Impact Of Stock Prices In South Africa
The world market for oil prices is controlled by the simple economic supply and demand curve. When supply and demand are equal the oil price will be at equilibrium, however when the supply is greater than the demand then this results in a downward shift in the supply curve and a decrease in the price of oil. The opposite will be applicable when the demand exceeds the supply, you will find that the price of oil will increase. Any movement in the price of oil results in uncertainty in the stock market. This leads to the stock market and the price of oil having an inverse relationship. Say, a decrease in the oil prices by 10% in US will result in the expected return to double up on the stock market in the following month. The waves of the impact on the world market index will make its presence felt significantly. Though the stock market moves in the opposite direction with respect to oil prices, it is basically a one way traffic. The stock market returns has no impact on the crude oil prices. (Omar L. Caban, 2011)
There are many factors that drive the price of oil up. Firstly there is an ever increasing demand for worldwide oil as many countries are rapidly industrializing their economies. The other force driving prices is organized terrorism in the Middle East. Destroying oil production in Iraq and other producer countries, which will drive up crude prices, is seen by terrorists as a highly desirable goal. Political unrest in the oil producing countries like Venezuela, Libya and previously Iraq and Iran also drive the price of oil up.
The price of a share in a company at any one time is equal to the expected value of discounted future cash flows of that company. The model used to calculate the stock price has and interest portion to it, which means that the stock prices can be indirectly affected by an increase in interest rates caused by a rise in crude oil prices or the crude oil prices can directly impact the share prices by affecting the future cash flows of the company.
It can be argued that the increase in the crude oil prices will increase the cost of doing business and this will lead to the increased costs of production being passed to the final consumer. If the consumer is paying the increased costs then the stock prices should not be affected, however the increased prices of goods will lead to the demand for the goods falling and therefore decrease the profits of the entity, again decreasing the stock price.
In theory it is well established that the crude oil prices affect the stock prices negatively however this paper will follow by discussing the empirical evidence to see if this notion is supported or not.
In comparison to the volume of work investigating the link between oil prices and macroeconomic variables, there has been relatively little work done on the impact on the financial markets, with studies as early as 1982 by Bruno and Sachs (1982) documenting the oil price and economy relationship. Thereafter it was well established by research of (Gisser and Goodwin (1986), Hickman et al. (1987), Hamilton (1983), Jones and Leiby (1996), Rasche and Tatom (1977, 1981), Barro (1984), Brown and Yücel (2002) and more recently Lescaroux and Mignon (2008)) that oil prices affect the economy and rising oil prices slow GDP growth. What is most surprising is before 1996 there was already ample research on the above linkage and little or no research on the impact on financial markets. If it was that apparent that the oil prices play a crucial role in the economy, it would not be surprising to think that the linkage between that crucial component of oil and the other vital economic development tool of the stock market should be established.
Jones and Kaul's (1996) recognized the need to venture into the oil and stock market relationship with their study titled ‘Oil and the Stock markets’. They use quarterly data to test whether the reaction of advanced stock markets (US, UK, Japan, Canada) during oil price spikes can be justified by current and future changes in real cash flows and/or changes in expected returns. They found that the reaction of the United States and Canada to oil shocks can be accounted for by the impact of the shocks on the cash flows alone. The United Kingdom and Japan show substantially greater changes in the stock prices that can be justified by the oil shocks alone. A possible reason for the greater increase is that the UK and Japan markets overreact to oil shocks.
Huang et al (1996) use the vector auto regression model to investigate the relationship between daily oil futures returns and daily US stock returns. They found that there was a relationship that existed, however it was only between some US oil companies that oil futures returns lead the US stock market and a significant relationship existed. They also found that the relationship was insignificant when trying to explain it using a broad based index like the S&P 500 and that oil futures volatility leads the petroleum stock index volatility.
Using quarterly data from 1947 to 1991, Jones and Kaul (1996), found that oil prices do have an effect on aggregate stock returns. In contrast, Huang et al (1996) used daily data from 1979 to 1990 and found no evidence of a relationship between oil futures prices and aggregate stock returns. Sadorsky (1999) identified the dissimilar results obtained by Jones and Kaul's (1996) and Huang et al (1996) and opted to use monthly data instead. Following Huang et al (1996), Sadorsky (1999) also used the VAR model in his research to build on the previous two studies and identify the interaction between oil prices and economic activity paying particular interest in the impact that oil price shocks may have on stock market returns. He found that oil prices and oil price volatility both play an important role in the economy. He also found evidence that oil price dynamics have changed. After 1986, oil price movements explain a larger fraction of the forecast error variance in real stock returns than do interest rates and that oil price volatility shocks have asymmetric effects on the economy.
Faff and Brailsford (1999) also use monthly data in their analyses of the Australian equity market and the oil price factor. They find that oil prices have a significant impact on most industries with the Oil and Gas and Diversified Resources industries positively impacted and the Paper and Packaging, and Transportation industries being negatively impacted.
Gjerde and Saettem (1999) use the VAR model as well to and they demonstrate that stock returns have a positive and delayed response to changes in industrial production and that the stock market responds rationally to oil price changes in the Norwegian market.
Sadorsky (2003) again uses monthly data, but this time investigates the macroeconomic determinants of U.S. technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of industrial production, oil prices, the federal funds rate, the default premium, the consumer price index, and the foreign exchange rate each have a significant impact on the conditional volatility of technology stock prices. Industrial production and the consumer price index each have the largest direct impact.
El-Sharif et al. (2005) argued that the research on the oil and stock market relationship was exclusive to North American and Australian data and was primarily conducted at a stock market-wide level. He instead opted to investigate the relationship between oil prices and the oil and gas sector instead. The results were just the same as previous studies in the sense that there is a significant relationship between the stock market variables and oil prices.
