Structural analysis of stock prices and some macroeconomic indicators in Ghana

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2014-10-16
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Abstract
Capital markets play a significant role in the financial sector of every economy. Through stabilization of the financial sector and the provision of important investment channels that contribute to attract domestic and foreign capital, an efficient market can promote economic growth and prosperity. This study investigates the relationship between stock prices and macroeconomic factors in Ghana using monthly data covering the period November, 1990 to June, 2011. The study employed the celebrated multivariate Vector Auto regression (VAR) models to establish the linkage between stock prices and macroeconomic factors. Additionally, the Granger causality analysis was used to examine the direction of causality between stock prices and the various macroeconomic factors. It was found that interest rate and inflation are the key macroeconomic factors that determine stock prices in Ghana within the period. Furthermore, it was found that with the exception of inflation and interest rate, no other macroeconomic variable specified in the model Granger causes stock prices. Indeed, causality does not also run from stock prices to these variables. Additionally, forecasting GSE index using macroeconomic variables was somewhat difficult since they are affected considerably by economic policies. . The immediate corollary of the results therefore is that, perhaps the Ghana Stock market might be sensitive to global macroeconomic factors other than the internal ones. Thus the economic policies of Ghana need to be properly and utterly synchronized thus brought to line with global macroeconomic and financial conditions. Incidentally, this policy direction would mean that, controlling domestic policies alone is not enough for the determination of stock prices in Ghana.
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A thesis submitted to the Department of Mathematics of the Kwame Nkrumah University of Science and Technology in partial fufilment of the requirement for the award of Master of Science degree in Industrial Mathematics.
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