Macroeconomic Variables and Nigerian Stock Market

The world’s financial market are categorized into three different classification namely developed, emerging and frontier markets, (FTSE 2003). This classification was done on the foundation of size of the economy, the economy’s wealth, markets quality and size. Considerable literature has been written that investigates the relationships that exists between stock returns and a series of macroeconomic variables of diverse economies stock markets, (mostly developed markets and a few emerging markets). However despite the large volume of literature on macro economic variables and stock markets movement very little are known on the relationship between macro economic variables and stock markets under the classification of frontier markets. The Nigerian stock market is an example of a frontier market, established in the year 1960 and became the Nigerian Stock Exchange in 1977 from the Lagos stock exchange it used to be called with six branches spanning across the length of the country. The exchange though, with a lower market capitalization and liquidity compared to other emerging and developed markets, it is still classified as a frontier market. The exchange is a market has gained the interest of different investors seeking for markets with low correlation with other market and high long term returns.

ECONOMIC BACKGROUND ON NIGERIA

Pre Independence Economy: Before the Nigerian independence in 1960, the Nigerian economy was characterized by export of agricultural product and other commercial activities. The economy was Agrarian in nature, which is solely depending on the agricultural sector of the economy. Agricultural sector constitute up to 70% of Nigeria export and 65% of the Gross Domestic Product. The colonial masters adopted the policy of import substitution strategy, where most consumers’ goods which were formally imported were produced within the country and other raw output from the agricultural sector was exported to other industrialized nations as raw material. The home firms were protected for them to grow with the use of protective measures like tariffs and quota. The unemployment rate reduced to 1.5%, the inflation rate reduces slightly and there was a moderate productivity within the economy.

Post independence economy (1960 – 1970): Within few years after the Nigerian independence, the country still relies heavily on the Agricultural sector of the economy. During this time, the sector account for about 40% of the GDP before 1973, with an annual growth rate of 3.1%. After these years the output from the sector start to decrease, the output from the agricultural sector decreased to 1.9% and agricultural export to 7.9%. The import share of the sector increases to 7% in 1980 from 3% in the early 1960s. This was as a result of the government action to abandon the sector as a result of the discovery of oil as a new source of revenue in the country. This neglect of the agricultural sector has lead to the naira depreciating, increase unemployment rate as the sector is the greatest employer of labour in the country. The economy was also characterized by subsistence and commercial activities. There was bias government policies that has have negative effect on economy development, over reliance on external factor input and weak institutional capability are the main features of the economy during this period.

Oil Boom era(1971-1977): During this period, the contribution of the agricultural sector which was 48.23% in 1997 fell to 21% in 1977 and the sector percentage to the country’s total export declined from 20.7% in 1971 to 5.71% in 1977. The agricultural sector was affected due to its neglect as a result of the embargo place on America on Arabian oil and the discovering of crude oil in commercial quantity. The oil sector constitutes about 90% of the economy foreign exchange earnings and contributed about 80% to total export. The revenue realised from oil were then utilised to import food which were formally produced within the country when the economy still rely on the agricultural sector. Though, the growth rate was high with 10.5% in 1976, inflation rate reduces to 16% in 197, but the exchange rate regime encourage importation. The manufacturing sector increased to 82.2% between 1972 and 1976 and 94% in 1977.

Structural adjustment and stabilisation: Though there was an increase growth rate during the oil boom era, but negative growth was witness in the economy between 1979 and 1985. This period record an increased inflation, unemployment rate and fiscal imbalance. The manufacturing sector declined tremendously from 14.6% in 1981 to 3.2% in 1989. The government then, introduced an economic reform in 1986 to curtail this macroeconomic downturn, aimed at altering and making adjustment in aggregate household spending with production pattern in the economy, so as reduced the reliance on import and improve the non oil sectors and bring back the economy to track. The objectives were to

1. Expand the productive base of the economy to other sectors
2. Attain financial balance of payment viability
3. Curtail the inflationary growth in the economy
4. Improve sector efficiency and ease the dominance of unproductive investment of the public sector, and strengthen development potentials in the private sectors.

