International Journal of Economics and Financial Issues (Oct 2024)

An Econometric Analysis of Inflation, Exchange Rate, and Interest Rate on Stock Market Performance in South Africa

  • Maake Trecy,
  • Semosa Donald,
  • Ogujiuba Kanayo,
  • Lethabo Maponya

DOI
https://doi.org/10.32479/ijefi.17095
Journal volume & issue
Vol. 14, no. 6

Abstract

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The stock market is crucial for resource production, distribution, and mobilization because it provides listed firms with long-term funding. Despite the extensive research on the relationship between inflation and exchange rates, the influence of interest rates on stock market performance has received limited investigation. The goal of this study is to address this gap by examining extensive South African data spanning from the first quarter of 2010 to the fourth quarter of 2022. The study constructs a sample space of 48 quarters, utilizing the JSE All Share Price Index as a substitute for measuring stock market performance. Furthermore, it incorporates additional macroeconomic data from reputable sources like the Federal Reserve Bank of St. Louis and the South African Reserve Bank. We employ the auto-regressive distributed lag (ARDL) model to examine the relationship between the stock prices of the Johannesburg Stock Exchange (JSE) and various variables, including inflation, interest rates, and exchange rates. The unit root test results indicate that the exchange rate integrates at order zero (I(0)), while the share price index, inflation, and interest rate integrate at order one (I(1)). The model explains roughly 96.5% of the variability in the dependent variable. According to the findings, short-term interest rates have a significant and negative impact on the Johannesburg stock market’s performance. However, the study does not demonstrate the significant effects of exchange rates and inflation. Furthermore, the Granger causality test has proven that the independent factors have no ongoing impact on the dependent variable. Without establishing the generalizability of the findings outside these boundaries, the study limits its conclusions to South Africa and the studied period. Different methods, as the quantile autoregressive distributed lag (QARDL) or the non-linear autoregressive distributed lag (NARDL) methodology, could be used in future studies to look into these relationships. These studies could also look at other factors that affect stock market performance. These insights may help policymakers adopt the most effective monetary or fiscal policies and support investors in making well-informed decisions to diversify their portfolios and minimize risks.

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