Abstract:
The study of stock market price movements and macroeconomic indicators has been
imperative in view of the country’s economic growth because the most sensitive
segment of any developing economy is its stock market. The buy and sell decision
rules are affected by the investors’ psychology which exerts influence on the
macroeconomic events. The critical question when it comes to this is that how
instantaneous the information is transferred to the investors and market analyst and in
return, reflects on stock market prices. Therefore, the purpose of this research was to
analyze causal and cointegrating relationship between macroeconomic indicators and
the stock market prices in the context of Nairobi Securities Exchange, Kenya. The
study’s specific objectives were; to determine the relation between inflation, exchange
rate, interest rate, nominal gross domestic product and stock market prices. Further,
the study aimed at investigating the bidirectional Granger causal effect between the
selected variables in this study. Efficient Market Hypothesis, Arbitrage Pricing
Theory and Capital Asset Pricing Models theories guided this study. The study used
longitudinal research design and employed monthly secondary data for the period
2005 - 2018. The data was obtained from Nairobi Stock Exchange, Kenya National
Bureau of Statistic and Central Bank of Kenya. Descriptive statistics such as mean,
minimum, maximum and standard deviation were computed to understand the nature
of data and other general characteristics. Augmented Dickey Fuller, Philip Perron and
Clemente-Montañés-Reyes tests confirmed the presence of unit root at levels, and all
the variables attained Stationarity after first difference. The Optimum lag length
selected was 2. Johansen’s cointegration test showed that the variables were
cointegrated thus Vector Error Correction Model was estimated. The error correction
term was −1.1804 and significant at p − value 0.000 which indicated a long-term
relationship among. Jarque-Bera test showed the residuals followed normal
distribution. There was no serial correlation among the variables as per Durbin
Watson statistic(DW − Stat 2.022 < 4). Inflation and interest rate was found to
negatively and significantly affect stock market prices with coefficients of
−0.8371 (p − value 0.005) and -4.0876 (p − value 0.000) respectively. However,
exchange rate and nominal gross domestic product had positive and significant effects
on stock prices at 0.0001 (p − value = 0.012) and 0.00002 (p − value =
0.000) respectively. It is recommended based on the findings that the government
should adopt expansionary monetary policy to enhance credit creation and curb
interest rate by stabilizing exchange rate changes thus promoting investment in stocks
and shares. There is need for the government to encourage activities that increases
gross domestic product since it is an important macroeconomic indicator for health
economy.