By 2005 the bulk of literature discussed have found that there is a relationship that exists between oil prices and the stock markets with Hammoudeh and Aleisa (2004), Hammoudeh, Dibooglu and Aleisa (2004) and Hammoudeh and Huimin (2005) taking the research further by investigating particular industries and the sensitivities those industries show to the changes in oil prices. Although the literature up to this point has been plentiful and the relationship undoubtedly proven to exist there bulk of the research concentrated on oil-importing countries. Abu Zarour (2006) went on to research the impact of oil prices on the stock markets of GCC countries. He applied the VAR model to the stock market of Five countries in the GCC and found that the response of these markets to shocks in oil prices increased and became faster during episodes of oil price increases.
Maghyereh and AL-Kandari (2007) later found that oil price affects the stock price indices in GCC countries in a nonlinear fashion and they supported the statistical analysis of a nonlinear modeling relationship between oil and the economy. Arouri and Rault (2010) also studied the relationship between stock markets and oil prices for GCC countries. He used the the panel-data approach of Kónya (2006), based on seemingly unrelated regression (SUR) systems and Wald tests with Granger to study the sensitivity of stock markets to oil prices for GCC countries over the period from June 2005 to October 2008, and from January 1996 to December 2007. Their results showed that there is statistically significant relationship and that is bi-directional for Saudi Arabia only. The other GCC countries stock markets do not influence the oil price changes but, the oil price shocks influence stock market changes in a negative direction.
A. Fayyad, K. Daly (2010) used the VAR model, DCV and Impulse Response techniques to examine the effects of changes in oil prices on the GCC countries, the UK, and the US stock markets. They examined the dynamic structures of the oil rich GCC countries and the US and UK in terms of the inter-relationships between oil and stock market returns. A. Fayyad, K. Daly (2010) found that oil return prediction vary over time for most countries over a number of periods.
South Africa is classified as an emerging market and although the literature discussed have established the relationship between oil prices and the stock markets in various ways which is useful in a sense that it establishes the basis of this study and the direction that the study should be heading. The only problem with the literature discussed is that it is concentrated on the developed nations and little research followed on the GCC nations but none have discussed the impact of oil price shocks on the emerging economies. This is rather surprising since emerging economies show much greater rate of growth then the developed economies and the demand for oil in emerging economies are increasing at a quicker rate then that of the developed countries. Papapetrou (2001) studied the impact with regards to Greece which is an emerging market. However, it was Maghyereh (2004) who identified the lack of literature on the impact of crude oil on the emerging markets other then those of the GCC.
Maghyereh (2004) examine the impact of oil prices of 22 emerging stock markets including South Africa using the unrestricted VAR model. He found that there was very weak evidence to suggest that there is a relationship between crude oil prices and stock market returns in the emerging markets and the study had no reason to believe South Africa had any significant results to suggest otherwise. The results were inconsistent with that of the developed markets and it was suggested that this may also indicate that the importance of oil price for the aggregate economy, especially in emerging economies, is greatly over-estimated and that stock market returns in the emerging economies do not rationally signal changes in the crude oil prices.
Papapetrou (2001) uses the vector autoregression (VAR) model to show the relationship between oil prices and the emerging stock market of Greece and found a significant short term link between oil prices and the stock market. Basher and Sadorsky (2006) use an approach which uses an international multi-factor model that allows for both unconditional and conditional risk factors to investigate the relationship between oil price risk and emerging stock market returns. They found strong evidence that oil price risks impact stock market return for emerging markets including South Africa. This is consistent with the findings of Papapetrou (2001).
Basher, Haug, Sadorsky (2010) researched the impact of oil price shocks on the emerging economies stock markets and exchange rates. South Africa was included in the data as an emerging market. They used SVAR model to model the dynamic relationship between real oil prices, an exchange rate index for major currencies, emerging market stock prices, interest rates, global real economic activity and oil supply. The results concluded that the stock markets react negatively to positive oil price spike and that oil prices react positively to a positive emerging market shock. It was also found that an increase in oil prices tend to depress the stock markets while on the other hand an increase in the emerging market stock markets tend to increase the oil price. They also propose that these results were consistent with economic theory that suggests that emerging markets are among the fastest growing economies (with GDP growth rates much faster than the growth rates observed in developed economies) and have, over the past ten year, been accounting for a larger proportion of global GDP.
The common conclusion in most literature is that the price of oil impacts the stock markets in the broader perspective as well as in the individual sectors themselves. In the sectors of the stock markets one would expect there to be statistically significant impacts but the direction of the impact will be different depending from sector to sector. The time and extent of the impacts differ when it comes to different countries but the literature examined do seem to show a trend in that net-oil importing countries are affected negatively by an oil price increase and the net oil exporting countries are positively affected.
When it comes to the emerging economies on the other hand, the impact of the crude oil prices are transmitted slowly to the stock markets compared to the developed economies. Maghyereh (2004) argued that the reason for this difference may be because the stock markets in the emerging economies are inefficient in transmission of new information of the oil market and it may also indicate that the importance of oil price for the aggregate economy, especially in emerging economies, is greatly over-estimated. He went further on to suggest that the results could imply that the stock market returns in the emerging economies do not rationally signal changes in the crude oil prices. Another notable difference in findings between the emerging markets and that of other economies is the impact the equity markets have on the oil price. In developed markets and GCC markets besides Saudi Arabia there was no bi-lateral relationship as Fayyad and Daly (2010) found. For emerging markets on the other hand Basher, Haug, Sadorsky (2010) found that emerging markets may influence oil prices and that an increase in oil price spike will depress the emerging stock markets, but increases in emerging market stock markets will lead to an increase in oil prices. Therefore emerging markets may have a bilateral relationship between the stock markets and oil prices.
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