Abstract
─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