Effect Of Economic Factors On FTSE100 Stock Prices
It’s believed that an economic atmosphere is a major factor in determining the primary trend of a stock market. L H Beng (1998)The stock market, on the other hand, is often regarded as an effective and a reliable barometer of a country’s economy, and the stock prices are deemed as a reflection of future expectations concerning the economic well being of a country. Invariably, Stock, by its very nature, cannot be seen off as an independent entity from economic realities and performance. Consequently, it is of great interest to find out or examine the relationship between some economic variables and the pricing of stocks in the London stock exchange.
This empirical study is carried out to examine the effect of economic factors on stock price with reference to FTSE100 price index of London stock Exchange. The main objective of the study is to examine some peculiarities or differences in terms of economic variables that influence stock prices in the London stock market. The effects of retail sales index, consumer price index and industrial production index (IPI) on stock prices shall be duly examined.
The study makes use of regression model to analyze nine year (Jan. 2000 – Nov. 2009) monthly data obtained on ftse100 price index and some identified explanatory variables among other numerous variables that could be identified to determine stock prices in any economy.
Series of empirical studies have been carried out on the effect or influence of economic variables on the stock price. P I Ojeaga & V O Folajin (2009) showed in their study that stock price correlated with the price of industrial product and composite price index, also strongly related to the average naira dollar exchange, market capitalization, broad money supply and maximum lending rate in Nigeria economy.
N F Chen, R Roll & S A Ross (1986) argued that stock returns are exposed to systematic economic news, that they are priced in accordance with their exposures and that the news can be measured as innovations in state variables whose identification can be accomplished through simple and intuitive financial theory. The study was carried out with the use of efficient market theory and rational expectations inter temporal asset-pricing theory (Cox et al 1985). According to the study, industrial production and changes in risk premium have a great influence on the stock returns while index of oil price changes showed no effect on the asset pricing.
Abeyratna G, Anirut P and David M P (2004) displayed empirically in their study that there is a long run equilibrium relationship between the stock prices and the rate of inflation, the money supply and the Treasury bill rate in an emerging market of South Asia.
Mukherjee and Naka (1995) applied Johansen’s (1998) VECM to analyze the relationship between the Japanese Stock Market and exchange rate, inflation, money supply, real economic activity, long-term government bond rate, and call money rate. They concluded that a co integrating relation indeed existed and that stock prices contributed to this relation.
R C Maysami, L C Howe and M A Hamzah (2004) concluded in their research study that Singapore stock market and the SES All-S Equities Property Index formed significant relationships with all macroeconomic variables identified, while the SES All-S Equities Finance Index and SES All-S Equities Hotel Index form significant relationships only with selected variables. Specifically, for the SES All-S Equities Finance Index, real economic activity and money supply were not significant, and in the case of SES All-S Equities Hotel Index, money supply, and short- and long-term interest rates were insignificant.
Omran (2003) examined the impact of real interest rates as a key factor in the performance of the Egyptian stock market, both in terms of market activity and liquidity. The co integration analysis through error correction mechanisms (ECM) indicated significant long-run and short-run relationships between the variables, implying that real interest rates had an impact upon stock market performance.
Maysami and Koh(2000) studied and found out that inflation, money supply growth, changes in short- and long-term interest rate and variations in exchange rate formed a co-integrating relation with changes in Singapore’s stock market levels.
As revealed above, two variables (index of industrial production and consumer price index) out three highlighted variables have been tested by earlier researchers and the results showed a clear relationship with stock prices. In this study, the variables will be retested along side with retail sales index vis-a-viz London stock exchange.
ABOUT THE LONDON STOCK EXCHANGE
The London Stock exchange is the most important exchange in Europe and one of the largest in the world. It lists over 3000 Companies and with 350 of the companies coming from 50 different countries, the LSE is the most international of all exchanges.
The London stock exchange is comprised of two different stock markets: the main market and the alternative investment market (AIM). The main market is solely for established companies with high performance, and the listing requirements are strict. Approximately 1,800 of the LSE’s company listings trade on the main market, and the total market capitalization of 37 Billion.
