References
Bank for International Settlements. (2022). Triennial Central Bank Survey of Foreign Exchange and OTC Derivatives Markets. https://www.bis.org Chen, Y., Li, X., & Zhao, W. (2022). Explainable AI for financial forecasting: Applications and challenges. Journal of AI Research, 74, 101–118. Nguyen, T., Tran, Q., & Hoang, P. (2022). LSTM-based models for currency prediction. International Journal of Computational Finance, 14(3), 55–70. Rahman, S., & Liu, H. (2023). Ensemble machine learning approaches for forex market trend prediction. Journal of Financial Technology, 9(2), 45–63. Zhao, F., & Wang, L. (2022). Hybrid deep learning and reinforcement learning in algorithmic trading. Expert Systems with Applications, 203, 117480. Alpha Vantage. (2025). Forex API documentation. https://www.alphavantage.co/ MetaTrader 5. (2025). Historical data platform. https://www.metatrader5.com Bank for International Settlements. (2022). Triennial Central Bank Survey of Foreign Exchange and OTC Derivatives Markets. https://www.bis.org Chen, Y., Li, X., & Zhao, W. (2022). Explainable AI for financial forecasting: Applications and challenges. Journal of AI Research, 74, 101–118. European Commission. (2023). Ethical guidelines for trustworthy AI. https://digital- strategy.ec.europa.eu Khan, M., Abbas, S., & Javed, H. (2023). Comparative evaluation of machine learning models for forex market prediction. Financial Data Science Review, 5(2), 44–59. Li, Y., & Zhou, P. (2023). Toward interpretable deep learning in financial time series prediction. AI and Finance Journal, 11(1), 65–81. Nguyen, T., Tran, Q., & Hoang, P. (2022). LSTM-based models for currency prediction. International Journal of Computational Finance, 14(3), 55–70. Okonkwo, C., & Ogu, E. (2023). Application of AI-driven systems in Nigerian financial markets. African Journal of Computational Intelligence, 7(1), 25–42. Rahman, S., & Liu, H. (2023). Ensemble machine learning approaches for forex market trend prediction. Journal of Financial Technology, 9(2), 45–63. Tran, M., & Le, D. (2022). Ensemble learning for currency volatility modeling. Computational Economics Letters, 8(4), 201–218. Wang, Y., & Li, H. (2022). Econometric modeling of exchange rate volatility in post-pandemic markets. Economic Modelling and Forecasting, 17(1), 33–52. Zhao, F., & Wang, L. (2022). Hybrid deep learning and reinforcement learning in algorithmic trading. Expert Systems with Applications, 203, 117480. Chen, Y., Li, X., & Zhao, W. (2022). Explainable AI for financial forecasting: Applications and challenges. Journal of AI Research, 74, 101–118. Khan, M., Abbas, S., & Javed, H. (2023). Comparative evaluation of machine learning models for forex market prediction. Financial Data Science Review, 5(2), 44–59. Nguyen, T., Tran, Q., & Hoang, P. (2022). LSTM-based models for currency prediction. International Journal of Computational Finance, 14(3), 55–70. Rahman, S., & Liu, H. (2023). Ensemble machine learning approaches for forex market trend prediction. Journal of Financial Technology, 9(2), 45–63. Tran, M., & Le, D. (2022). Ensemble learning for currency volatility modeling. Computational Economics Letters, 8(4), 201–218. Bank for International Settlements. (2022). Triennial Central Bank Survey: Foreign exchange turnover in April 2022. BIS Publications. Chen, H., Wu, D., & Singh, R. (2022). Enhancing forex prediction using hybrid deep learning models. IEEE Access, 10(1), 122340–122356. Li, J., & Huang, S. (2023). Temporal learning in volatile markets: LSTM networks for forex forecasting. Expert Systems with Applications, 223, 119871. Nguyen, M., Zhao, L., & Yeo, J. (2022). Machine learning approaches for financial time-series forecasting: A review. Applied Intelligence, 52(9), 9231–9252. Okonkwo, C., & Ogu, B. (2023). AI adoption and data-driven decision-making in Nigeria’s forex market. African Journal of Computing and ICT, 16(3), 44–59. Rahman, A., & Liu, T. (2023). Comparative analysis of AI-driven forex trading models. Journal of Computational Finance, 27(2), 87–104. Zhang, P., Lin, Y., & Ahmed, S. (2023). Explainable AI for trading: Improving trust and transparency. Journal of Financial Data Science, 5(1), 55–74.
