The Impact and Link of Macroeconomic Variables
on the Share Prices in UK
Introduction
Background
A remarkable literature exists on the investigation of
the impact of macroeconomic variable changes on the
stock market share prices. A number of models are
provided by the existing economic theory which
provides the framework to study the relationship
(Andreas and Peter, 2).
In the globally integrated world of today, access to
information is easier and universal. The efficient
market hypothesis theory depicts an efficient market to
be the one in which there is a rapid change in the share
prices as the new information is available.
A significant literature has explored the correlation
between the economic changes and macro economic
variables. For instance Asprem, Mads (609) has
studied the effect of changes in macroeconomic
variables on stock prices in ten European countries,
Nasseh, A liraza and Jack Strauss (229) researched
affect of domestic and international macroeconomic
variables on stock prices and Park, Jungwook and
Ronald A.
Ratti (2604) has studied effect of oil price shocks on
sock markets of US and 13 European countries. The
literature suggests that stock market indices are highly
sensitive to the changes in basic and main variables of
the economy (Pal, Karam, and Ruhee, 85).
Aim of study and Overview of Research Paper
An effective market is one wherein rapid adjustments
in the security prices take place to introduce latest
information. Hence, the information about the security
is reflected by the prices of securities. It means that it
is not easy for the new investors to predict the
movements of stock price quickly, in order to make
profit by trading the shares.
As for the macroeconomic economic variable effect,
for instance interest rate on stock prices and money
supply, the hypothesis of efficient market suggests that
the competition of profit maximizing investors ensures
that all the new information is well know and reflected
in stock prices, therefore the investors are not able to
make unusual profit by predicting the future movement
of stock market.
The presence of the co integrated relationship in stock
prices and macroeconomic variables brings the doubts
to efficient market hypothesis.
The behavior of stock market, principally, needs to be
predicted and policy makers may need to evaluate
again their economic policies if the variables affecting
the stock market are not what they desire (Maysami,
Lee, and Mohamad, 58).
The capital markets have to play very important role in
the financial sector of every economy and an efficient
capital market has capability to promote the prosperity
and growth of an economy by stabilizing its financial
sector and providing important investment channel to
contribute for the attraction for foreign and domestic
capital.
Efficiency of capital markets indicates the fact that
unanticipated part of the return on the security cannot
be predicted and is almost equivalent to zero over a
sufficient number of observations. Buyuksalvarci
stated that, “The unanticipated in the actual return less
what has been expected, based on the fundamental
analysis” (408).
Literature Review
A number of researchers have studied and estimated
the extent of effect of macroeconomic variables on
stock market share prices. Humpe, Andreas, and Peter
Macmillan (n. d) have compared the Japanese and US
stock markets, for understanding the long term
movements of the share prices, using monthly data of
40 years.
They have found, from the US data, a single so
integration vector among stock prices, inflation,
industrial production and long interest rate. The
coefficients of the single vector showed that the US
stock market share prices were positively impacted by
industrial production and negatively impacted by
lengthy inflation.
However, they found that there was insignificant
influence of the money supply on the stock prices. On
the other hand, they found two co integrating vectors
from Japanese data. One of the vectors was normalized
on the share price that gave evidence about the
industrial production and showed that it has positive
effect on the stock prices.
However, money supply was seen to have a negative
effect. They also have found for the second vector that
rate of inflation and interest rate has negative effect on
the industrial production (Pal, Karam, and Ruhee, 90).
The reason of the difference of stock market behavior
in the two countries is explained to be the result of
slump of Japan after 1990 and liquidity trap of the late
1990 and start of 21st century.
Gunsel, N. & Cukur, S. (140) have investigated the
Arbitrage Pricing Theory (APT) performance at
London Stock Exchange for the 1980-1993 period.
The study has developed seven various
macroeconomic variables that include the risk
premium, the term structure of interest rate, the money
supply, the exchange rate and unanticipated inflation.
In addition the authors have added the industry specific
variables such as sectoral unexpected production and
sectoral dividend yield and used OLS technique to
demonstrate that there were some major differences
among the industries.
The issue of serial correlation was discussed with the
help of Durban-Watson statistics, prior to the
demonstration of the OLS results. The study has found
that effective exchange rate is very important factor of
tradable industries. The results indicated that there is a
significant effect of the macroeconomic variables on
UK stock exchange, however each factor affects the
various industries in different ways.
Many researchers have studied the behavior of share
prices due to changes in macroeconomic variables.
Mohd Rosylin, Yousof, M. Sabri., and Ahmad Nazri
Razali (9) have analyzed the long run as well as short
run dynamics of macroeconomic variables and stock
markets. Moreover many other writers have researched
the same relationship with different stock markets and
have found strong relationship among various
macroeconomic variables and stock prices.
