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Aug 15, 2026
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2026-2027 University Catalog
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FIN 63000 - Financial Machine Learning
Credit Hours: 2.00. This course explores the use of modern data-driven methods in finance. Students apply programming-based techniques to financial data to examine market behavior, risk, and expected returns. The course emphasizes empirical analysis and critical evaluation of results.
Learning Outcomes
1. Identify key drivers of returns and risk in financial markets using data-driven and machine learning-based approaches.
2. Demonstrate the ability to apply forecasting, factor modeling, and portfolio construction techniques to real financial data using programming-based tools.
3. Outline the strengths, limitations, and appropriate use of alternative modeling approaches, including issues related to overfitting and model selection.
4. Develop an empirical analysis that integrates financial theory, data, and machine learning methods to address finance-related research or applied question.
5. Criticize empirical results and model outputs by interpreting them in an economic and financial context and assessing their robustness and practical relevance.
Credit Hours: 2.00
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