics activities and stock market
returns. In a study researcher conclude that stock market is influence by interest rates,
inflation rates, industrial production and bond yield spreads. The study is investigated
for the role of economic activities on emerging stock market in Jordan especially
concerning oil price impact.
The hypothesis of the study is a linkage among the Jordanian stock market and
several economic activities and the point of departure is to search the long and short
term linkage among Jordanian stock market and macroeconomic factors. There are
many economic variables which are allied to business cycles that can impact the risk
and return of stock market. The result of the study show that money supply, foreign
exchange reserves, oil prices and trade surplus are the factors of macroeconomics that
influenced the Jordanian stock market. Hassan and Rifai (2012) put forward that there
is positive relation of money supply and stock market, further concluded that stock
market will result in negative if there is increment in the price of oil.

Haque and Sarwar (2012) investigate the relation between stock returns and
macro-determinants on equity returns. For this they consider the data from the period
1998 to 2009 which includes 394 companies listed in the Karachi Stock Exchange
(KSE). Gross domestic product (GDP), money supply, inflation, consumer price
index, volatility, budget deficit and interest rate were considered as variables. The
data was collected from the KSE reports, publications of federal bureau of statistics,
bulletins of state bank of Pakistan and business recorder. Panel data specification test
is applied to test the relationship. A regression equation is estimated to find out the
effect of macro-determinants on equity returns. The results confirmed a strong
association between equity returns and variables. The result shows that volatility and
gross domestic product are significant positive while interest rate, budget deficit,
money supply, consumer price index and money supply are negatively related. The
results of this study will benefit people like portfolio manager, policy makers and
other concerned people while inspecting the stocks.
Iqbal and Javed (2012) investigate issue for a rising market that is Pakistan. A
main purpose of study is to give practical proof that macroeconomics variables can
help to predict instability of stock in case of local as well as international market. The
research focuses on daily data along with monthly from stock market index KSE- 100
and other is obtain from yahoo finance which is S&P- 500. Eleven years data used as
a data sample in which macro data of Pakistan are excluded like call money rate,
money-stock, consumer prices and exchange-rate because their current data equal to
July 2010. International Financial Statistics is used to get Pakistani macroeconomics
data.
To get recent US macro data researcher access the economics research
division from website of Federal Reserve Bank of St. Louis and same source use to

know most recent oil prices. The study uses the rising markets which are characterize
through superior instability, also superior related profit compare with develop market.
Results indicate that business and international macro-economic condition can be
affected through instability of rising market. Central role played by stock price
volatility in decision making of both financial and economics. Result also shows, in
Pakistani market investor decrease the risk at the time of increase in oil prices and
when level of activity in foreign market is high.
Karunanayake et al. (2012) investigate the interplay among stock market
returns and GDP growth rate by analyzing the data from 1959 to 2010 on quarterly
basis and a multivariate GARCH model on four countries i.e. USA, UK, Canada and
Australia. He argued that the US economy influences all the three economies as it is
the strongest. In this study they examine the interdependency of stock market returns
and real GDP in the three continents. They further added that because of
globalization, it is very important to understand and determine the cross-country
interactions from the aspect of investor and policy maker. In this study, they use the
diagonal version of DBEKK. The DBEKK model is widely used especially for the
purpose that it reduces the number of parameters as well as it guarantees the positive
definite of variance. The results pointed out that the quarterly mean and mean GDP
growth rates of all four stock exchanges are positive. Also it is found out that the US
stock exchange is the least volatile and the Australian stock exchange demonstrates
the highest volatility. The results also show that the stock return series of the four
countries are negatively skewed (Karunanayake et al., 2012).
Nopphon (2012) analyzes the macro-variables and stock returns considering
variables that are categorized into four groups that are factors regarding the price
level, monetary policy and interest rates, variables reflecting economic conditions and

