Modelling the impact of oil prices on stock prices in Kenya
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The purpose of the study is to model the impact of oil prices on stock prices in Kenya using monthly data for between 2003 and 2015. The study uses the Johansen's multivariate cointegration test and the vector error correction model (VECM). The Johansen's cointegration test shows that the variables are cointegrated with at most one cointegrating vector and the cointegration estimate reveals that oil prices have a significant relationship with stock prices in the long-run in Kenya. The VECM model reveals that in the short-run, oil prices have a significant influence on stock prices. Similarly, in the long-run, the study finds that oil prices have a negative effect on stock prices in Kenya. To address the impact of oil price shocks on stock prices, the study uses impulse response and variance decomposition analysis. The impulse response results show that oil price shocks cause an immediate decline in stock prices. On the other hand, the cumulative effects of oil price shocks account for 9.02% of the variation in stock prices in the long-run. The study recommends policymakers, financial analysts and shareholders to take into consideration the effects of oil prices in their financial decisions given the significant impact of oil prices on stock prices in Kenya.