All these are achieved using different measure like the privatisation and commercialisation of public sectors companies, reliance on market forces and reduce administrative controls, promotion of private firm by tariff restrictions and the use of appropriate pricing policies for petroleum products among others. [1]

The Nigerian Stock Exchange

The Exchange was founded in the year 1960, formerly known as the Lagos stock exchange, before it became the Nigerian Stock Exchange (NSE) in 1977. The exchange house the trading floor where stock of the capital market are been traded. The NSE is characterised by a self regulatory called the Security and Exchange Commission (SEC) which is the agent responsible for the regulation of transaction on the exchange. The Nigeria stock market has been made more friendly and competitive in the course of the deregulation of the NSE in the year 1993, which results to an increase in the number of securities and companies on the exchange and the recapitalisation of the country’s banking sector. There are 266 securities listed on the exchange in 2008 with a market capitalization of (N9516.2billion). The market capitalization of the stock exchange has grown over the years from (N5billion) in 1981 to N9516.2 billion [2] in the year 2008. The volume of transaction, on the exchange grew from 138.1billion share valued at N2.1trillion in 2007 to 193.14 billion shares valued at N2.4trillion traded in 2008 [3] . The trading on the floor has been replaced by the automated trading system from the manual call over system and the establishment of the central clearing system limited (CSCS) which took charge of the clearing and settlement of the trading transaction has lead to effectiveness and improvement of the exchange. The exchange has practice cross border listing and transaction and has attracted so many foreign investors into the market.

LITERATURE REVIEW

Theoretical background to the Study

It is said that an efficient capital market is one in which security prices adjust rapidly to the arrival of new information about the security (Ramin et al 2004). That is no investor should be able to take advantage of readily available information in order to make profit on trading of stocks based on that information. To study the relationship between stock market movement and macroeconomic variables, some models which provide a appropriate structure has been provided by existing financial economic theory (Humpe and Macmillan 2009). These includes the Arbitrage pricing model(APM), The Efficient Market Hypothesis (EMH) and the Capital assets pricing model (CAPM) among others. For the purpose of this research we use the APT, EMH (semi-strong version) and the CAPM to know the relationship that exist between macroeconomic variables and the Nigerian stock market movement.

The efficient market hypothesis

The basis of recent financial economics has been the efficient market hypothesis, the hypothesis assert that it is impossible to beat the market due to stock market efficiency that cause active share prices to always involve and reflect all information that are relevant within the system. (Fama 1978) defined an efficient market as the one that reflect all existing information. Jenson (1978) defined an efficient market as regards to the information set that is available in the market that is if it is impossible to make economic profit [4] on the basis of the information set. There are three main variation of the efficient market hypothesis: weak form, the semi strong form and the strong form hypothesis.

The weak form of the efficient market hypothesis asserts that the current prices of traded assets constantly reflect all previous prices and all available information. Current prices of assets completely reflect previous prices and information .It means that it is impossible to use the past movement of stock prices to determine or forecast future stock value.

The semi strong variant of the EMH stipulates that a stock price includes all available information in the public and that stock prices quickly changes to reflect the newly public information. This shows that the efficient market hypothesis could be used as the source to derive the relationship that exist between an economy microeconomic variables and stock prices since the semi strong form assert that economic factors are completely reflected in stock prices. It on the aspect we investigate whether it is positive or negative relationship that exists between stock prices and different economic factors.

The strong efficient market hypothesis depict that market prices also reflects insider or private information and this make it impossible to make excessive trading profits.

Efficient capital market

According to (Fama 1976) he shows that the efficiency of a market necessitate that in fixing Stock prices at a previous time say t-1, all publicly available information are used. If for instance we assumed the price of an assets at a previous time t-1 depends on just the features of the joint distribution of prices to be fix at a current time i.e. t. An efficient market implies that, if new information exists in the market, this will be incorporated in the stock price rapidly with respect to the direction to the stock price movement and the volume of the movement. In an efficient market no investor will have the opportunity to make return on a stock that is greater than a fair return for the risk associated with the stock. The absence of making an abnormal profit arises because current and past information are instantly reflected in the current prices of assets. In most stock markets of the world today, stock prices are set on the basis of the of the interaction of demand and supply, different analyst and investors receives information through the media, as a result of technological advancement. In an efficient market the moment there is a positive news or information, investors react and stock prices rise rapidly to a level that gives no opportunity for abnormal profits. In an efficient market, the current stock price is a function of price at period t-1 and all information set available in the period i.e.