variables concerning international activities. Variable concerning price level includes
oil prices and etc., variables concerning international activities includes FDI and ER,
while the variables concerning economic conditions include industrial production
index and employment level. This paper investigates that different techniques have
been used to identify the results of those relationships that are regression models,
GARCH family model and the volatility clustering, dynamic model and long run
relationships and event studies. The regression equation is the most standard
technique to test the relationship in which an equation is used. Numerous studies
show that there is linkage between the macro-variable factors and stock returns. But
the results of these studies are not directly comparable as they all applied different
techniques and methods. Current results are mix, as some studies show that these
variables can describe future returns, while the other studies show the reverse case.
Özlen and Ergun (2012) explore the effects of Macroeconomic Factors on
Stock Returns, the data of February, 2005 to May, 2012 has been extracted from
Turkish Central Bank, websites of ISE and Turkish Statistical Institute to
examine the stock returns of 45 listed corporations from 11 different sectors. They use
five variables Unemployment rate, exchange rate, interest rate, current account deficit
and inflation. They choose Autoregressive distributed lag method to test these
variables. Results indicate that most significant determinants of stock return are
exchange and interest rate regardless of the type of companies and impact all the
sectors or the economy constantly and industry respond significantly on the changers
occurred in exchange rate and interest rate. Hence it is suggested policy makers of the
economy could carefully do changes in interest and exchange rate because it plays
critical role to control the hazard of recession and financial crises in the economy.

Additionally, exchange and interest rates could be used to forecast the company’s
stock returns.
Samadi et al. (2012) study the linkage between macro-variables and stock
returns of Tehran Stock Market through the use of monthly data of stock returns index
including all the listed companies in Tehran Stock Exchange in the period of April
1999 to the July 2011. The inflation, exchange rates, liquidity, oil price and world
gold prices are considered as a key variable. The study uses the GARCH model and
Results reveal the inflation, foreign exchange rate and gold price have significant
relationship with the stock return while liquidity and oil price have no such impact on
stock return consequently it is recommended that at macro level the policy maker
should consider the impact of these variables on indexes of stock and other financial
markets while making monetary and financial policies.
Zhu (2012) research a study to see the influence of macroeconomic variables
on stock returns. The energy division is concerned of (SEE) Shingai stock market.
Variables are industrial production, money supply (M2), unemployment rate, imports,
exports, bond, inflation rate and exchange rate. Six years of data from 2005 to
2011collected from National Bureau of Statistics and People’s Bank of China. To
display the energy sector the data are chosen from SEE. The results substantiate the
hypothesis in which there is positive linkage among exchange rate and stock returns,
Chinese money (CNY) is decline compared to US dollar if the energy sector’s stock
return grows.
However, there is negative linkage among stock returns and exports that show
each time exports grow if industry’s stock return declines. Further finding shows the
positive link of stock return and foreign reserve that define foreign reserve increases
at the same time stock return of the industry will also increases. The relation of

unemployment and stock return also show the positive connection which also
acknowledge that if stock return grows of the industry there will be also a positive
change in unemployment rate.
Hosseini et al. (2011) examine the impact of macroeconomic variables on
India and China’s stock market index. Four variables were taken in this study i.e.
inflation rate, money supply, crude oil price and industrial production. The data from
the year January 1999-January 2009 was taken. The article specifically focuses the
stock market fluctuations of developing countries rather than developed countries like
in past the studies were mostly conducted on developed countries. By understanding
the linkage among these factors and capital market, it will be very helpful for the
investors to diversify their risk by investing in different countries.
Different tests are performed for testing the hypothesis in which unit root test;
multivariate co-integration test and vector error correction model are included. After
the testing, the results show that there is a connection between these factors and stock
market index in both countries, in long and short run. In long run in china, money
supply, inflation and crude oil price show positive relationship while in India
industrial production and inflation shows positive impact. In short run, china’s stock
market shows positive relation with money supply and inflation rate, while India’s
stock market shows positive impact with crude oil. These relationships help investors
in their decision making so that they have knowledge of different economies
(Hosseini et.al, 2011).
Kuwornu and Owusu-Nantwi (2011) conducted the research among the
relationship of stock market returns with the particular variables of macroeconomics.
Sample size for this research was from 1992 to 2008 monthly. Selected variables for
the study were Consumer Price Index (CPI); Crude oil prices (OP), ninety one day

