Granger Causality between Macroeconomic Variables and Stock Market Prices at Nairobi Securities Exchange, Kenya
- April 3, 2020
- Posted by: RSIS
- Categories: Economics, IJRISS
International Journal of Research and Innovation in Social Science (IJRISS) | Volume IV, Issue III, March 2020 | ISSN 2454–6186
Cornelius Kiprono Serem1, Edwin Kipyego Kipchoge2, Silas Kiprono Samoei3
1Department of Economics, Moi University, Kenya
2Department of Mathematics and Computer Science, University Of Eldoret, Kenya
3Department of Agricultural Economics, Moi University, Kenya
Abstract: The concept of co integration as have been since the time of Adam Smith and is the central theme in his work, An Inquiry into the Nature and Causes of the Wealth of Nations, as it shows that one of the crucial application of economic theory is to give explanations to the link that exist between different causal relation among economic variables and the most critical question posed is how do economist relate the existence of causal relationship with a given number of observations. To answer this question, it is necessary to understand the concept of causality and its application in economics. This paper tried to find the bidirectional relationship of selected microeconomic variable and stock market prices. Before estimating Granger causality, variables were tested for stationarity using Philip Perron test in which variables were integrated upon first difference. The results showed that stock market prices granger caused exchange rate, inflation granger caused interest rate. There was also significant granger causality between nominal GDP and exchange rate and on the relationship between interest rate and nominal GDP. All these effects were unidirectional effects.
Key Words: Granger Causality, Stationarity, NSE, Kenya
I. INTRODUCTION
Statistical concept of pair wise was put forward by Granger (1981) is based on F-test which tries to explain the effects of changes in one variable has changes in another variable. It is said that there is granger causality between variables X and Y if the past values of X forecast the present values of Y. The term Granger causality does not imply that a change in one variable causes a change in another variables and it simply implies that there is correlation between past values of one variable and the past values of another variable.
There is a lot of cynics in regard to the relationship that exist between exchange rate, interest rate, inflation rate and GDP fluctuation variables and the financial performance of a firm in terms of its profitability and security returns. Some studies indicate significant relationships between the variables whereas some indicate insignificant relationship between the variables.
