Exchange rate volatility and stock prices of companies listed on Nairobi securities exchange, Kenya
Kenya has experienced continuous exchange rate volatility since October 1993 when the fixed exchange rate regime was abolished and floatation of the Kenya shilling was introduced. The continuous volatility of exchange rate brings about increase in foreign exchange risk exposure which in turn leads to increase in transaction costs of companies. Higher transaction costs lower the expected earnings of companies which subsequently affect the market price of stocks hence, the value of companies and the investors’ wealth. Stock prices represent returns which investors expect from a given security. Hence, variables that cause stock prices to change are of importance to investors and the economy at large. Changes in stock prices and the trend of changes have always been of interest in the capital market given their effect on the stock market stability and strategies adopted by investors. The stock market plays a vital role of intermediation between borrowers and lenders hence uncertainty in the market impacts negatively to the economy. For the period 2007 to 2014, Kenya experienced high exchange rate volatilities which affected the performance of the Nairobi Securities Exchange. Stock market performance is key in determining if investors’ portfolio of stocks will bring adequate returns based on their expectations. Therefore, variables that influence the performance of the stock market are important to investors, stockbrokers, and the regulatory authorities. This study examined the interaction between foreign exchange market and the stock market in Kenya, with the aim of identifying the effect exchange rate volatility on stock prices of companies listed in Nairobi Securities Exchange. Further, the study sought to establish the moderating effect of selected monetary policy variables on the relationship between exchange rate volatility and stock price movement in Kenya. The study employed an explanatory non-experimental research design. A census of 61 companies listed in the Nairobi Securities Exchange, was taken. The study utilized monthly data for the period of 96 months from January 2007 to December 2014. Pairwise Granger causality test revealed that causality runs from exchange rate volatility to stock prices. Regression analysis results revealed the existence of statistically significant negative relationship between daily mean exchange rate, monthly mean exchange rate, and combined drivers of exchange rate volatility on stock prices of companies listed in Nairobi Securities Exchange. However, regression results revealed that inflation rate had insignificant negative relationship with stock prices. The moderating monetary policy variables were tested using the stepwise multiple regressions. Stepwise regression results revealed that there is significant moderating relationship between combined drivers of exchange rate volatility and stock prices of companies listed in the NSE. Therefore, monetary policy variables have a moderating effect on the relationship between drivers of exchange rate volatility and stock prices in Kenya. The study recommends that Capital Markets Authority should fast-track the establishment of Derivatives Exchange Market in Kenya. The derivative instruments help economic agents to improve their management of both market and credit risks hence increasing the market resilience to shocks. The establishment of derivatives market will further boost attraction of both domestic and foreign participation at the Nairobi Securities Exchange thereby benefiting all sectors of the economy. The study further recommends that portfolio managers should continually analyse the behaviour of foreign exchange market with a view to disposing of stocks in their holdings if they predict increased exchange rate volatility. Otherwise, portfolio managers should increase their holdings when they predict a decrease in exchange rate volatility. Most importantly, both regulatory bodies and corporate managers should make strategic decisions in consideration of all identified variables since these variables are not in isolation.