Treasury bill rate (TB) as well as exchange rate (ER). The research was carried out in
the context of Ghana by using the method of Full Information Maximum Likelihood
Estimation. Results revealed that ER and TB have significantly negative relationship
with the stock returns in Ghana, while the CPI which used as a proxy of inflation
shows the significant positive relationship. However, OP was the only variable which
volatility did not make any significant changes on stock returns of Ghana.
Singh, Mehta, and Varsha, (2011) scrutinizes the relation of stock price and
the macroeconomic variables. This study takes place in Taiwan to inspect the casual
connection between index returns and certain key macroeconomic variables such as
GDP, employment rate, inflation, money supply and exchange rate. Interestingly, this
investigation is based on stock portfolio rather than stocks. Four areas have been
observed while this examination P/E ratio, market capitalization, PBR and yield. The
data was taken from Taiwan’s Stock Exchange where 50 companies were listed. The
data from the year 2003 to 2008 was taken from Taiwan’s stock exchange’s website.
Firstly, the companies were grouped as small, medium and big companies based on
market capitalization. Secondly three portfolios were made on the basis of P/E ratio,
PBR and yield. Linear regression was estimated. Exchange rates impacts portfolios
positively. The findings of this study demonstrates that except the PBR, GDP and
exchange rates affects all the portfolios return of small companies, on the other hand,
money supply and employment rate don’t significantly affect the stock returns. It is
worth noticing that the effects of equity financing are positive. These findings are
noteworthy from the point of view of companies as well as investors. From the results
of this study, the investors and decision makers can develop gainful investment
according to changes in variables (Singh et al., 2011).

Benakovic and Posedal (2010) investigate the stock returns that were given on
fourteen stocks of the Croatian stock market. The data was taken from January 2004-
October 2009 and the factors that were considered are interest rates, market index, oil
prices, inflation and industrial production. The analysis contains both, the fourteen
stocks and sensitivity to factors was predicted. The multiple regression and cross
sectional regression model was used to estimate the sensitivity of the stocks. The
findings of the study shows that oil prices, industrial production and the exchange rate
are positively related to stock returns while the inflation has negatively impact the
stock return. In cross-sectional regression the sensitivities were taken as independent
while stock returns as dependent. The factor that affects stock prices the most was
market index which is positively related to the risk premium, while the other variables
were not significant.
Nazir, Khalid, Shakeel and Ali (2010) examine the impact of macro factors on
the returns of stock market by analyzing 216 monthly observations from January 1991
to December 2008; the stock returns are measured by all share indexes data of KSE
while the interest rate, exchange rate, inflation rate, GNP per capita, are considered
along with the political competition, types of institution and level of democracy and
autocracy phenomenon in Pakistan. The Exponential Generalized Auto Regressive
Conditional Heteroskedasticity (EGARCH) technique were used to find out the
relationship among these variables and it validates the previous finding that the stock
returns volatility or performance has inverse relationship with the inflation rate,
interbank interest rate , and exchange rate. Furthermore interest rate has greater
impact in this volatility.
On the other hand, per capita income has a direct relationship with the stock
returns because it persuades people to save and invests in stock market. They

recommended that to increase the returns and stock trading activities of equity market
of Pakistan the government should take the corrective actions to control the inflation
and interest rate. In addition, potential effect on the returns of stock market ought to
be forecasted by the regulator during devaluation of currency (Nazir et. al, 2010b).
Singh (2010) investigates the link among the macro-variables and the Indian
stock market’s index. The factors that were considered were industrial production,
BSE Sensex, exchange rate and wholesale price index. Data was taken from April
1995-March 2009 on monthly basis. Granger causality, correlation and unit root
stationary tests were used. The results that found were vague as there is strong
correlation among industrial production and BSE Sensex. Also the wholesale price
and BSE Sensex were strongly correlated. But exchange rate and BSE Sensex were
not strongly correlated.
Although the outcomes demonstrates that there is strong correlation between
the macro variables and the BSE Sensex but the connection that comes out was just
one i.e. industrial production and stock market that illustrates that Indian stock market
is in its emerging phase. The correlation among all the factors was high. The Granger
causality test illustrates that wholesale price and exchange rate is not liable to create
vibrations in the Indian stock exchange but there are some other factors which
influenced them.
Rjoub et al. (2009) investigate the effects of macro factors on stock returns by
analyzing the data of 193 corporations listed in Istanbul Stock Exchange (ISE) from
January 2001 to September 2005. They classified these companies into 13 portfolios.
In this study, six macroeconomic factors are considered that is unanticipated inflation,
real exchange rate, the term structure of interest rate, risk premium, money supply
(M1), and unemployment rate. In this regards the correlation and regression analysis

