Interest Rate, Inflation and NSS rate sensitivity on Stock Market – A case of Pakistan.

Institute of Business Management

Interest Rate,
Inflation and NSS rate
sensitivity on Stock
Market.
A Case of Pakistan – KSE100

Mehrose Amin – 11653
Shoaib Lalani – 11541
Ramshah Ahmed – 9172

Table of Contents
INTRODUCTION ............................................................................................................................................. 1
METHODOLOGY ............................................................................................................................................ 1
VARIABLES AND DATA SOURCE .................................................................................................................... 1
LITERATURE REVIEW ..................................................................................................................................... 2
Results:.......................................................................................................................................................... 5
Conclusion: .................................................................................................................................................... 7
Bibliography: ................................................................................................................................................. 8

Interest Rate, Inflation and NSS rate sensitivity on Stock Market.

INTRODUCTION
It is a long debated issue of interest rate sensitivity to stock market prices. The impact of interest
rate fluctuations on the stock prices has received a great deal of attention in the literature. Interest
rate changes are broadly recognized as a major source of uncertainty for investors. Extensive
research has been done in the past to examine and analyze the economic significance of interest
rate changes and its effect on stock market prices.
The results of these empirical research papers have played significant role in establishing
meaningful conclusions about relationship between interest rate sensitivity and stock market
prices all around the world, as the research conducted has been for many different countries
around the globe to make the results more reliable.
This research paper examines the causal relationship between interest rate sensitivity on stock
market prices in case of Pakistan. The dependent variable in this study is the KSE-100 Index and
the independent variables are M2 growth, CPI (Consumer Price Index), Call rate (short term
interest rate), and DSC (Defense Saving Certificate rate). The data has been gathered from the
year 1992 to 2012 and the source of data compilation is the World Bank and State Bank of
Pakistan.

METHODOLOGY
The methodology used in this research paper to examine the effect of interest rate sensitivity on
stock prices is linear regression model. A series of tests were run on the data to check the
reliability and authenticity of the data itself. First, test for multicollinearity was run to check if
the explanatory variables are highly correlated or not. Test for hetroskedasticity was run
followed by Autocorrelation test to check homoskedasticity and correlation of the variables
respectively. ADF (Augmented Dickey Fuller test) test is finally applied on the data to check the
stationarity of the data.

VARIABLES AND DATA SOURCE
The data has been gathered from the World Bank and data examined in this study is from 1992
till 2012. The independent variables are of a critical significance and need to be defined in depth.




CALL RATE (Short-term interest rates) – or overnight rate is the rate that banks use
to borrow from and lend money to each other. It is a bench mark rate used to determine
the long term interest rate and is used by State Bank of Pakistan to influence the
monetary policy.
CPI (inflation) – theoretically, is a measure that examines the weighted average price of
a basket of consumer goods and services, such as food, transportation and medical care.

Topics in Macroeconomics

Page 1

CPI is calculated by taking price changes for each item in the predetermined basket of
goods and averaging them. Changes in CPI are used to assess price changes associated
with cost of living.
Inflation is too much money chasing too few goods. Most studies conclude that expected
inflation can either positively or negatively affect the stock prices, depending on ability to
hedge and government’s monetary policy. However unexpected inflation has a strong
positive correlation to stock returns during economic contractions. The data on inflation
rate in Pakistan has been taken in this case.


LNKSE-100 - KSE-100 is the stock index used to compare prices on Karachi Stock
Exchange. It is illustrated to tell the investors how is the KSE performing over a
particular period. It is derived by calculating market capitalization and dividing it from
the previous base. Log of KSE-100 index have been taken to reduce the error from the
variable as the heavy fluctuation in KSE-100 causes it to disperse from its mean.



M2 Growth (money supply)
M2 = M1 + time deposits + resident’s foreign currency deposits
There is a common assumption that if the stock market was efficient, it would have
already incorporated all the current and anticipated changes in money supply. Previous
studies have shown that stock market is not efficient with respect to money supply.
However, some studies also establish a long run relation between money supply and
stock prices on basis of cointegration test analysis.



DSC (Defence Saving Certificate rate) - DSC can be taken instead of long term interest
rate. It is the return on the long term government securities in Pakistan. The long term
interest rate is taken on the basis (on the benchmark) of the short term interest rate and is
mostly on the tenure of a longer term (more than 1 year, usually 10 years).

