PREDICTION OF NAIRA TO DOLLAR RATE USING MACHINE LEARNING

ABSTRACT

This research investigates the application of machine learning models for predicting the NairaDollar exchange rate. The project explores the effectiveness of various models, including Linear Regression, Support Vector Machines, and Artificial Neural Networks, in capturing the complex relationship between economic factors and exchange rate fluctuations. Historical data on exchange rates and relevant economic indicators (interest rates, inflation rates, oil prices) are utilized to train and evaluate the models. The performance of each model is assessed using established metrics like R-squared score and Mean Absolute Error. Additionally, the impact of incorporating economic factors on model accuracy is analyzed. The findings highlight the potential benefits of leveraging machine learning for exchange rate prediction. The ability to generate accurate forecasts offers advantages for various stakeholders, such as businesses, investors, and financial institutions. These predictions can inform investment decisions, enhance financial planning, and contribute to economic research and analysis. The project also acknowledges the limitations encountered, including data availability and model interpretability. Future research directions are proposed, focusing on tackling these challenges and exploring advanced techniques like real-time data integration and regional model customization. Overall, this project contributes to a better understanding of the applicability of machine learning for predicting the Naira-Dollar exchange rate. The developed model holds promise for promoting informed decision-making within the financial sector, potentially leading to increased financial stability and growth.