technique were used and Results specify that there is no serial correlation among
these portfolios.
The regression analysis pointed out the significant difference among these
market portfolios with respect to the macroeconomic factors. The complete analysis
results show that, statistically seven portfolios had significant effect of unanticipated
inflation while risk premium had a key impact on three portfolios. Alongside, money
supply influenced two portfolios and one portfolio by term structure. In contrast with
this the unemployment rate and real exchange rate has no such significance in all
portfolios statistically. Hence it is recommended that even though there is strong
linkage among stock returns and tested macro factors however some further
macroeconomic factors are also responsible for affecting the stock market returns in
Istanbul Stock Exchange (ISE) (Rjoub et al., 2009).
Gay Jr (2008) examines the link between the stock market price index and the
macro-economic factors of exchange rate and oil prices for the emerging economies
i.e. China, Brazil, Russia and India. The date was taken from March 1999 to June
2006. The Box-Jenkins ARIMA model was used to determine the link among the
dependent factor stock market price and the independent macro-factors i.e. Exchange
rate and oil prices. The analysis did not tell any significant relationship among the
variables. Other factors like interest rates, inflation and trade balance etc may impact
the stock prices more significantly. As assumed, the linkage between exchange rate
and the stock index price should relate positively. But it was found to exist among the
exchange rate and stock price for India, China and Brazil but not for Russia.
Zafar et al. (2008) examine that what effect can be on stock return if there is
volatility in interest rate. Volatility is checked through the monthly return of Karachi
Stock Exchange and the treasury bills of 90 days for the time of 2002 to 2006. The

GARCH (1, 1) model is used, one hand it is checked with and without interest rate’s
effect. The outcome shows that conditional market return has negative significant
impact on interest rate in contrast there is negative insignificant result of interest rate
with conditional variance returns. These outcomes mutually describe that interest
rates have “strong positive predictive power for stock returns” but “weak predictive
power for volatility”. Stock return’s variation has been studied many times that what
factors are affecting them. There is a significant role of stock market in measuring any
economy’s economic condition. Better stock returns define greater profitability of
firms as well as overall development of economy (Zafar et al., 2008). Stock return
volatility is defined as the fluctuations in the stock prices changes throughout a period
of time. There is more volatility when stock prices decreases rather than stock price
increases.
If there is any change in interest rate that will affect the company’s stock as
well as company’s shares in last it will also influence stock return. If interest rate goes
up then risk and required rate return of an investment will be higher but the
company’s profitability will be lower thus the stock value will be down (Zafar et al.,
2008). Investors are persuaded by high interest rate to retain their savings in bank
accounts for sake of higher profit. They prefer it on to put their money in risky stock
market. Whenever risk free return goes down, investors put their investment in stock
market. Therefore, the stock market arises when demand of stocks boosts and as a
result of interest rate cut (Zafar et al., 2008).
Ratanapakorn and Sharma (2007) investigate the short and long term relation
among the six macroeconomic variables and US stock price index (S&P 500) and by
using data from January 1975 to April 1999. The study observes that stock prices
have negative relationship with long term interest rate but short term interest rate,

industrial production, exchange rate, inflation and money supply have positive
relationship with it. Variables used for the study are money supply, inflation, real
economic activity, foreign exchange rates and short term and long term interest rate.
The study uses the technique vector error correction model (VECM) with Granger
causality after forecasting variance of that forecast is done by error correction model.
Results of study indicates that all of the long term variables have an effect on US
stock prices but there is no such confirmation or proof of short term variables. Among
all six macro variables which considered in study, only bond rate explain stock prices
of US more than any other variables.
Gan, Lee, Yong, & Zhang (2006) scrutinizes the connection among the New
Zealand stock index and seven macro-economic factors i.e. oil prices, inflation,
exchange rate, long term interest rate, money supply, gross domestic product, and
short term interest rate. The data was taken from January 1990-2003. Time series data
and monthly observations were taken of both dependent and independent variables.
Co-integration tests were applied during this study. To test that New Zealand stock
market is an important indicator for macroeconomic factors Granger-causality tests
and Johansen Maximum Likelihood were also applied. Also the innovation
accounting analysis was used to examine the short run dynamic linkage between New
Zealand stock market and the macroeconomic factors. The results of Johansen co-
integration test shows that there is long term relationship among the seven variables
and New Zealand stock market while the results of Granger-causality test indicates
that the stock market of New Zealand is not an important indicator because it’s stock
market is small if we compared it to the markets of developed countries. At the end,
the innovation accounting shows consistency with the other empirical results of stock
market.