LITERATURE REVIEW
The relation between interest Rate and Stock Price (Empirical evidence from developed and
developing countries by Mohammed Alam and MD. Ghazi salah Uddin.); the report is published
by International Journal of Business Management vol 4. The data gathered is of 15 developed
and developing countries and is gathered for the year Jan 1988 to March 2003. The dependant
variable is return on stock/share price and change in ROE; the independent variables are interest
rate and change in interest rate. The methodology used in this study is time and panel series
approach regression model. The result show that for all countries it is found that changes of
interest rate has significant negative relationship with changes of share price. The
recommendation in this case study is that if the interest rate is considerably controlled in these


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countries, it will be the great benefit for their stock exchange through demand pull way of more
investor in share market, and supply push way of more extensional investment of companies.
Relationship between macroeconomic variables and stock market indices (cointegration
evidence from stock exchange of Singapore’s All-sector indices). This article is by Ramin Cooper
Maysami, LEee Chuin Howe and Mohammed Sktin Hamzah (2004). This article was published in
the Journal Pengurunsan. The data on M2 growth and short term interest rate was taken from the
year of January 1989 to December 2001. The dependent variables are SGX and SES. The
independent variables are inflation, growth, long term and short term interest rate and M2
growth. The methodology used in this study was Engle and Granger test and Johansen and
Juselius test to test the causal relationship between the dependent and independent variables. The
results showed that short term interest rates have positive relation with stock indices while the
long term interest rate has a negative relation. Policy makers should be careful while deciding to
control economic indicators by macroeconomic variables such as money supply and interest rate.
Moreover, different macroeconomic variables have different relation with stock indices, so
priority of the government is a main factor they might choose to control one thing while leaving
other for opportunity cost.
The sensitivity of Bank stock returns to market, Interest and exchange rate risks. This article is
written by Joongmoo Jay Choi, Elyas Elyasiani and Keneth J. Kopecky written in the year 1992.
This article was published in Journal of Banking and finance 16 (North Holland). The data for
returns on stock and interest rate has been taken for the year Jan 1975 to Dec 1987. The testing
methodology used was multiple factor model to describe returns on the back stock. The results
showed that stock prices react in the opposite way towards the change in interest rate. While
exchange rate innovations had first negative relation with the stock prices in early years of data,
and later had positive relation with the latter. A micro model of an international banking firm
was also presented to provide protections of the sign of coefficients of the unexpected
components of market, interest and exchange rate variables.
The interest Rates-stock prices nexus in highly volatile markets: Evidence from Pakistan. This
article is written by Attaullah shah, Jamil Ur Rehman, Yasir Kamal and the source of this article
is Journal of Basic and Applied Scientific Research, 2012. The data is KSE-100 index from 2007
to 2010. The dependant variable is stock prices and the independent variable is interest rate. The
methodology used in this study is the ADF test for unit root and Johensan cointegration test, and
VAR-based granger causality test. The results of the study reveal that VAR-based granger
causality test shows that stock prices do not granger cause interest rate but interest rate does
granger cause stock prices. Cointegration test for long run relationship showed that interest rates
and stock prices have no long run relationship.
Economic forces and the stock Market by Nai-Fu Chen, Richard Roll and Stephen A. Ross is
taken from the source, The journal of Business Vol 59, written in 1986. The data has been
gathered for the years of 1958-1978. The dependent variable is the stock market prices and is the
independent variable is the spread between short-term and long-term interest rates and
unexpected inflation, spread between high and low grade bonds. The methodology used is
multivariate regression. The results of the study reveal that negative risk premium indicates
that’s stocks whose returns are inversely related to increases in long rates over short rates are

Page 3

more valuable. This paper has explored a set of economic state variables as systematic influences
on stock market returns and has examined their influences on stock market returns and has
examined their influence on asset pricing. Several of these economic variables were found to be
significant in explaining expected stock returns, especially industrial production, changes in risk
premium, twists in yield curve and measures of unanticipated inflation during periods when these
variables were highly volatile.
The Relation between stock prices and Inflationary Expectations: The international Evidence by
BRUNO SOLNIK. The source of this journal is The Journal of Finance, Vol XXXVIII. The data
has been gathered for 9 countries over a period of 1971-1980. The dependant variable is Real
Return on Asset and the independent variables are inflation rate and expected inflation rate. The
methodology used is Fisher Framework, regression. The results for the US confirm the previous
findings of a significant negative relation between asset returns and inflationary expectations.
The coefficient of expected inflation is negative for all countries except Canada and is
significantly different from zero for Japan, Switzerland and Belgium. The recommendation of
this study is that without deciding on the “causality” direction, the link between inflation and
stock returns appears to be through inflationary expectations and more specifically revisions in
expectations.
Impact of Short-term Interest Rate on stock prices by Zhang Chutang and Emil Sudath Kumara.
The source of the article is school of management, Wuhan university of Technology, China. The
data gathered is of 91 days, 182 days, and 364 days T-bills on stock prices. The dependant
variable is stock prices and the independent variable is short term interest rates. The
methodology used is Multiple regression Analysis in which ADF test is used, test of
autocorrelation and multicollinearity test. The results of the study reveal that there is weak
relation between short-term interest rates and stock prices of Sri Lanka and correlation between
364 T-bill rate and stock prices indicates a negative relationship. Granger Causality test reveals
the existence of causality between 364 days t-bill rates and stock prices.


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Results:
To test the sensitivity of interest rate, inflation, and defense saving rate on stock market. The
equation that we used to test our hypothesis is
LNKSE = α + α1CALLRATE + α2CPI + α3DSC + α3M2Growth + μ
Variable

Coefficient

Std. Error

t-Statistic

Prob.

