Analysing Stock Market Reaction to Macroeconomic Variables: Evidence from Nigerian Stock Exchange (NSE) (Published)
This study examined the impact of some selected macroeconomic variables on stock market performance in the Nigerian Stock Exchange (NSE). The study adopted all share index (ASI) as proxy for stock market performance and the dependent variable, while the selected macroeconomic variables included broad money supply (BMS), interest rate (ITR), inflation rate (IFR), and exchange rate (EXR) used as the independent variables. Secondary data for the variables was sourced from Central Bank of Nigeria (CBN) Statistical Bulletins covering the period 1985 to 2017. The study employed multiple regression technique, Augmented Dickey-Fuller unit root test, Johansen co-integration test and Error Correction Model (ECM) based on the E-views 9.0 software as methods of data analysis. The analysis of data revealed that a long-run equilibrium and short-run dynamic relationships existed between the selected macroeconomic variables and stock market performance in the Nigerian Stock Exchange. Overall, the empirical results showed that all the independent variables had significant influence on stock market performance. The impact of the individual macroeconomic variables indicated that broad money supply and exchange rate had significant positive effect on all share-index, while interest rate and inflation rate exhibited an inverse relationship with all-share index. Based on the findings, the study recommended that the monetary authorities should put in place sound monetary policies that would bring about positive developments in the stock market.
Whether economic interdependence among countries is a contributing factor to co-integration and common stochastic trends in international stock markets is indiscernible due to conflicting results from prior empirical works. The purpose of this study is in two folds: Firstly to investigate whether the implementation of the Maastricht treaty has played any role in determining the long-run relationship between U.K stock market and other E.U and non-E.U stock markets and also to investigate the extent to which world stock markets have been correlated in the short-run over the study period and how such relationships would benefit investors in their portfolio diversification decisions. Data for this study was obtained from M.S.C.I indices and covered the period from 1985-2003. The methodologies used for this study are the correlation coefficient, the Vector Error Correction model and Vector Autoregressive model for the short-run relationship as well as the Johansen Co-integration approach for testing the long-run stochastic trend among the variables under consideration. The results for the short-run relationship among the variables indicates that in general, stock markets from the developed economies have become integrated in the short-run after the implementation of the Maastricht treaty compared to the pre-Maastricht treaty era. The results also show that the U.K stock market shows high correlation with the U.S stock market both before and after the implementation of the treaty and that correlation with other European Union economies, increased after the treaty. The co-integration results for the pre-Maastricht treaty period showed 2 co-integrations among the variables but there was no evidence of co-integration after the implementation of the treaty. However, when test was carried out for the whole study period, the results showed 1 co-integration among the sample country indices. The implication from the above results shows that diversification benefits for international investors wishing to invest into these developed markets especially in the short-run should expect reduced gains. However, long-term diversification benefits are possible as long as the correlations between these markets are low.
Forecasting a financial time series, such as stock market trends, would be a very important step when developing investment portfolios. This step is very challenging due to complexity and presence of a multitude of factors that may affect the value of certain securities. In this research paper, we have proved by contradiction that the Nigerian stock market is not efficient but chaotic. Two years representative stock prices of some banks stocks were analyzed using a feed forward neural network with back-propagation in Matlab 7.0. The simulation results and price forecasts show that it is possible to consistently earn good returns on investment on the Nigerian stock market using private information from an artificial neural network indicator.