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.

Topics in Macroeconomics Page 1

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.



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



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



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.



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

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 Std. Error t-Statistic Prob.

C 10.82212 0.392518 27.57100 0.0000

CALLRATE 17.21600 3.985814 4.319319 0.0005

CPI 4.292321 2.218016 1.935207 0.0698

DSC -34.28074 3.410811 -10.05061 0.0000

R-squared 0.888518 Mean dependent var 8.187221

Adjusted R-squared 0.868845 S.D. dependent var 0.981426

Variable Coefficient Std. Error t-Statistic Prob. C 10.74141 0.482401 22.26657 0.0000

CALLRATE 17.56293 4.251404 4.131090 0.0008

CPI 4.204230 2.297859 1.829629 0.0860

DSC -34.39341 3.524989 -9.757028 0.0000

M2GROWTH 0.467770 1.532866 0.305161 0.7642 R-squared 0.889163 Mean dependent var 8.187221

Adjusted R-squared 0.861454 S.D. dependent var 0.981426

S.E. of regression 0.365304 Akaike info criterion 1.028084

Sum squared resid 2.135155 Schwarz criterion 1.276780

Log likelihood -5.794884 Hannan-Quinn criter. 1.082058

F-statistic 32.08907 Durbin-Watson stat 1.271742

Prob(F-statistic) 0.000000



S.E. of regression 0.355427 Akaike info criterion 0.938649

Sum squared resid 2.147582 Schwarz criterion 1.137606

Log likelihood -5.855819 Hannan-Quinn criter. 0.981828

F-statistic 45.16367 Durbin-Watson stat 1.267745

Prob(F-statistic) 0.000000 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 0.744673 Prob. F(2,15) 0.4917

Obs*R-squared 1.896756 Prob. Chi-Square(2) 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 1.384501 Prob. F(3,17) 0.2815

Obs*R-squared 4.123362 Prob. Chi-Square(3) 0.2484

Scaled explained SS 4.813764 Prob. Chi-Square(3) 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 Prob.* Augmented Dickey-Fuller test statistic -3.871085 0.0378

Test critical values: 1% level -4.616209

5% level -3.710482

10% level -3.297799



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.



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

http://databank.worldbank.org/data/databases.aspx

http://www.ukm.my/penerbit/jurnal_pdf/Jp24-03.pdf

http://astro.temple.edu/~jjchoi/pub/JBF1992.pdf

http://www.ccsenet.org/journal/index.php/ijbm/article/view/217/0

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

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