SPt= fx (spq, θt-1) = MSPt = fx (MSPq, θt-1)

Where SP represents the prices of stock at current time t, which is a function of the combinations of previous stock prices, SPq (Pt1, pt2…..Ptn) and θt-1 which represent the publicly available information at previous time t-1. Likewise for the stock market, the current market stock prices (MSPt) are determined by the previous market prices of stock and the information set at time t-1. This can be used to express the relationship between macroeconomic variables and returns on stock.

The Arbitrage pricing theory

The theory gives a different method to show the relationship between macroeconomic variables and stock movement. This theory was initiated by (Rose S. 1976), it propose another method to test the Capital assets pricing model (CAPM) and gives related assumption to that of CAPM which are less friction capital markets, perfect competitive market and assumption of homogeneous expectations and introduced the process generating security. This was derived from the law which specifies that for an efficient market, an asset most have a single price.

The Arbitrage pricing theory shows that the expected return of assets can be modeled as a linear function of different macroeconomic factors or indices of the market, with the factors denoted with a factor specific beta coefficient which measures how responsive the assets are to each factors in the model. The factor specific coefficient is derived from the change that occurs in the financial and economic variables in the economy such as the changes in exchange rate, inflation rate and the rate of interest (Chen et al, 1986). The theory, assumes that the returns on an assets Ri follows a factor structure of different economic factor given as

E (RI) = bi1f1 + bi2f2 + bi3f3 + bi4f4 + ………+ binfn + Ui

E(Ri) represent the expected returns on the assets i, the f1 f2 f3 …… fn represent the uniform factor that drives return on the assets and the b coefficient b1, b2, b3,…….bn represent the factor specific beta coefficient that measures each factors and the Ui is the characteristics component of the assets i that is not related to the assets returns, where f1, f2, f3……fn have means equal zero.

Rose S. 1976, shows that if the number of assets involved are so many, that is using that of an entire market, the relationship is that the expected returns will be determined by a risk less rate of return and the equilibrium risk premium of the factors f1, f2, f3……..fn.

E (Ri) = λo + λ1bi1 + λ2bi2 + λ3bi3 + λ4bi4 +…… ………….+ λnbin

E(R) represents the expected return, λo is constant, λ1 to λn are the risk premium, for factors f1 to fn. The zero mean random factors are the unexpected changes in the macroeconomic variables where the value of the beta coefficient measures the degree and trend of the return on the assets. (Haider and Iqbal, 2005).

Empirical Review

Many research works has been carried out after the literature by (Chen et al, 1986) examining macroeconomic variables and stock markets. In their paper they tested multifactor model in the United State using seven macroeconomic variables, they came out to establish that the prices of oil, consumption and market index are not value by the financial market. Though, industrial production, twist in the yield curve and risk premium changes are detected to be significant in describing stock returns. In the work of (Chen et al, 1991), they perform another study on the US economy, their findings suggest interpreting some US macroeconomic variables like dividend price ratio and growth in industrial production could be used to forecast future market returns. Gjerde and Saetten (1999) also investigate the causal relationship between the stock macro variables and stock prices in the Norwegian economy, the outcome of their study was that there exist a positive connection between the prices of oil and the real economy activity and the returns on stock. (Clare and Thomas, 1994) examines the effect of macro variables on the UK stock market, using 18 macroeconomic variables, which includes oil prices, banks lending rate, retail price index and corporate default risk as the main risk factors for stock return in the UK economy. Gan C et al (2006) investigated the links between seven macroeconomic variables and the New Zealand stock index for a period of thirteen years covering 1990 to 2003 employing johansen cointegration and Grainger causality test. They found out that the New Zealand stock index is constantly decided by the real Gross domestic product, interest rate and the volume of money supply among these macroeconomic variable with no proof that the market’s stock index is the principal pointer for changes in macroeconomic variables.

Another group of study examined the connection between macroeconomic variables and stock market on emerging market. Bailey and Chung (1996) looked at the effect of macroeconomic risk on the Philippines equity market, their investigation reveals that financial volatility, exchange rate movement and political change on owners of Philippines equities could not explain returns on stocks in the Philippines. Ibrahim and Aziz (2003) examine the link between stock prices and some macroeconomic variables of money supply, CPI, exchange rate and industrial production in the Malaysian economy. Their findings was that, exchange rate and money supply have a long run negative relationship with stock prices while the consumer price index (CPI) and industrial production has a long run connection with the stock prices in the Malaysian economy. Ramin et al (2005) studied macroeconomic variables and Singapore all s sector indices using a twelve year period between 1989 and 2001 employing the Vector cointegration model (VECM) they found evidence of a relationship between the Singapore stock exchange and inflation rate and real economic activities, short run relationship exist for money supply, interest rate and exchange rate and stock returns but are negatively related in the long run.