C
CALLRATE
CPI
DSC
M2GROWTH

10.74141
17.56293
4.204230
-34.39341
0.467770

0.482401
4.251404
2.297859
3.524989
1.532866

22.26657
4.131090
1.829629
-9.757028
0.305161

0.0000
0.0008
0.0860
0.0000
0.7642

R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)

0.889163
0.861454
0.365304
2.135155
-5.794884
32.08907
0.000000

Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat

8.187221
0.981426
1.028084
1.276780
1.082058
1.271742

At 10% significance level, call rate, cpi and dsc have a significant relationship with lnkse.
However, result shows that M2 growth is highly insignificant with LNKSE. All together they
vary 86 times together and F-stats show that overall the model is significant. We believe that the
insignificance of m2 growth is led due to multi collinearity. Changes in call rate have direct
impact on money supply therefore we dropped m2growth from our model. The new regression
equation and analysis are as follow.
LNKSE = 10.82 + 17.21 CALLRATE + 4.29 CPI + (-34.28) DSC + μ

Dependent Variable: LNKSE100
Sample: 1992 2012
Variable
Coefficient
C
CALLRATE
CPI
DSC
R-squared
Adjusted R-squared


10.82212
17.21600
4.292321
-34.28074
0.888518
0.868845

Std. Error

t-Statistic

Prob.

0.392518
3.985814
2.218016
3.410811

27.57100
4.319319
1.935207
-10.05061

0.0000
0.0005
0.0698
0.0000

Mean dependent var
S.D. dependent var

8.187221
0.981426

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S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)

0.355427
2.147582
-5.855819
45.16367
0.000000

Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat

0.938649
1.137606
0.981828
1.267745

Standard error of call rate, cpi and DSC decreased after dropping M2 growth from the model.
However the Durbin-Watson stat shows that there is an uncertainty about the presence of
positive auto correlation in the model. To test for auto correlation we used Breusch-Godfrey
Serial Correlation LM Test.
H0: There is no Auto-Correlation
Breusch-Godfrey Serial Correlation LM Test:
F-statistic
Obs*R-squared

0.744673
1.896756

Prob. F(2,15)
Prob. Chi-Square(2)

0.4917
0.3874

There is no significant evidence to conclude that there is a chance of serial auto correlation in the
model. The probability of F stats is more than 10%; therefore, there is strong evidence which
suggest that there is no serial auto correlation found in the model.
To test the equal variance among the error term we used Breusch-Pagan-Godfrey test to check
for hetroscedasticity in the model.
H0: The data is homoscedastic
Heteroskedasticity Test: Breusch-Pagan-Godfrey
F-statistic
Obs*R-squared
Scaled explained SS

1.384501
4.123362
4.813764

Prob. F(3,17)
Prob. Chi-Square(3)
Prob. Chi-Square(3)

0.2815
0.2484
0.1860

The probability of F stats of Breusch Pagan is more than 10% therefore we failed to reject our
null hypothesis and conclude that there is equal variance among error term and our model is
homoscedastic.
Null Hypothesis: LNKSE has a unit root
Exogenous: Constant, Linear Trend
Lag Length: 3 (Automatic based on SIC, MAXLAG=3)
t-Statistic
Augmented Dickey-Fuller test statistic
Test critical values:
1% level
5% level
10% level


Prob.*

-3.871085
-4.616209
-3.710482
-3.297799

0.0378

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Generally, Pakistani the stock market follows an upward trend so we believe that there is a
chance of trend stationary of our data. We ran Unit root test and at 5% significance level we
found our data stationary after3 lags.

Conclusion:
After a series of test, we concluded that the data was reliable and authentic for our results to be based
upon.
When all the factors are zero, natural log form of KSE 100 is 10.82. Keeping other factors constant a one
percent increase in call rate would bring a relative change in natural log form of KSE 100 by 17.21. A one
percent change in CPI will change LN KSE relatively by 4.29. With one percent growth in DSC, LNKSE will
relatively fall by 34.28.
Our results contradict the economic theory too. The economic theory suggests that short term interest
rates are the bench mark to the financial sector and with the increase in call rates would bring down the
stock prices and hence the KSE100 index. However in Pakistan companies shift their increase in finance
cost on the consumers. Therefore, their profit margin remains same and does not affect the stock prices
significantly.
In Pakistan, DSC is an alternative investment opportunity for the general public due to lack of awareness
amongst them regarding the financial sector and what returns it brings to them. So with an increase in
the long term interest rate, people shift their savings to DSCs, which in turn reduces the investment
opportunity in the stock market. As people assume that there is probably no default risk when
investing in a government security.


Page 7


Bibliography:
http://databank.worldbank.org/data/databases.aspx
http://sbp.org.pk/
www.ukm.my/penerbit/jurnal_pdf/Jp24-03.pdf
http://astro.temple.edu/~jjchoi/pub/JBF1992.pdf
http://rady.ucsd.edu/faculty/directory/valkanov/pub/classes/mfe/docs/ChenRollRoss_JB_1986.pdf
http://www.ccsenet.org/journal/index.php/ijbm/article/view/217/0


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Interest Rate, Inflation and NSS rate sensitivity on Stock Market – A case of Pakistan.

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