Open Access ISSN: 2375-4389 Journal of Global Economics Research Article Volume 8:2, 2020 DOI: 10.37421/economics.2020.8.345 Cointegrating Relationship between Macroeconomic Variables and Stock Market Prices in Nairobi Securities Exchange Abstract The study of stock market prices 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 rule are affected by the investor’s psychology which exerts influence on the macroeconomic events. The very 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 paper was to analyze cointegrating relationship between macroeconomic indicators and the stock market prices in the context of Nairobi Securities Exchange. The paper used longitudinal research design using monthly secondary data for the period 2005 to 2018. The data were sourced from NSE, KNBS and Central Bank of Kenya. Augmented Dickey Fuller test confirmed the presence of unit root at levels for some variables, and all the variables attained stationarity after first difference. The Optimum lag length selected was 3. Johansen cointegration test showed that the variables were cointegrated thus Vector Error Correction Model was used to estimate the parameters. The error correction term was -1.1804 and significant at p-value 0.000 indicating a long-term existence between variables and the stock market prices. Jarque-Bera test showed the residuals followed normal distribution. Inflation and interest rate negatively and significantly affected stock market prices at coefficient -0.8371 (p-value 0.005) and -4.0876 (0.000) respectively. However, Exchange rate and nominal GDP had positive and significant effects on stock prices at 0.0001 (p-value=0.012) and 0.00002 (p-value=0.000) respectively. It was recommended based on the findings that the government should adopt expansionary monetary policy to by regulating interest rate and stabilizing exchange rate to create more money for investors. There is need for the government to encourage activities that increases GDP since it is an important macroeconomic indicator for health economy. Keywords: Cointegration • Unit root • VECM • Economy Cornelius Kiprono Serem*, Ernest Saina and Alfred Serem Department of Economics, Moi University, Kenya *Address for Correspondence: Cornelius Kiprono Serem, Department of Economics, Moi University, Kenya, E-mail: Cornelius.serem@outlook.com Copyright: © 2020 Serum CK. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received 14 January 2020; Accepted 19 May 2020; Published 26 May 2020 Introduction Engle and Granger coined the term cointegration that variables are cointegrated if they possess a stochastic trend in the long run. In economic models, the concept of cointegration is commonly associated with economic theories that shows economic relationship between time series variables for instance purchasing power parity implies that there is long term relationship between mon ey income, prices and interest rate and in the Fisher presentation shows that there is long term association between interest rate and the rate of inflation [1]. In financial economics, cointegration relationship ranges from high frequency relation to low frequency. In high frequency levels the concept of cointegration is motivated by arbitrage arguments and the law of one price implies that assets must sell at the same unit price to avoid arbitrage opportunities and in this case, the cointegration between prices of the trading assets. Similarly, the arbitrage arguments of markets imply that there exist a cointegration between current and future market prices. Thus, the cointegrating relationship in these association is defined as the long-term relationship due to the fact the forces in this relationship adjusts the deviation to bring the system into equilibrium long term relationship. Cointegration have been modelled using long spans and low frequencies time series data that is normally measured annually, bi-annually, quarterly or monthly. Two time series X t and Y t are said to be cointegrated if either one of them is I (1). That is, if there is a randomness but its linear combination is integrated of order zero denoted as 1(0) according to Herlemont. This implies that these variables X t and Y t are not cointegrated and in the long run they become cointegrated and no longer assume their random nature but assume a common path [2]. The security market is a crucial institution for a country’s economy. It is the market that deals with the exchange of securities issued publicly by listed firms and the government bonds. It is crucial in the sense that it greatly determines the performance of an economy. For any government, the nature and the state of a stock market is of great concern. Under general equilibrium, it is agreed that the stock market plays a very important role in collecting and efficiently allocating funds. Stock market through investment fund collections, and maturity transformation and savings mobilization are required to meet two or more basic requirements of supporting industrialization and ensuring that environment is safe and efficient in discharging their functions. Economic reform programs such as privatization, liberalization have not been completed or rather in the process of completion in most emerging economy. In this case, the prevailing knowledge of the relationship between prices of stock and macroeconomic variables for instance consumption, GDP, industrial production investment is predominantly important by the fact that a stable relationship between these variables is most likely to reform postulated economic models. Literature Review 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. According to Chen et al, multi-factor models have been developed as an explanation for the variation in security returns and the extant literature suggests that a wide range of factors explain security returns. The variations have been attributed to such variables as goods