This study investigates the predictive relationship between market microstructure and price efficiency in the Nigerian stock market using time series analysis over the period 1995–2023. Market microstructure, operationalized through bid-ask spread, trading volume, and market depth, is examined as a determinant of price efficiency, measured by the variance ratio test statistic. The study employs an Autoregressive Distributed Lag (ARDL) bounds testing approach, controlling for gross domestic product per capita growth rate, inflation rate, population growth rate, trade openness, institutional quality proxied by the corruption perception index, natural resource dependence measured as oil revenue to total revenue ratio, human capital proxied by life expectancy, and infrastructure development captured through access to electricity. Results from the time series regression reveal that bid-ask spread exerts a statistically significant negative effect on price efficiency in both the short run and the long run, while trading volume and market depth positively predict improvements in price efficiency. Among the control variables, GDP per capita growth, trade openness, institutional quality, and infrastructure development demonstrate significant positive associations with price efficiency, whereas natural resource dependence and inflation rate exhibit negative effects. Post-estimation diagnostics confirm the stability, normality, and serial correlation-free nature of the estimated model. The findings contribute to the growing body of literature on market microstructure in emerging markets by providing granular, time-varying evidence from Nigeria—a frontier market characterized by structural peculiarities that distinguish it from developed economies. The study recommends targeted regulatory interventions to enhance market transparency, reduce transaction costs, and strengthen institutional frameworks as pathways to improving informational efficiency in the Nigerian capital market.
Building similarity graph...
Analyzing shared references across papers
Loading...
Onipe Adabenege Yahaya
Nigerian Defence Academy
Building similarity graph...
Analyzing shared references across papers
Loading...
Onipe Adabenege Yahaya (Fri,) studied this question.
www.synapsesocial.com/papers/69bf89a9f665edcd009e982f — DOI: https://doi.org/10.5281/zenodo.19140525