Chapter # 3
Methodology

3.1 Researchapproach
In this research, quantitative research approach is used. The quantitative
researches put emphasis on scrutinizing the fundamental associations among
variables. The mathematical and statistical based methods and tools are used to collect
the data and quantify the results which help the researcher to draw conclusions.
3.2 Researchpurpose
The purpose of this research is to explain the causal relationship among the
variables. The explanatory research is used when little information about the subject
is known or past theories do not apply to the current study. Explanatory research
gathers data, clarifies problem and then creates initial hypothesis.
3.3 Researchdesign
The co relational research design is used in this study. It is a design which is
used to find out the linkage between two variables of the similar group. In addition it
investigates either there is any impact of one variable on the other or not. In simple
words change in one variable (independent) brings change in other variable
(dependent) of not and to which extent this co variation exists.
3.4 Data source
The data which is not collected by the researchers themselves is called
secondary data. In this research the secondary data is extracted from the bona fide
sources which are the websites of the Index mundi and World Bank.

3.5 Sample size and period
In this study, the data of Karachi Stock Exchange (KSE 100 index), from the
year 1993-2012 is taken.
3.6 Statistical technique
We use regression technique in the research. Regression is a statistical
measure which tries to determine relationships between a dependent variable and the
other independent variables. Dependent variable is usually denoted by Y.
3.7 Model
SR= αo+ β1ER+ β2IR+ β3GDP+ β4OP+ β5FDI+ ε
Where;
SR is Stock Return
ER is Exchange Rate
IR is Interest Rate
GDP is Gross Domestic Product
OP is Oil Price
FDI is Foreign Direct Investment
3.8 Model hypothesis
H01: Exchange Rate has an insignificant impact on stock returns
H02: Interest Rate has an insignificant impact on stock returns
H03: Gross Domestic Product has an insignificant impact on stock returns
H04: Oil Price has an insignificant impact on stock returns
H05: Foreign Direct Investment has an insignificant impact on stock returns

3.9 Variable description
Following are the variables of this study.
3.9.1 Stock returns
It is a rate which the investors get by overall its investment in the stock. It
consists of two parts dividend and capital gain.
3.9.2 Exchange rate
It is a rate at which one country’s currency can be traded for another.
3.9.3 Interest rate
It is a rate which is charged for the use of resources. It is frequently articulated
as a yearly proportion of the principal.
3.9.4 Gross domestic product
The monetary worth of the entire services and goods produced in a country.
3.9.5 Oil prices
It is a price of crude oil which is prevailing in the world in a year.
3.9.6 Foreign direct investment
Investment made by a company of one country in another country.

Chapter # 4
Data Analysis

4.1 Introduction
The core rationale of this paper is to scrutinize the impact of macroeconomic
variables on the stock market returns in Pakistan. The data of the factors has been
gathered from index mundi and World Bank website. To test the impact of
macroeconomic variables on the stock returns, the least square technique in regression
analysis has been used. To test the impact of independent variable on dependent
variable the following analysis has been done.
4.2 Summary of Statistics
Table # 1 descriptive statistic
GDP FDI ER OP DR SR
MEAN 3.792000 1.31600 57.54700 45.020500 12.42500 0.05150
MAXIMUM 7.6700 3.670 93.400 105.0100 19.000 0.250
MINIMUM 1.0100 0.380 0.380 13.0700 7.500 -0.170
STD.DEV 1.8722871 0.955557 19.065612 31.7955895 3.416350 0.127249
OBSERVATIONS 20 20 20 20 20 20
The above information is used to interpret the essential properties of the data.
The first factor is gross domestic product (GDP) growth which demonstrates
the maximum value of 7.6700 and the minimum value of 1.0100. Total number of
observations is 20, while no value is missing. The data shows increasing trend during
the period from 1993-2012.
The second factor is foreign direct investment (FDI) as percentage of GDP.
This illustrates the maximum value of 3.670 and the minimum value of 0.380. The
data demonstrates a mix trend of increasing and decreasing FDI from 1993-2012. But
it significantly increases from 2004-2007.

