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Vol 3 No 4 (2025)

  • AI-Driven Currency Forecasting in Emerging African Economies: Risks of Algorithmic Dependence

    Suleiman Ibrahim Roba, Maxwell Muthini Kyalo

    Artificial Intelligence (AI) has become one of the defining technologies of the 21st century. Despite growing attention to AI applications in currency forecasting, there remains a scarcity of research on African contexts. Specifically, the risks of algorithmic dependence have been underexplored in the African financial policy literature, even as reliance on foreign-developed technologies accelerates. Therefore, this study sought to examine the risks of algorithmic dependence in AI-driven currency forecasting in emerging African nations. The study was grounded in dependency theory. In addition, the study relied on a convergent mixed-methods design. The study gathered secondary data and primary data from 60 key informant interviews (KIIs) with central bankers, fintech practitioners, analysts, and academics from four African nations (Kenya, Egypt, Nigeria, and South Africa). Four risks emerged as primary concerns: limited accountability (22/60; 36.7%), data bias and misrepresentation (16/60; 26.7%), erosion of institutional capacity (13/60; 21.7%), and geopolitical dependence (9/60; 15.0%). The findings revealed that algorithmic dependence is both a technical vulnerability and a socio-political phenomenon that reproduces external epistemic authority and geo-economic asymmetries. Therefore, this study concludes that the promise of AI-driven currency forecasting could turn into a new cycle of subordination in the global financial order if a context-sensitive AI adoption strategy is not implemented for currency forecasting in African states.

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  • Oil Price Shocks and Stock Market Reactions: Insights from Impulse Response Functions

    Tam Phan Huy, Quan Do Anh, Long Pham Phuc, The Trinh Ngoc, Duc Nguyen Thanh

    This research aims to analyze the impact of oil price shocks on stock market indices using the VECM. The data spans from January 1, 2000, to December 31, 2023, capturing both short-term dynamics and long-term equilibrium relationships. Key findings indicate that oil price shocks significantly influence stock market indices, with varying impacts across different regions. For instance, Japan and Vietnam exhibit stronger negative effects compared to other regions. The results also reveal differences in the speed of adjustment towards long-term equilibrium, highlighting varying levels of market efficiency. The Johansen cointegration test results reveal significant long-term equilibrium relationships between oil prices and stock market indices, underscoring the interconnected nature of these variables. The study concludes that oil prices are a critical factor in stock market performance, underscoring the need for informed strategies by investors, corporate managers, and government agencies to mitigate risks and capitalize on opportunities. These insights are crucial for understanding the interconnected nature of global financial markets and developing effective risk management strategies.

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