The third group of studies examines the situation across countries, these paper include that of Cheung and Ng (1998), they examine the link between stock prices and macroeconomic variables which include the Gross National Product (GNP), money supply, oil prices and total consumption in 5 economies of Germany, USA, Japan, Canada and Italy. The result of their findings suggests a long run movement between these variables and real stock market prices. Wongbangpo P and Sharma S. (2002) investigated the impact of some selected macroeconomic variables which include GNP, consumer price index, money supply and exchange rate of five countries in Asia, consisting of Thailand, Singapore, Philippines and Malaysia on stock prices of these markets. They found that both short and long run relationship between these macroeconomic variable and the prices of stock. And straight financial strategy could lead to notable growth in both sectors due to this relation.

Gay R.D (2008) examines the impact of macroeconomic variables on stock return in four emerging markets. He employs the box Jenkins ARIMA model to investigate the consequences of exchange rate and the real oil prices of India, Russia, China and Brazil on the stock return in these emerging economies. The effect was that there was no evidence to show that these two macroeconomic variables result to the movement in the stock prices of these markets, that there exist other domestic factors that can decides stock prices in these markets.

METHODOLOGY AND DATA

The empirical question is whether macro economic variables such as inflation, exchange rate, oil prices, money supply, consumer price index, industrial production and Gross national product significantly explain stock market returns. Given that the rationale of this study is to investigate a long term relationship between macroeconomic variables and the Nigerian stock market movement. For the purpose of this study, we employ the Johansen cointegration Analysis to test whether the variables are co integrated with the stock prices in the Nigerian stock market and also the Granger Causality test to establish the causality of our chosen variables with the stock market prices. Since we are using a time series data (Annual data) we make use of the Augmented Dicken fuller test by Dicken and Fuller (1979) to ensure stationarity in our chosen series.

Data selection

Available annual data of stock prices index, exchange rate, money supply, Gross national product, interest rate, oil prices, industrial production, inflation, consumer prices index and covering a period of twenty three years (1985-2008) would be obtained from the international monetary fund (IMF), the Central Bank of Nigeria (CBN) and the Nigerian stock exchange (NSE).

Variables

Definition

Exchange rate (EXC)

Rate at which the Nigerian Naira is converted to US$

Money supply (M1)

The stock of money in circulation in the Economy

Industrial production (IDP)

Annual industrial production to determine economic activity

Interest rate (IR)

Real interest rate in Nigeria

Oil prices (OILP)

Crude oil prices in Naira

Inflation (INF)

Annual inflation rate

Share price index (SPI)

General market prices index, listed on the NSE

Preliminary data analysis

A brief look at the data disclose no missing data in the annual data set for the data range (1985- 2008).To enable for better analysis between the data set due to the size difference among the data sets such as the share index, oil prices money supply and industrial production which are quite large in size when compared with interest rate and exchange rate figures. The Log of the data set was taken to correct for this disparity in the difference in data size. Unit root test carried out to test for stationary since stationarity is a prerequisite for time series analysis, the augmented dickey fuller test was carried out on all the data set. The test result confirms the presence of unit root for all data set. I then proceeded by the first taking difference and retesting for the presence of unit root. The unit root test at first difference shows stationary for all data sets.

RESEARCH FORMAT

The structure of this work will be as follows: chapter one of this research will talk about the background to the study, looking at the structure of the Nigerian economy and the Nigerian stock market base on its performance it has achieved over the years. The second chapter will focus on the theoretical background supporting the study of macroeconomic variables and stock returns and different contribution by different researcher on the subject matter. The methodology, data source and techniques to be used are contained in the third chapter. The forth chapter will include the analysis of test result conducted in the third chapter while the last chapter is meant for the conclusions on the study.

CONCLUSION

This research work is expected to contribute to available literature on macroeconomic variables and stock market movement while filling the void in the frontier market segments of these literatures. It aims to explain the relationship between stock markets and macro variables if any in frontier markets. It also hopes to provide sufficient insight for policy makers in their policy formulation for economies with frontier markets and also it should serve as a starting board for future research work on frontier markets.