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Quantitative Data Analysis in Finance

FIN 580

1224
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The course gives a broad introduction to the techniques of machine learning, and places those techniques within the context of computational finance. Topics include parametric and non-parametric regression, and supervised learning techniques. Methods covered include regularized linear models in high dimensions (LASSO family), Ensemble methods (Bagging and Boosting), Regression Trees/Random Forests/Boosted Trees, Neural Networks/Deep Learning, Classification methods, Clustering. We also discuss the implementation of dimension reduction techniques, including principal components analysis. Examples are taken from financial models.
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Section L01

Section P01

  • Type: Precept
  • Section: P01
  • Status: O
  • Enrollment: 24
  • Capacity: 50
  • Class Number: 40614
  • Schedule: M 06:00 PM-07:20 PM