The third factor is exchange rate (ER) which is dollar into rupee. This
demonstrates the maximum value of 93.400 and the minimum value of 0.380. The
data illustrates an increasing trend for the duration of the period 1993-2012.
The fourth factor is price of crude oil (OP) per barrel in US dollar. This
demonstrates the maximum value of 105.0100 and the minimum value of 13.0700.
The data illustrates an increasing trend throughout the period from 1993-2012.
The fifth factor is discount rate of State bank of Pakistan. This demonstrates
the maximum value of 19.000 and the minimum value of 7.500.
The sixth factor (which is dependent) is stock returns calculated from KSE
100 index by using the percentage change method. This illustrates the maximum
value of 0.250 and the minimum value of -0.170. The data consist of seven negative
and thirteen positive stock returns of KSE 100 index.
4.1.1 Parameter Estimation
Table # 2 Estimated Results
Variable Coefficient T-Statistics Probability VIF
C -2.947688 -1.786566 0.1172
DR 1.247192 2.077031 0.0764 1.480
ER 0.074129 4.064093 0.0048 1.655
GDP 1.418971 4.958068 0.0016 5.369
OP -2.286445 -4.155569 0.0043 5.737
FDI 0.488258 2.273716 0.0572 1.606
Adjusted R-Squared 0.734339
Durbin-Watson Stat 2.500920
F-Statistic 7.634075
Prob (F-Statistic) 0.009381
The above table consists of (Constant, discount rate, exchange rate, gross domestic
product, oil prices and foreign direct investment).

Adjusted R square elucidate the accurateness in the stock returns, that is
explain by the discount rate, exchange rate, gross domestic product, oil prices and
foreign direct investment. In the above model the value of Adjusted R square is
0.734339 which clarify that discount rate, exchange rate, gross domestic product, oil
prices and foreign direct investment can be estimated by 73.4339 % of the stock
market returns. It shows that we have decent model explaining around 73.4339 % of
stock returns in Pakistan. Durbin Watson demonstrates the auto-correlation in the
factors. It should range from 1.5 to 2.5. In the study, Durbin Watson is 2.5 which
indicate that there is no auto-correlation in our preferred variables.
Probability of F-Statistic symbolizes the importance of the model. Less than
0.05 probability value of F-Statistic clarify that discount rate, exchange rate, gross
domestic product, oil prices and foreign direct investment are the good predictor of
stock returns in Pakistan and that's why rejects the null hypothesis. Whereas, the
greater than 0.05 probability of F-Statistic value shows that discount rate, exchange
rate, gross domestic product, oil prices and foreign direct investment is not good
predictor of stock returns in Pakistan and accepts the null hypothesis. In our model,
the probability of F-Statistic is 0.009381 which is smaller number than 0.05 which
identify the independent variable of our model is good predictor of the dependent
variable.
SR= -2.947688+ 0.0741291ER+ 1.247192IR+ 1.418971GDP-2.286445OP+ 0.488258FDI
Constant value is -2.947688 that refer the Y intercept which explains that
those variables which might affect the stock returns and not considered in the study.
This means, if all variables are 0, so constant value is the estimated value of stock
returns.

Coefficient of discount rate is 1.247192 that shows that the one unit increase
in discount rate will cause a 1.247192 unit increase in stock returns in Pakistan. The
rationale of positive and significant relationship between discount rate and stock
returns is that the discount rate is used to control the inflation in the economy by the
Central Bank of Pakistan. When interest rate rises, it decreases the inflation which
enables people to buy more of goods and services. This impacts the firm’s cash flows
of the firm and result in higher stock returns. Another possible reason is that the
progress in the profit outlook boosts the cumulative demand and, therefore,
investment and, thus raises the interest rate.
Coefficient of exchange rate is 0.074129 that depicts one unit rise in exchange
rate will be caused a 0.074129 unit boost in stock returns in Pakistan. The cause of
positive and considerable relationship between exchange rate and stock returns in
Pakistan is; increasing exchange rate or depreciation in domestic money could
influence the export-oriented firms positively. The significant relationship between
exchange rate and stock prices signify the intensity of openness of stock market,
globally. As the local currency depreciated so the goods and services becomes
cheaper for the international market. So the international customers increase the
demand of goods and services produce in the country that helps to increase the profits
of the firms which enables them to give more dividend or in other words more stock
returns.
Coefficient of GDP is 1.418971 that means increase of one unit in GDP will
be caused a 1.418971unit raise in stock returns in Pakistan. The explanation of
positive relationship between GDP and stock returns in Pakistan is when the firms
produce more of goods and services it will increase the GDP of the country and the
firms can earn more profits which in turns increase the stock returns.

