MACROECONOMIC DETERMINANTS OF STOCK MARKET CAPITALIZATION IN AFRICA'S MOST DEVELOPED FINANCIAL SECTOR: A BAYESIAN APPROACH

Abstract

This research investigates the macroeconomic determinants of market capitalization within South Africa, the most developed financial sector in Africa, over the period from 1985 to 2022. The study is pertinent as it evaluates various models to identify the variable combinations that most significantly impact stock market performance in South Africa. The Bayesian information criterion was employed for determining the prior distribution for regression coefficients, while a Bernoulli distribution (p = 0.5) was utilized for the prior distribution on the models. The Markov Chain Monte Carlo (MCMC) algorithm was used for sampling in performing the posterior Bayesian inference on the parameters. Additionally, the Cochrane-Orcutt AR (1) regression technique was implemented for further evaluation. Empirical results from the Bayesian analysis indicate that the model including gross domestic product (GDP) and the repo rate most effectively influences the market capitalization of listed domestic companies in South Africa. Conversely, the Cochrane-Orcutt AR (1) regression reveals that broad money growth and GDP positively and significantly impact market capitalization, whereas repo rates and trade openness have a significant negative effect. The study concludes that effective management of the real and monetary sectors is crucial for market capitalization. It is recommended that the government create a macroeconomic environment conducive to minimizing business activity costs. Simultaneously, the South African Reserve Bank (SARB) should foster an effective transmission mechanism for repo rates that aligns with reduced capital costs and enhanced productivity.