Tvaronaviciene Manuela, and Julija Michailova (213)
have argued that there is a strong influence of entirety
of factors on securities market, which could be roughly
be divided into different groups. The authors have
strived to review the theories of behavior of stock
prices, in order to show the complexity of the
phenomenon.
The authors have considered that different researchers
have presented controversial empirical evidences of
various factors that have impact on stock prices.
The authors have tried to test the relationships
practically. Statistical analysis has been performed
with the aim of evaluating quantitatively the stock
index dependence on some statistically measurable
factors.
For the purpose, the authors have employed various
factors, such as state budget revenue, foreign direct
investment, gross domestic product, money in the
broad sense, consumer products and services and
inflation, and stock prices
Ratanapakorn, Orawan, and Subhash, C. Sharma (9)
has analyzed the short as well as long term relationship
amongst six macroeconomic variables together with
UK stock price index between the/ years 1975 and
1999.
The scholars have observed that there is negative
impact of the long term interest rate on the stock
prices, while positive effect of industrial production,
exchange rate, global economic inflation and lastly,
short term interest rate.
According to the Granger causality, every change in
the macroeconomic variables has an impact on stock
prices only in the long run and not in the short run.
In addition, the results of the researchers’ study were
supported by the VDC. For instance, the stock prices
being exogenous with respect to other variables as
about 87% of its variance is caused by its own stock
even after 24 months.
Moreover, the treasury bills too showcased negative
effect, thereby indicating that with increase in the
interest rates on treasury securities, investors show
unanticipated tendency of switching out of stock that
lead to failure in stock prices.
Nevertheless, variables from lagged money supply did
not show strong predictions of stock price movement.
It had also been seen that stocks do not offer hedge
against inflation, especially in cases where trading,
manufacturing and other sectors of the stock exchange
are involved.
A similar study had been conducted by Antoniou
Antoniou, Lan Garret and Richard Priestley (221) ,
Garza-Garcia, J. G., and Vera-Juarez, M. E. (2) for
stock markets of Chili, Mexico and Brazil, Kandir, S.
Y. (39) with Turkish stock market, Rehman, A. A.,
Noor Zahira Mohd Sidek, and Fauziah Hanim Tafri
(102) with the case of Malaysian stock market. All of
them have found a significant relationship among
changes in macroeconomic variables and stock prices.
In their study Antoniou Antoniou, Lan Garret and
Richard Priestley (221) have investigated the APT
performance of securities traded in the London Stock
Exchange. They have also examined and demonstrated
the performance, when common factors are present
between two various specimens that indicate that that
an estimated structure is exhibited by return.
Compared to prior research conducted by several other
researchers in this domain, these scholars have
observed the possibility to conclude a distinctive
process of return generation. By this, they mean that
three factors directly related to inflation, money
supply, as well as excess return of stock markets have
been priced and thereby are associate with the similar
risk prices for the specimens.
Hardouvelis, G. A. (135) has analyzed the stock prices
response to the fifteen reprehensive macroeconomic
variables. There was strong response, according to the
results of study, from the monetary variable
announcement.
He also tried to argue that stocks belonging to financial
companies and institutions show greater sensitivity
towards monitory news. In essence, the stock price
reaction undoubtedly indicated that Federal Reserve
has a very crucial duty to fulfill in the overall
macroeconomic developments from futuristic point of
view.
Methodology
The research methodology that is chosen in order to
carry out the research is of utmost importance to the
accuracy of the results and on the level of reliability
that can be put to the results.
Another important aspect of research methodology, as
far as statistical projects are concerned is that incase
proper research methodology is not chosen and
executed, the research will not show and reach the
desired results and thus the entire research will become
meaningless.
Extra case has been taken concerning the above stated
facts and thus for the current research, the following
research methodology was chosen.
The variable chosen to carry out this research report
and to analyze the impact of macroeconomic variables
on the stock prices in the United Kingdom were,
SPM: The Stock Market Index as read by the
FTSE 100- Price Index
EX: The value of pound in exchnage of US
dollar to study the appreciation or the
depreciation of the currency in the region.
M1: The money supply as fixed by the central
bank.
TB: The rate of the United Kingdom Tresaury
Bill
IP: The industrial production capacity of the
United Kingdom’s economy in the given period.
CPI: The consumer price index to study the level
of inflation in the united kingdom’s economy in
a given period.
All of the chosen variables are important
macroeconomic variables which very strongly
determine the health of the economy overall. The point
of the each variable is explained as under:
The first variable, SPM is the dependant variable as
chosen in the time series software as Yt. This would
study the effect that changes in rest of the variable
have in the given period.