The LSE is completely electronic, but different shares are traded on different systems. Highly liquid shares are traded using SETS automated system on an order driven basis. This means that when a buy and sell price match, an order is automatically executed. For securities that trade less regularly, the London stock exchange implements the SEAQ system, where market makers keep the shares liquid. These market makers keep are required to hold shares of a specific company and set the bid and ask prices, ensuring that there is market for the stock.
The LSE also has a new and growing exchange for equity derivatives called EDX London, created in 2003. In 2004, EDX traded an average of 382,599 contracts per day. It aim is to become the leading derivative market in the world (see http://www.advfn/stockexchanges/about/LSE/LondonStockExchange.html)
A stock market is a public market for the trading of company stock and derivatives at an agreed price; these are securities listed on a stock exchange as well as those on traded privately.
The size of the world market was estimated at about $36.6 trillion US at the beginning of October 2008. The stocks are listed and traded on stock exchanges which are entities of a corporation or mutual organisation specialized in the business of bringing buyers and sellers of the organisation securities together. The stock market in the United States is NYSE while in Canada; it is the Toronto stock exchange. Major European examples of stock exchanges include London Stock Exchange, Paris Bourse, and the Deutche Borse. Asian examples include the Tokyo stock exchange, the Hong kong stock exchange, and Bombay stock exchange. In Latin America, there are such exchanges as the BM&F Bovespa and BMV (see http//en.wikipedia.org/wiki/stock_market).
A security is a fungible, negotiable instrument representing financial value. Securities are broadly categorized into debt security (such as banknotes, bonds and debentures) and equity securities, e.g., common stocks; and derivative contracts, such as forwards, futures, options and swaps. The company or other entity issuing the security is called the issuer (see http://en.wikipedia.org/wiki/security_(finance)).
STOCK MARKET INDEX
The movement of the prices in a market or sections of a market are captured in price indices called stock market indices of which there many, e.g. S & P, the FTSE and the Euronext indices. Such indices are usually market capitalization weighted, with the weights reflecting the contribution of the stock to the index. The constituents of the index are reviewed frequently to include / exclude stocks in order to reflect the changing business environment (see http://en.wikipedia.org/wiki/stock_market).
FTSE 100 INDEX
It is a share index of the 100 most highly capitalized UK Companies listed on the London Stock exchange. FTSE 100 companies represent about 81% of the market capitalization of the whole London Stock Exchange. Even though FTSE All share index is more comprehensive, the FTSE 100 is by far the widely used UK stock market indicator (see http://en.wikipedia.org/wiki/FTSE_100Index).
INDUSTRIAL PRODUCTION INDEX (IPI)
The industrial production index is an economic indicator which measures real production output. It is expressed as a percentage of real output with base year. Production indexes are computed mainly as fisher indexes with the weights based on annual estimates of value added. This index, along with other industrial indexes and construction, accounts for the variation in national output over the duration of the business cycle (see http://en.wikipedia.org/wiki/industrial_production_index).
CONSUMER PRICE INDEX (CPI)
CPI is a measure estimating the average price of consumer goods and services purchased by households. A consumer price index measures a piece change for a constant market of goods and services from one period to the next within the same area (city, region, or nation). It is a price index determined by measuring the price of a standard group of goods meant to represent the typical market basket of a typical urban consumer. The percent change in the CPI is a measure estimating inflation (see http://en.wikipedia.org/wiki/consumer_price_index). According to B Hobijn & D Lagakos (2003) CPI is the benchmark measure of inflation.
RETAIL SALES INDEX (RSI)
RSI is a monthly measurement of all goods sold by retailers based on a sampling of retail of retail stores of different types and sizes. The retail sales index is often taken as an indicator of consumer confidence. Many analysts choose to look at the figure ‘’ex-auto” (excluding the volatile car sales figure). It is thought that this number is a better measure of across-the-board purchasing trends. The report does not include money spent on services, so it represents less than half of total consumption during the month. However, even with these limitations the figures are closely watched as an indicator of the health of the economy (see http://www.investorword.com/5768/retail_sales_index.html).
DATA AND METHODOLOGY OF THE RESEARCH
In this research work, the data used are monthly market index data from Jan. 2000 to Nov.2009. Secondary data were obtained from yahoo finance (FTSE 100 index) and Office for national statistics (consumer price index, industrial production index and retail sales index). November data were not captured in the regression result because, data available for industrial production index does not cover November (the last data released was in October 2009).
