GLOBAL FINANCIAL MELTDOWN, STOCK MARKET VOLATILITY AND THE NIGERIA ECONOMY
ABSTRACT
This study investigated the relationship between volatility in the United States economy and capital markets, and the Nigerian capital market and economy alike. The aim being to determine if the Nigerian bourse is volatile and if it is significantly affected by the current global economic meltdown (using data from the United States as proxies). Using secondary data for the period December, 1990 to December, 2008, the study made use of multiple regression analysis and the extension of Engle (1982) ARCH model, which is the GARCH model, developed by Bolerslav (1986). The study found positive and significant relationship between volatility in the United States economy (and bourse) and volatility in the Nigerian economy (and bourse). The result also discovered that the level of volatility was higher in the Nigerian bourse and that the level of Nigeria’s economic performance is not significantly determined by the level of volatility in the Nigerian bourse though, a weak relationships exist. Because of this weak relationship and significant effects of external stocks on Nigeria’s economy and bourse in particular. It is recommended that the Nigerian economy be properly diversified in such a way that it does not depend upon only one source of revenue. Also, policy makers are advised to be careful in their use of the Nigerian bourse as a barometer to reflect performance in the general economy as our findings suggests that this could lead to misleading conclusions. Finally, we recommend an improvement in the depth and breadth of financial products currently obtained in the Nigerian bourse.
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND TO THE STUDY
Numerous empirical studies have appeared in recent years concerning the volatility of stock market returns. Indeed a wide variety of research has been conducted on stock returns volatility in both developed and emerging markets since the 1970’s in which the nature of volatility in different markets at different point in time were uncovered; and financial economists during this period have been able to determine the causes and variables behind the existence, nature and anomalies relating to market volatility. More recently, the volatility of stock market prices and returns on the Nigerian stock market has been a major concern to investors, analysts, brokers, dealers and regulators. Stock return volatility has severally been defined as a representation of the variability of stock price changes (perceived by many as a measure of risk). Variability also refers to the degree to which financial prices fluctuate. Large volatility means that returns (i.e. the relative price changes) fluctuate over a wide range of outcomes. The understanding of the level of volatility in a stock market will naturally be useful in the determination of the cost of capital and in the evaluation of asset allocation decisions. Policy makers therefore rely on market estimates of volatility as a barometer of the vulnerability of financial markets (Olowe, 2009). However, the existence of excessive volatility, or “noise” in the stock market undermines the usefulness of stock prices as a “signal” about the true intrinsic value of a firm, a concept that is core to the paradigm of the informational efficiency of markets (Karolyi, 2001).
The traditional measure of volatility as represented by variance or standard deviation is unconditional and does not recognize that there are interesting patterns in asset volatility: e.g., time-varying and chestering properties. Researchers have introduced various models to explain and predict these patterns in volatility. Engle (1982) introduced the autoregressive conditional heteroskedasticity (ARCH) to model volatility. Engle (1982) modeled the heteroskedasticity by relatiing the conditional variance of the disturbance term to the linear combination of the squared disturbances in the recent past. Bollerslev (1986) generalized the ARCH model by modeling the conditional variance to depend on its lagged values of disturbance, which is called generalized autoregressive conditional hetereskedasticity (GARCH). Some of the models include IGARCH originally proposed by Engle and Bollerster (1986), GARCH-in-mean (GARCH-M) model introduced by Engle, Lilien and Robins (1987), the standard deviations GARCH model introduced by Taylor (1986) and Schevert (1989), the EGARCH or Exponential GARCH model proposed by Nelson (1991), JARCH or Threshold ARCH and Threshold GARCH were introduced independently by Zakoian (1994) and Gilosten, Jajanoathan, and Runkle (1998), the power ARCH model generalized by Ding, Zhvanzin, C.W.J. Granger, and R.F. Engle (1993) among others.
If investors are risk averse, theory predicts a positive relationship should exist between stock return and volatility (Leon, 2007). If there is a high volatility in a stock market, the investors should be compensated in form of higher risk premium. The GARCH-in-mean (GARCH-M) model introduced by Engle, Lilien and Robbins (1987) has been used by various researchers to examine the relationship between stock return and volaitility (see French, Schwert and Stambough, 1987; Cheu, 1989) while some others found it negative (Nelson, 1991; Colosten et al, 1993 among others). Little or no work has been done on modeling stock returns volatility in Nigeria particularly using GARCH models (Olowe, 2009).
Furthermore, the term “global economic meltdown” (with its pervasive effect) on many economies, is increasingly becoming a topical issue in many developing and emergent economies in recent time. It currently is used to refer to a financial crisis that is currently plaguing much of the advanced world with increasing levels of spillovers into the economies of developing nations. The current global financial crisis which was triggered by the credit crunch within the US sub-prime mortgage market, is continuing to spread and deepen in several countries. Countries around the world have approached this whirlwind pragmatically, prompting emergency funding support for relevant sectors, thereby mitigating the impact of the crisis on economies as well as avoiding the entire collapse of the international financial system. In spite of such support, some countries have been officially declared as being in recession, owing to a monumental decline in their wealth, manifesting itself in falling productive capacity, growth, employment and welfare (Ajakanye and Fakiyes, 2009).
The global financial crisis of 2008, an ongoing major financial crisis, could have affected stock volatility. The crisis which was triggered by the sub-prime mortgage crisis in the United States became prominently visible in September, 2008 with the failure, merger, or conservatorship of several large United State – based financial prime exposed to packaged sub-prime loans and credit default swaps issued to insure these loans and their issuers (Wikipedia, 2009). The crisis rapidly evolved into a global credit crisis, deflation and sharp reductions in shipping and commerce, resulting in a number of bank failures in Europe and sharp reductions in the value of equities (Stock) and commodities worldwide (Wikipedia, 2009). The financial crisis created risks to the broad economy which made central banks around the world to cut interest rates and various governments implement economies stimulus packages to stimulate economic growth and inspire confidence in the financial markets. The financial crisis dramatically affected the global stock markets. Many of the world’s stock exchanges experienced the worst declines in their history, with drops of around 10% in most indices (Wikipedia, 2009). In the US the Dow Jones industrial average fell 3.6%, not falling as much as other markets (Olowe, 2009). The economic crisis even caused some countries to temporarily close their market (Wikipedia, 2009).
The purpose of this study is to determine if the Nigerian economy is affected significantly by the current global economic meltdown, with the aid of secondary data collected between the periods of 1990-2008. Specifically our aim is measure the level of volatility in the Nigerian bourse for the specified period of time. Also this study sought to determine if the level of volatility in the Nigerian bourse is significantly determined by the level of volatility in the American economy using United States gross domestic product (GDP) and the Dow Jones Industrial Average (DJIA) as proxies for reflecting the effect of the global economic meltdown on the Nigerian economy. Lastly, the study also sought to determine if there is a significant relationship between Nigeria’s economy performance and its level of stock market volatility.
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