EX, studying the exchange rate of pound to dollar was
studying the value of the currency in respect of the
purchasing power parity.
Given that the pound depreciated in response to the
dollar, investors would shift their investment towards
the United States and thus the price of the shares as
measured by SPM will fall. Thus this variable is
hypothesized to have a positive relationship with the
Yt.
M1 is the money supply as fixed by central bank. This
is the first aggregate of money supply and the data is
gathered by a financial recorder. For the current
research study, the data was collected from a daily
newspaper’s financial section. M1 is hypothesized to
have a positive relationship with the price of stock,
SPM.
TB was the UK government’s Treasury bill and this
was hypothesized to have a negative relationship with
SPM because an increase in the rate of TB meant that
the investors are shifting their investments away from
FTSE-100 and towards the government bonds. The
lack of demand will cause the price of FTSE-100 to
fall in a given period of time.
IP is the production capacity of the industry of the
United Kingdom. This has a positive relationship with
the FTSE-100 because it sends out a positive signal to
the investors.
As mentioned above, CPI measures the inflation rate
and this is hypothesized to have a positive relationship
with the SPM because as the general price level in the
economy rises, the prices of goods sold by industry
rises and therefore there is more return to each
company.
The demand by inflation falls yes, by the return
increases more than the fall and thus there is a positive
hypothesized relationship. What the data finds out
however will be discussed in the empirical analysis
section.
Firstly, this methodology has been developed from an
extensive use of the software STATA, typically used to
analyze collected data. For the time series analysis of
data collected, STATA has been used for the
following:
To check whether Stationarity existed in the data
and this was found by
Unit root testing
In order to check for Stationarity in the data, Unit root
testing was carried, as has been mentioned above. The
expected results of the Unit Root test were stated using
hypothesis testing.
Ho: D=0 (The root present is unit and the data is not
stationary. The data has a stochastic trend present)
HA: D<0 (The root present is not unit and the data is
stationary. The data has a deterministic trend present)
Decision rule: If D<0, then reject the Null Hypothesis.
The rejection of Null hypothesis would further lead us
to the two things to consider:
1. Yt is stationary with a zero mean
2. Yt is stationary with a non zero mean
Such a hypothesis testing made is easier for me to state
and analyze the results of the time series. Moreover,
this was a more formal way of stating what was
expected out of the time series analysis of the data.
As studied in the module and as was required for the
above mentioned objectives, the following tests were
conducted in the software:
1. AUGMENTED DICKEY FULLER TEST
2. PHILLIPS PERRON TEST
3. KPSS TEST ( KWAITOWSKI PHILLIPS
SCHMIDTAND SHIN )
The second objective, after finding out the Stationarity
and the Unit Root through the time series software,
was to find out Co-Integration relationship amongst the
variables that were chosen for the research project. For
this purpose, the Co-integration Johansen Test was
carried out in STATA on the data collected.
Data Collection
The data has been collected from Data Stream which is
the database utilized in the university to collect the
data.
The macroeconomic variables analyzed are as follows:
1. SPM Stock Market Index FTSE 100 – PRICE
INDEX
2. EX Exchange Rate UK US $ TO 1
3. M1 (Money Supply). UK Money Supply M1
(Estimate of EMU Aggregate for the UK)
CURA
4. TB (UK Treasury Bill TENDER3M – Middle
Rate
5. IP = Industrial production a measure of the
productive capacity of the economy
6. CPI Consumer Index Price
Empirical Analysis
As mentioned in the research methodology section, the
data on the variables was collected by various means
and then was put through the time series software to
find out various trends in the data. The priority first
was to check out whether or not the data was stationary
and for that the Unit Root rest was conducted.
The reason for conducting the stationary test was to
find out and then be able to remove it from the data for
a better analysis.
The first Unit Root test was the Augmented Dickey
Fuller test:
Dfuller + l variable,lags() reg
This equation was used to check out for stationarity in
each of the variables. In this Reg stands for regression
in the variable. This test is used by adding a lagged
value of the depedant variable according to the criteria.
The number of the lagged variable that are included for
each test is determined in the basis of AKAIKE and
SCHWARZ informtion criteria.
For this, the optimal number of lags is one.
Results
Through finding out the optimal number of lags for
each variable and by conducting the test in STATA, it
is found out that none of the varibale are stationary.
This means that
H0 is not rejected and the value of the test statistic is
lower than the critical value. This means that that Ds is
not significantly greater than Dc at a 5% significance
level.
Because stationarity was not proven, first difference
was applied and through that the test statistic came out
to be larger than the critical value and so the null
hypothesis was rejected meaning that there was
stationarity in variables found.
