No abstract

Debate on the stochastic behaviour of stock market returns, 3-month Treasury Bills rate, lending rate and their cointegrating residuals remains unsettled. This study examines the stochastic properties of the macroeconomic variables, stock market returns and their cointegrating residuals using an Autoregressive Fractionally Integrated Moving Average (ARFIMA) model. It also investigates Granger causality between the two measures of interest rate and stock market returns. The study uses monthly data from 1st January 1993 to 31st December 2015. The results indicate that the 3-month Treasury Bills rate, lending rate and stock market returns are fractionally integrated which implies that shocks to the variables persist but eventually disappear. The results also reveal that the cointegrating residuals are fractionally integrated which suggests that a new and harmful long-run equilibrium might be established when each of the measures of interest rate is driven away from stock market returns. Additionally, the results indicate that the 3-month Treasury Bills rate and lending rate negatively Granger cause stock market returns in the long run. This suggests that stocks and Treasury Bills are competing investment assets. On the other hand, ARFIMA-based Granger causality reveals that stock market returns lead the 3-month Treasury Bills rate and lending rate with a negative sign in the short run. This implies that a prosperous stock market results into a favorable macroeconomic environment. A key contribution of this study is that it is the first to empirically examine fractional cointegration and ARFIMA-based Granger Causality between interest rate and stock market returns in Kenya.

The moderating effect of events such as the 2008 Global Financial Crisis (GFC) on the relation between stock market returns and macroeconomic variables has attracted very little attention. This study investigates the extent to which the 2008 GFC moderated the relationship between inflation rate and stock market returns. The study uses month-onmonth inflation rate and year-on-year inflation rate from 1st January 1993 to 31st December 2015 and divides the sample data into pre-crisis period (from 1st January 1993 to 31st December 2007); crisis period (from 1st January 2008 to 30th June 2009); and post-crisis period (from 1st July 2009 to 31st December 2015). It uses a product-term regression model instead of the most widely applied additive regression model. Results indicate that a unit increase in the both measures of inflation rate had significant depressing effects on stock market returns after the crisis compared to before the crisis. Likewise, the results reveal that average stock market returns were significantly higher after the crisis compared to before the crisis at low rather than medium or high values of the two measures of inflation rate. These results suggest that the Kenyan stock market is highly sensitive to variations in inflation rate, especially as it emerges from a financial or political turmoil. This study is empirically innovative in the sense that it is the first to examine the moderating effect of the 2008 GFC on the relation between inflation rate and stock market returns in Kenya using a product-term model.