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Macro-Economic Factors Affecting Stock Market Performance in Zambia: A Case of the Lusaka Securities Exchange

Author

Listed:
  • Muyinda P. Muyanga

    (Institute of Distance Education, University of Zambia)

  • Jason Mwanza, PhD

    (Institute of Distance Education, University of Zambia)

  • Austin Mwange, PhD

    (Graduate School of Business, University of Zambia)

  • Lubinda Haabazoka, PhD

    (School of Business, University of Zambia)

Abstract

This study examined the influence of macroeconomic variables on stock market performance in Zambia using data from the Lusaka Securities Exchange. The study analyzed annual interest rates, exchange rates, money supply, GDP growth rate, and the Index of Industrial Production as independent variables against the All LuSE Share Index. Secondary data covering 1998–2017 were analyzed using multiple linear regression in SPSS. Results showed that the selected macroeconomic variables explained 81.9% of the variation in stock market performance. Interest rates had a significant negative effect on stock market performance, while money supply, exchange rates, and industrial production index exhibited positive significant relationships. GDP growth had a positive but statistically insignificant influence.

Suggested Citation

  • Muyinda P. Muyanga & Jason Mwanza, PhD & Austin Mwange, PhD & Lubinda Haabazoka, PhD, 2025. "Macro-Economic Factors Affecting Stock Market Performance in Zambia: A Case of the Lusaka Securities Exchange," African Journal of Commercial Studies, African Journal of Commercial Studies, vol. 6(5).
    • Handle: RePEc:cwk:ajocsk:2025-99
    DOI: 10.59413/ajocs/v6.i5.6
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    References listed on IDEAS

    as
    1. Jeffery A. Born & David H. Myers & William J. Clark, 2017. "Trump tweets and the efficient Market Hypothesis," Algorithmic Finance, IOS Press, vol. 6(3-4), pages 103-109.
    2. Meredith Beechey & David Gruen & James Vickery, 2000. "The Efficient Market Hypothesis: A Survey," RBA Research Discussion Papers rdp2000-01, Reserve Bank of Australia.
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