The second test conducted to check for stationarity was
the Phillips Perron Test and the command for that was
the following:
Pperron L variable, reg
For each variable the result comes out to show that the
variables are not stationary. That means that the null
hypothesis is not rejected. Following these reults then
first difference need to be applied by using the
following command:
Pperron DL variable, reg
Results of the first Difference
The results of the first difference show that the variable
are stationary because the test statistics come out to be
higher than the critical values. This means that the null
hypothesis is rejected and the test statistic is
significantly negative at 5%.
The phillips Perron test satisfies the following
condition
H0 Yt I(1)
H1 Yt I(0)
The third test to check out the stationarity was the
KPSS test and command given for it was
KPSS + VARIABLE
Through this, the variable came out to be not stationary
and thus the first difference needed to be applied to the
variables. The commany for that was
KPSS D L + VARIABLE
Through the first difference, the variable came out be
stationary and the null hypothesis was rejected.
Th KPSS test satisfies the following condition
H0 Yt I(0)
H1 Yt I(1)
Conclusively, through the first difference of all the test,
it was founf that the variables are stationary.
The Co-Integration Test
For this, as mentioned by the research methodology
previously, the Co-Integration Johansen test was
carried out in STATA. The command for this was,
VECRANK + 1 Variable + 1 Variable + 1 Variable +1
Variable + ecc.
In this case, the trace statistic needs to be higher up to
the rank number of two. This menas that the variables
are cointegrated to the rank of 2 and that there are two
cointegrayion vectors.
The values are read of the Johansen S tables and the
null hypothesis are rejected because cointegration
significantly exists at 5% significance levels.
Furthermore, the test helps the researcher in analyzing
the long term relationship between the variables. It is
observed a long term equilibrium among the two
cointegrated variables exists.
Conclusion
Findings
Current study has analyzed the impact and relation of
UK share prices with macroeconomic variables. The
macroeconomic variables that have been studied for
their impact include, FTSE 100 – Price Index, Treasury
Bill UUK Treasury Bill Tender3M – Middle Rate,
Index of Industrial Production, Exchange rate (UK US
$ to 1) and Money Supply (UK money supply M1).
The data of the variables has been collected from Data
Stream of the university and analyzed using STATA
software. The Co-integration Johansson Test has been
applied to check the relationship among variables
(Rahman, 101).
The results show that in the long run, het share price is
affected by the changes in stock market price index.
Industrial production is related negatively to the share
price and is significant. It means that industrial
production index is procyclicality.
In addition an increase or decrease in the industrial
production will result in decrease or increase in the
index of the stock price of a particular company. The
long run relationship between Treasury bill is not
significant. It means, this variable is independent of
others, in the short run and do not effect significantly.
The share price of a company is significantly affected
by the stock market index in the long run that means
increase in the stock market index will lead to increase
in share price index of the company. In addition an
increase in industrial production will result in rise in
share price index of a company (Park, Jungwook and
Ronaldi, 2590).
Extensive research has been conducted for estimating
the relationship between macroeconomic variables
with respect to the price index across stock market.
Many researchers have studied the relationship for the
emerging economies, such as Gay, Robert, D (7). has
studied the effect of international macroeconomic
variable affect on the prices of stock markets of Russia,
India, China and Brazil and found no significant
relationship.
The results of the study were not unexpected as other
international and domestic macroeconomic variables
may also have important role in the stock market price
determination.
Limitations of the Research
The findings of the study have practical implications
for the stock market regulators, policy makers and
investors. However, there are limitations of the study
that may be overcome by other researchers. There is
need to add more macroeconomic variables to study
the impact on share prices.
In addition, there are certain measures that need to be
taken into account while making policy to influence
the economy.
In addition to this, limitations of the study encountered
during the work as the chosen lag length of the
augmented-dickey fuller analysis is very difficult and
Johnson and ADF methodology is very sensitive of the
choice of lag length. It is important for the other
studies to consider Autoregressive Distributive Lag
(ADRL) methodology of Pearson and Shin (1997).
Recommendations
The paper has examined teh relationship and impact of
macroeconomic variables on stock prices of UK. The
conclusion of the study was that the stock prices of UK
stock market have significant relationship with the
macroeconomic variables, used in the research. The
results of the study are beneficial for two basic reasons:
To explore if there is an opportunity of profit
from inefficiencies of stock market mechanism
in the transformation of information among
stock markets,
Is there a superior capability of earning with the
help of observing movemnt of stock prices and
To make policy recommendations for stock
prices of emerging economies.
The cointegration relationship between the stock prices
and macroeconoic variables bring the conclusion that
behavior of stock market may be predicted and policy
makers may have to reevaluate teh policy f affect on
the stock market is not somethiong that they desired.
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