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Explore the intersection of artificial intelligence and finance in this 35-minute seminar that examines how machine learning can be effectively applied to financial problems. Learn why directly applying existing machine learning models to finance is insufficient and discover specialized approaches needed for financial applications. Delve into key research areas including tail modeling and risk management, portfolio optimization, and financial derivatives pricing. Understand the unique characteristics of machine learning in finance and how traditional models must be adapted for financial contexts. Examine advanced machine learning concepts such as uncertainty quantification and out-of-distribution (OOD) generalization, and their relevance to financial modeling. Gain insights from research that spans both finance and machine learning domains, covering topics from empirical asset pricing to consumer credit analysis. Access comprehensive materials including video recordings and presentation slides to reinforce your understanding of this interdisciplinary field that combines FinTech innovation with rigorous data science methodologies.
