<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This study examines the dynamic impacts of oil prices on stock market development in four oil exporting sub-Saharan African countries in the period of 1989-2015. The Arbitrage Pricing Theory (APT) is used as the theoretical framework where stock market prices are hypothesized to be fully reflective of all available information. Static panel data (Pooled OLS, panel Fixed Effect Model, panel Random Effect Model) and dynamic panel model of Generalized Method of Moments (GMM) were employed in the estimation. The estimation of the static panel model shows that oil prices, exchange rates, gross domestic product, inflation and the corruption index have a positive and significant impact on stock market development. However, there is a slight improvement from the estimation of the GMM dynamic panel model which confirmed that oil prices, exchange rates, gross domestic product, investment, inflation and the corruption index have a positive and significant impact on stock market development. The study therefore recommends that investors in selected the Sub-Sahara Africa (SSA) stock market need to be cognizant of the varying impacts of macroeconomic indicators, particularly those that have been found to exert strong influence on stock returns like oil prices, exchange rates, inflation and the corruption index.</p></abstract>

This study examines the dynamic impacts of oil prices on stock market development in four oil exporting sub-Saharan African countries in the period of 1989-2015. The Arbitrage Pricing Theory (APT) is used as the theoretical framework where stock market prices are hypothesized to be fully reflective of all available information. Static panel data (Pooled OLS, panel Fixed Effect Model, panel Random Effect Model) and dynamic panel model of Generalized Method of Moments (GMM) were employed in the estimation. The estimation of the static panel model shows that oil prices, exchange rates, gross domestic product, inflation and the corruption index have a positive and significant impact on stock market development. However, there is a slight improvement from the estimation of the GMM dynamic panel model which confirmed that oil prices, exchange rates, gross domestic product, investment, inflation and the corruption index have a positive and significant impact on stock market development. The study therefore recommends that investors in selected the Sub-Sahara Africa (SSA) stock market need to be cognizant of the varying impacts of macroeconomic indicators, particularly those that have been found to exert strong influence on stock returns like oil prices, exchange rates, inflation and the corruption index.

Impact of Oil Prices on Stock Market Development in Selected Oil Exporting Sub-Saharan African Countries

Financial Internet Quarterly

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This study examines the dynamic impacts of oil prices on stock market development in four oil exporting sub-Saharan African countries in the period of...

Impact of Oil Prices on Stock Market Development in Selected Oil Exporting Sub-Saharan African Countries

Published Online: Jun 30, 2020

Page range: 1 - 13

Received: Mar 06, 2020

Accepted: May 06, 2020

DOI: https://doi.org/10.2478/fiqf-2020-0008

Keywords
Oil Price, Stock Market Development, Panel Data, Africa

© 2020 Adewale T. Muritala et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Impact of Oil Prices on Stock Market Development in Selected Oil Exporting Sub-Saharan African Countries

Published Online: Jun 30, 2020

Page range: 1 - 13

Received: Mar 06, 2020

Accepted: May 06, 2020

DOI: https://doi.org/10.2478/fiqf-2020-0008

KeywordsOil Price, Stock Market Development, Panel Data, Africa

© 2020 Adewale T. Muritala et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Oil Price, Stock Market Development, Panel Data, Africa