Coefficient of oil prices is -2.286445 that mean one unit increase in oil prices
will be caused a -2.286445 unit decrease in stock returns in Pakistan. The rationale of
negative relationship between oil prices and stock returns is that the cost of
production is directly associated with the oil prices in Pakistan as we are oil importing
nation and the increase in international oil prices will directly shifts the production
cost upwards and thus results in lowering profit. So the firm’s returns will be
negatively affected.
Coefficient of foreign direct investment is 0.488258 that mean one unit raise
in foreign direct investment will cause a 0.488258 unit raise in stock returns in
Pakistan. This may be rationale of positive relationship between foreign direct
investment and stock returns in Pakistan in which FDI increases the employment and
the public has more money to spend so they buy goods and services which helps the
firms to produce more and generate more profits which in turns increase their stock
returns.
The values of VIF of all variables in our model are less than 10 which mean
that there is no multi-co linearity issue in the model.

Chapter # 5
Conclusion and
Recommendations

5.1 Conclusion
In the current literature, the relationship among macroeconomic variables and
stock returns are studied by using regression model in the context of Pakistan. There
were five variables of the macroeconomic variables which are concerned in the study:
Discount Rate (DR), Exchange Rate (ER), Gross Domestic Product (GDP), Oil Prices
(OP), and Foreign Direct Investment (FDI). Data of macroeconomic variables are
collected from Index mundi and World Bank’s website for the period 1993 to 2012.
Whereas, Stock returns are calculated from KSE 100 index by percentage change
method.
Results indicate that DR, ER, GDP, and FDI have significant positive
relationship with stock returns. On the other side OP only the variable in the study
which shows significant negative relationship with the stock returns. The results of all
the variables are very much similar to the previous literature. As in empirical study
the findings of Zhu (2012) and Benakovic and Posedal (2010) about ER is positive
with the stock returns verifies the relationship found in our study however there were
authors Khalid et al. (2010) whose research findings shows negative relationship of
ER with the stock returns. If DR increases by it will impact positively on stock return.
The finding is similar to some previous studies of Benakovic and Posedal (2010) and
Ratanapakorn and Sharma (2007) while contrast with Chen et al. (2012), Khalid et al.
(2010) and (Haque & Sarwar, 2012). In similar way, if GDP rise then the stock
returns will behave positively. The results align with studies of (Haque & Sarwar,
2012), (Benakovic & Posedal, 2010) and (Ratanapakorn and Sharma, 2007). FDI has
also shown positive impact on the Stock Returns as in (Zafar, 2013). However, OP
indicates that if OP increases then the stock return will fall that show the significant
negative relationship. Hassan and Rifai (2012) ; Chen et al. also proved the significant

negative relationship of OP with stock returns but , (Benakovic & Posedal, 2010) and
(Hosseini et al. 2011) shows inverse case.
5.2 Recommendations
We suggest the following after analyzing the above study:
 It is found that stock returns are highly dependent on economic variables.
Such a mechanism should be adapted which helps to increase the benefit
of economic factors so the investor gets a higher return on their investment
and then they could re-invest in the economic cycle.
 If there is regular investment flow in the stock market, it will increase the
business activities. Such policies should be made which increase the
economic activities in the country which in turns raise the economic
development.
 The result indicates that GDP is the most considerable economic variable
to expect about the stock market returns. So the investor should carefully
examine the GDP rate of the country before investing in stock market for
better returns.
 The discount rate is also an influential variable on stock returns. If DR is
high the stock returns will also increase. So the investor should take the
risk to invest in the stock market rather than in commercial banks.
 Government should control the exchange rate, which is beneficial to the
export oriented companies which will lead to the high returns of their
stock.
 Another economic factor is FDI which has significantly positive impact on
stock returns, so the Government should take such steps which encourages

foreign companies to do FDI in the country, the law and order situation is
one the key influential factor in this regard.
 The companies should rely on other sources to generate energy rather than
oil only. This can reduce their cost of production and will lead to the
higher profit which in turns increase returns of their investors.
5.3 Future Recommendation
Some recommendations for further studies on this topic are as follows:
 The more economic variables like inflation, money supply, unemployment
rate and gold prices etc can be considered in the study which impacts stock
returns.
 The data of other market like Lahore stock exchange (LSE), Islamabad
stock exchange (ISE) can be included to get more definite results in
Pakistan.
 The further in depth analysis of this topic can be done through other
models like EGARCH, GARCH, ADRL, DBEKK, VAR and VECM etc.

