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Education

Ph.D., Economics, Northern Illinois University

M.S., Applied Probability and Statistics, Northern Illinois University

M.S., Applied Mathematics, Ohio University

M.S., Financial Economics, Ohio University

B.S., Economics, Abia State University

Biography

Dr. Ngwaba is a quantitative economist and financial risk scholar whose research lies at the intersection of financial economics, risk management, econometrics, and machine learning. His research focuses on developing innovative approaches to financial risk analysis and volatility forecasting.

Teaching

Dr. Ngwaba’s teaching philosophy emphasizes quantitative reasoning, analytical thinking, and practical application. He seeks to help students understand not simply how to use quantitative methods, but why those methods work, when they should be used, and how their results can inform real-world economic and financial decisions.

Scholarship

Ngwaba, C.A. (2025). HAR-RV-CARMA: A Kalman Filter-Weighted Hybrid Model for Enhanced Volatility Forecasting. Risks.

Ngwaba, C.A. (2025). Forecasting Covered Call Exchange-Traded Funds (ETFs) Using Time Series, Machine Learning, and Deep Learning Models. Journal of Risk and Financial Management.

Ngwaba, C. A. (2024). Broad-Based Black Economic Empowerment Policy and Entrepreneurship in South Africa. Journal of Developmental Entrepreneurship.

Ngwaba, C. A. (2023). Corporate taxes and FDI in developing economies. International Economics and Economic Policy.

Azizi, S., Ngwaba, C. A., & Ekhator-Mobayode, U. E. (2021). Can Machine Learning Predict Quantity and Duration of Migration to the USA?. The Journal of Prediction Markets.

Ngwaba, C. A., & Azizi, S. (2019). Effectiveness of tax reform on entrepreneurship. Journal of Entrepreneurship and Public Policy.

Student Involvement Opportunities

Academic and Thesis Advising – Advised over 50 actuarial science and economics students on course selection, degree requirements, exam preparation and research.