The Effect Of Macroeconomic Information Finance Essay - Free Essay Example

In this study, we examined some peculiarities or differences between selected macroeconomic variables and the UK FTSE All Share Index. The secondary data used in this study are monthly FTSE All Share index of London Stock Exchange and selected macroeconomic variables, including consumer price index, industrial production index and average earnings index (whole economy) between January 2000 and October 2009. The economic data were collected from Office of National Statistics while FTSE All Share Index from Yahoo! Finance which covers a period between January 2000 and October 2009. To measure the effect of macroeconomic information on UK FTSE All Share Index, I will utilize multiple regression analysis. In general, stock market is affected by macroeconomic information. INTRODUCTION Economic factor has been attributed to be the cause of stock market movement (Fama 1981). In same vein, the stock market is a common feature of an economic growth and it is reputed to perform some necessary functions, which promote the growth and development of the economy. Stock market returns shows an efficient market hypothesis (EMH), Fama (1991). Fama argues that stock prices do not show a strong form nor weak form but rather semi-strong form efficiency. This means that stock price movement must reflect all publicly available information and not fundamental or technical analysis about the security. Athanasios and Antonios (2009) are of the same view with Famas hypothesis affirming that the negative relationship between stock returns and inflation reflects positive impact of real variables on stock returns. The link between stock market performance and economic growth has complemented this hypothesis among analysts based on their study of developed and emerging markets. Chong and Goh (2005) emphasize the importance of macroeconomic variables as relating to investors earning abnormal profit returns. Geske and Roll (1983) and Kaul (1987) emphasize the importance of policy responses in explaining stock returns. The determination of the overall growth of an economy depends on how efficiently the stock market performs its allocative functions of capital (Tokunbo n.d). As the stock market mobilizes savings, concurrently it allocates a larger proportion of it to the firms with relatively high prospects as indicated by its rate of returns and level of risk. The importance of this function is that capital resources are channelled by the mechanism of the forces of demand and supply to those firms with relatively high and increasing productivity thus enhancing economic expansion and growth (Alile, 1997). However, stock markets play an important role in stimulating economic growth. The FTSE All-Share Index is a market-capitalisation weighted index comprising of over 600 companies listed on the London Stock Exchanges main market. The index base date is 10 April 1962 with a base level of 100. The FTSE All-Share Index is considered to be the best performance measure of the overall London equity market with the vast majority of UK-focused money invested in funds which track it. According to FTSE report 2008, the FTSE All-Share Index accounts for 8.11% of the worlds equity market capitalisation. 1.1 RATIONALE OF THE STUDY A great deal of research has been conducted in the developed market (US, UK, Australia, Belgium, France etc) and in emerging markets (India, Nigeria, Russia etc) as regards the relationships between macroeconomic variables and stock market returns. Nil Gnsel and Sadk ukur (2007) examined the effect of economic variables on London Stock Exchange but with a different approach, different methods and different time period covering 1980-1993. They found out that macroeconomic factors have a significant effect in the UK stock exchange market. Also, in the emerging markets, Tokunbo (n.d) examined the case of Nigerian Stock Exchange and came out with a conclusion that there is a positive relationship between growth and all the stock market development variables. However, my empirical studies will focus on selected macroeconomic variables as well as the time period different from the one used by the above researchers. This will be distinguishable by testing the effect of Average Earnings Index (excluding arrears and bonuses) on stock market index. 1.2 AIMS AND OBJECTIVES The relationship between economic growth and stock market has been the subject of intensive theoretical and empirical studies (James Laurenceson, 2002). The question is whether stock market development causes economic growth or reversely. The main objective of this study is to empirically examine some peculiarities or differences that exist between selected macroeconomic information (especially Average Earnings Index) and stock market index, a case study of FTSE All Share Index using regression analysis. The study covers for the period of January 2000- October 2009. 1.3 RESEARCH QUESTIONS The following research question will form the core of empirical investigation of studies. Do, index of industrial production, Average Earnings Index, and Composite Consumer Price Index affect FTSE All Share Index? If, yes to what extent? This will be proved or shown empirically via correlation and regression model. We would like to know if there is relationship among the economic variables used. 2.0 LITERATURE REVIEW Recent empirical study has found quantitative evidence relating stock market to the secular bull and bear cycles, their patterns of returns and volatility, and the relationships between the market and the economy. The stock market is perceived as an indicator to mirror the economy through which long-term funds mobilization are provided (Inanga and Emenuga, 1997). The link between stock market and key economic variables in developed and emerging market is well documented. The link can be attributed to research of Christopher Gan et al. (2006), Arestis Demetriades (1997), Robert D. Gay, Jr (2008), Taufiq Choudhry (1999), Chen, Roll and Ross (1986), Stijn Van Nieuwerburgh et al. (2005), Athanasios and Antonios (2009), and Priestly (1996) in which their studies identified the relationship between stock market returns and macroeconomic