The method adopted is multiple regression model to analyse the quantitative relationship between ftse100 index and three explanatory variables i.e. index of industrial production, consumer price index and retail sales index. According to Gray Koop (2006, 2008 & 2009) Regression quantifies the effect of an explanatory variable, X, on a dependent variable, Y. Hence, it measures the relationship between two variables.
The relationship between Y and X is assumed to take the form, Y= α + βX, where α is the intercept and β is the slope of a straight line. This is called the regression line.
The regression line is the best fitting line through an XY graph. No line will ever fit perfectly through all the points in an XY graph. The distance between each point and the line is called a residual. The ordinary least squares (OLS) estimator is the one which minimizes the sum of squared residuals and provides estimates of α and β.
Regression coefficient should be interpreted as marginal effects (i.e. as measures of the effect on Y of a small change in X. Thus, multiple regression model in this research work can be represented as
Y = stock price (ftse100 index)
α = intercept
β = coefficient for the explanatory variables
X1 = consumer price index
X2 = index of industrial production
X3 = retail sales index
Ε = Error (residual)
Therefore the estimated regression equation is thus:
The multiple regression correlation coefficient,,
This a measure of the proportion of variability explained by the regression relationship model or the regression equation. Roughly, this means is the percentage at which the model explains the changes in the dependent variable based on the independent variables. The standard deviation is the range at which there is +/- error with a 95% confidence level.
In order to gauge the accuracy of α and β estimates, the use of hypothesis testing on regression coefficients become very relevant at 95% confidence interval. This is given as
Null hypothesis H0: β1 = β2 = β3 = 0
Alternative hypothesis H1: β1 ≠ β2 = β3 = 0
If the P-value is less than 5% (0.05) then t is ‘large’ and the conclusion is β ≠ 0. But, if the P-value is greater than 5% then t is ‘small’ which means β = 0.
ANALYSIS OF RESULTS
Adjusted R Square
Source: Regression results
The value of R (multiple Correlation coefficients) obtained for the data is 0.75 which lies between 0 and 1 indicating a positive relationship between stock price index and the selected economic variables (consumer price index, industrial production index and retail sales index).
It is significant to note that out of all the possible economic indicators that affect stock prices, 56% of changes could be attributable to real production output, inflation and goods sold by retailers as shown by above regression results.
Source: Regression results
Considering the model specification presented and utilizing the results obtained after running the data through Microsoft Excel 2007 the estimated regression model becomes;
The regression result above shows that there is a positive relationship between stock price and consumer price index (X1). This is in accordance with earlier expectation stated. Having P-value as 5.716E-16 i.e. it’s less than 5%. It means β1 ≠ 0; null hypothesis will be rejected while alternative hypothesis is accepted. This indicates that parameter estimate is statistically significant, meaning that consumer price index has relevant influence in explaining stock price.
P-value for X2 is 1.053 × 10^-19 which is less than 0.05, this shows that the result is statically relevant, it means, index of industrial production has a positive relationship with stock price. Therefore, β ≠ 0; null hypothesis should be rejected and accept alternative hypothesis.
The above regression result shows a positive relationship between stock prices and retails sales index considering the P-value of 1.598E-09 which is less than 0.05. Statically, it shows that parameter estimate is very relevant and that, retail sales index contribute meaningfully to stock price determination in London stock exchange. Consequently, β3 ≠ 0; null hypothesis must be rejected while accepting alternative hypothesis.
This study examined the effect of economic factors on stock price; the scope was limited to London stock exchange. As a result, FTSE 100 index was used as an independent variable while index of industrial production, consumer price index and retail sales index were examined as explanatory variables. It was deduced from the result of multiple regression model used that, there is a positive relationship between stock prices (as represented by FTSE 100 index) and the above listed economic variables most especially in the London stock Exchange. This by extension correlates with the results of some earlier researchers on the subject matter.
In safe guarding stock prices in London stock exchange market, it becomes highly imperative and a major point of consideration for policy makers when trying to influence the economy through changes in economic variables such as the money supply, interest rates, or the exchange rate while aiming to correct economic ills such as inflation or unemployment to always access its multiplier effect which may inadvertently depress the stock market, and curtail capital formation which itself would lead to further slowdown of the economy.