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:
- Yt is stationary with a zero mean
- 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:
- AUGMENTED DICKEY FULLER TEST
- PHILLIPS PERRON TEST
- 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:
- SPM Stock Market Index FTSE 100 – PRICE INDEX
- EX Exchange Rate UK US $ TO 1
- M1 (Money Supply). UK Money Supply M1 (Estimate of EMU Aggregate for the UK) CURA
- TB (UK Treasury Bill TENDER3M – Middle Rate
- IP = Industrial production a measure of the productive capacity of the economy
- 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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