factors in terms of production rates, productivity, GDP growth rate, unemployment, inflation rate, exchange rate, money supply, etc. Christopher Gan et al. (2006) examined whether the New Zealand Stock Index(NZSE40) is cointegrated with a group of macroeconomic variables (the inflation rate, long term interest rate, short term interest rate , exchange rate index , GDP, money supply (M1) and domestic retail oil prices) in the long run. They affirmed that the NZSE40 is majorly determined by the interest rate, money supply and real GDP and no strong evidence for the stock market index to be a leading indicator for changes in macroeconomic variables. In a similar context, Arestis Demetriades (1997, p.785-790) concluded that the relationship between stock markets and economic development in the US was largely positive but insignificant in the case of Germany. Robert D. Gay, Jr (2008) investigated the Brazil, Russia, India and China (BRIC) stock market and the linkage with two macroeconomic variables (exchange rate and oil price). It was evidenced that there exist relationship between exchange rates and stock prices for Brazil, India, and China but not for Russia. The other economic variable, oil price do not show a significant relationship between the three stock market exchanges. Priestley (1996) suggested the factors that may carry a risk premium in the UK stock market with seven macroeconomic and financial factors (default risk, industrial production, exchange rate, retail sales, money supply unexpected inflation, change in expected inflation, terms structure of interest rates, commodity prices and market portfolio). Taufiq Choudhry (2001) investigates how stock market in four high inflation countries reacts to inflationary pressure. The countries he investigated were Argentina, Mexico, Venezuela and Chile during the 80s and 90s. The results show that past and present inflation has relationship with the current stock returns and there is inverse relationship with one-period lagged inflation. Poon and Taylor (1991) reflect their study on the United Kingdom stock market using ARIMA model. It was affirmed that macroeconomic variables strongly affect stock returns in USA than in UK. Their findings were related to Chen, Roll and Ross (1986) and reemphasize the importance of representing only the unexpected component of share returns and macroeconomic variables. However, effort was also made by Stijn Van Nieuwerburgh et al. (2005) with the view of Institutional changes affecting the stock exchange explain the time-varying nature of the link between stock market development and economic growth. He studied to what extent macroeconomic factors could affect stock market changes in Belgium for a period between 1873 and 1935 using Granger Causality tests. Athanasios and Antonios (2009) used four different approaches to examine the causal relationship between stock market development and economic growth, a case study of France for the period 1965-2007. The methods are (1) unit root test: to examine stationary (2) Johansen co-integration analysis: to examine whether the variables are co-integrated of the same order (3) A vector error correction: to investigate the long-run relationship between stock market development and economic growth (4) Granger causality: to examine the direction of causality between the examined variables of the estimated mode l. They concluded that A short-run increase economic growth of per 1% leaded to an increase of stock market index per 0.24% in France, while an increase of interest rate per 1% leaded to a decrease of stock market index per 0.64% in France It is so glaring that research has been conducted to find what set of relationship could exist between stock market return and macroeconomic variables. Different approaches were used, from granger causality, johansen co-integration, regression analysis etc and different economic factors; inflation rate, production index, export and import indices, money supply, unemployment rate etc to reflect the relationships. Our study is to use a multiple regression analysis and review what other researchers has done about macroeconomic influence on stock market. 3.0 DATA AND METHODOLOGY To examine the effect of macroeconomic variables on stock market movement, we use monthly return data for the period January 2000 to October 2009 (118 observations) for all variables. The data used can be categorized into dependent and explanatory variables. Dependent Variable FTSE All Share Index- The data used is the monthly figure of FTSE All Share Index (a market-capitalization weighted index), an aggregation of the FTSE 100 Index, FTSE 250 Index and FTSE SmallCap Index listed on the London Stock Exchanges main market. Explanatory Variables: Index of Production CPI Inflation Average Earnings Index (whole economy, excluding payment of arrears and bonuses) Index of Production (IoP) is measured at base year prices (2000). The index measures the volume of industrial production (manufacturing, mining and quarrying, and energy supply industries). According to Office of National Statistics, IoP is used as- short-term economic indicator; a component of the production or output measure of GDP; and a requirement for the Statistical Offices of the European Community (Eurostat). CPI Inflation is a measure estimating the average price of consumer goods and services purchased by households. The percent change in the CPI is UK measure of inflation for macroeconomic purposes and forms the basis for the Governments inflation target. Average Earnings Index (whole economy, excluding payment of arrears and bonuses) measures the growth of earnings in UK economy. The index measures how earnings in the latest month compare with those for the last base year (2000). According to Office of National Statistics, average earnings are obtained by dividing the total amount paid by the total number of employees paid, including those employees on strike and temporarily absent. 3.1 SOURCES OF DATA The data used in this study is monthly data from January 2000 to October 2009. Data for the Industrial Production Index, Consumer Price Index, and Average Earnings Index were obtained from Office of National Statistics while data for the FTSE All Share Index was obtained from Yahoo! Finance. 