Chapter # 6
Bibliography

ACKNOWLEDGEMENT
We are to be grateful for the small things in life, the bigger stuff just seems to
show up from unexpected sources, and we are constantly looking forward to each day
with all the surprises that keep coming my way! No metaphysician ever felt the
deficiency of language as much as the grateful. The first and the foremost gratitude go
to Allah Almighty- the omnipresent and omniscient for His countless blessings and
for providing us one now and then which in turn obliges us to thank Him again!
We are extremely grateful to our facilitator Nadeem Khan from whom we
found never ending support, assistance, amity and love. He always guided us through
thick and thin. We would like to appreciate our families and friends who did not leave
our side in all situations and proved to be our pillars of strength. We would like to
thank all the faculty members of Iqra University and our colleagues for providing us a
helping hand during our research project.
Last but not the least we would like to pay a deep gratitude to our university
for making us capable to do research work and get experience on this. With sincere
appreciation, we wish there should more academies like it.

TABLE OF CONTENTS
Acknowledgement ..........................................................................................................i
Abstract ......................................................................................................................... iv
Chapter # 1.....................................................................................................................1
1.1 Introduction..........................................................................................................2
1.2 Statement of problem...........................................................................................3
1.3 Research question ................................................................................................4
1.4 Objective of the study..........................................................................................4
1.5 Significance of the study......................................................................................4
1.6 Limitation and delimitation of the study..............................................................4
Chapter # 2.....................................................................................................................6
2.1 Theoretical background........................................................................................7
2.1.1 Financial market............................................................................................7
2.1.2 Primary versus secondary markets................................................................7
2.1.3 Stock market .................................................................................................7
2.1.4 Stock market returns .....................................................................................8
2.2 Empirical studies..................................................................................................8
Chapter # 3...................................................................................................................24
3.1 Research approach .............................................................................................25
3.2 Research purpose ...............................................................................................25
3.3 Research design..................................................................................................25
3.4 Data source.........................................................................................................25
3.5 Sample size and period ....................................................................................266
3.6 Statistical technique ...........................................................................................26
3.7 Model.................................................................................................................26
3.8 Model hypothesis ...............................................................................................26
3.9 Variable description.........................................................................................277

3.9.1 Stock returns ...............................................................................................27
3.9.2 Exchange rate..............................................................................................27
3.9.3 Interest rate..................................................................................................27
3.9.4 Gross domestic product...............................................................................27
3.9.5 Oil prices.....................................................................................................27
3.9.6 Foreign direct investment ...........................................................................27
Chapter # 4...................................................................................................................28
4.1 Introduction........................................................................................................29
4.2 Summary of Statistics ........................................................................................29
4.1.1 Parameter Estimation..................................................................................30
Chapter # 5...................................................................................................................34
5.1 Conclusion .........................................................................................................35
5.2 Recommendations..............................................................................................36
5.3 Future Recommendation....................................................................................37
Chapter # 6...................................................................................................................38
References

Abstract
This paper explores the relationship between Karachi Stock Exchange Index returns
and macroeconomic variables by analyzing the impact of macroeconomic variables on
stock market returns. For this purpose, the least square technique has been used in
regression analysis. The 20 observations time series data from 1993 to 2012 have
been analyzed and the finding shows Discount Rate, Exchange Rate, Gross Domestic
Product, and Foreign Direct Investment have a significant positive relationship, while
Oil Prices has significant negative relationship with stock returns. The results support
previous studies and hence it is concluded that these macroeconomic variable play an
integral part in predicting the returns of the stock market. So the investor and
controlling authorities should keep their eyes on these variables for better returns and
to establish the stable stock market returns respectively.
Keywords:
Karachi Stock Exchange, Stock returns, Macroeconomic variables, Regression
analysis

Impact of macroeconomic variables on stock returns

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