3.2 METHODOLOGY In this study we examine the relationship between the dependent and explanatory variables using regression analysis. Regression analysis helps us understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. The method to be performed is outlined below: Scatter plots Estimated regression model Significance testing of the variable Estimating the coefficient of multiple determination Scatter Plots The diagnostic plot for multiple regression is a scatter plot of the residuals, against the predicted values . We use this plot to see the nature of relationship that exist and if the predictions can be improved by identifying outliers, transformation of predictors to achieve linearity, and unequal variability Estimated Regression Model We considered three explanatory variables; Index of Production (, CPI Inflation, and Average Earnings Index to be investigated for their relationship with a response variable FTSE All Share Index returns model as follows: This holds for the population of the values of response and explanatory variables. Where called regression coefficients of the explanatory variables while ÂÂ µ is the error term that assumed normal distribution (ÂÂ µ) with mean, 0 and standard deviation, . We will therefore need to fit a regression line through the observations of the sample (Koutsoyiannis, 1977). The estimated regression lines thus: Where are the estimates of respectively. The regression coefficients of the explanatory variables (Index of production, CPI Inflation and Average Earnings Index) quantify the amount of the response variable (FTSE All Share Index return). Testing the response variable and Regression Coefficients We used student t-test to examine if explanatory variables are significant predictor of the response variable. The t-statistics is given as: Where is given as: is the hypothesised value, K is the number of parameters and n is the number of sample observation. Then we set the hypothesis: If the hypothesised value, then the testing amounts to deciding if the explanatory variables are a significant predictor of the response variable. However, in testing the overall significance of the regression we set the hypothesis: This test aims at finding out whether the explanatory variables do actually have any significant influence on the response variable. The easiest way to reach a decision is by means of p-values. A p-value less than 5% suggests that the estimated model is significant. Estimating coefficient of multiple determination The coefficient of multiple determination (denoted by ), in the four variable-model shows the percentage of the total variation of the response variable, Y that is explained by changes in the explanatory variables, . Therefore: The value of lies between 0 and 1. The higher the greater the percentage of the variation of response variable (the better the goodness of fit) explained by the regression plane (Koutsoyiannis 2003). 4.0 ANALYSIS OF THE RESULT The results that were obtained after running the data through Microsoft Excel 2007 are as follows: The value of R (Correlation coefficient) obtained for our data is approximately 0.72 which lies between 0 and 1 indicating a positive relationship between stock market index (FTSE All Share Index) and the selected macroeconomic variable (index of production, Inflation and average earnings index). Coefficient of multiple determination () for our data is approximately 0.52 which indicates that the model fit the data. Also, the Adjusted which represents a somewhat reduced value of indicates that 52% of the total variation in FTSE All Share Index is due to CPI Inflation, Index of Production and Average earnings index. The estimated regression model becomes; Where: FASI- FTSE All Share Index IoP- Index of Production CPI- CPI Index AEI- Average Earnings Index The results suggest that at 0.05 and 0.01 level of significance comparing with , there is a significant relationship between the FTSE All Share Index and all the macroeconomic variables (Index of Production, CPI Index, and Average Earnings Index) used. We use Pearsons correlation coefficient as a measure of correlation. The results suggest that there is a weak positive correlation between FTSE All Share Index and the macroeconomic variables (Index of Production, CPI Index, and Average Earnings Index) used. However, among the macroeconomic variables, there is a strong positive relationship between Average Earnings Index and CPI Index. There exist strong negative relationship between CPI Index and Index of Production, and between Average Earnings Index and Index of Production. 5.0 CONCLUSION We have been able to answer the research questions base on the empirical analysis conducted on the data. We found that there exists a significant and a weak positive relationship between FTSE All Share Index and the selected macroeconomic variables (Index of Production, CPI index and Average Earnings Index). Also we were able to show that; An increase (decrease) in CPI Index should lead to Increase (decrease) in Average Earnings Index. Decrease (increase) in Index of Production Also, an Increase (decrease) in Average Earnings Index should lead to decrease (increase) in Index of Production. However, Chen et al. (1986), Christopher Gan et al. (2006) and Athanasios Vazakidis and Antonios Adamopoulos (2009) have suggested a negative relation between stock returns and inflation which is contrary with our findings suggesting a positive relationship between FTSE All Share Index and CPI Index. Our study support research conducted by Chen et al. (1986) and Thornton (1993) on the relationship that exists between Stock market and real economic activity. Index of Production is one of the measures of real economic activity. Thornton studied the UK market and concluded that a stock return is being affected by real economic activity. The relationship among industrial production, interest rates and the SP 500 Index seem to suggest that the interrelationships among the three variables are insignificant (Mallaris and Urrutia, 1991). Therefore, it can be concluded that there exist relationship between stock market and macroeconomic variables. APPENDIX