Quantitative Risk Management
6:10pm–8:00pm
URIS HALL URI 303
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Quantitative Risk Management continues building your quantitative foundation in order to work with more advanced models and use mathematical and statistical intuition for building those models. At the end of this course, you will be able to use analytics algorithms for risk management; use factor models to assess the quality of investment portfolios and trader positions; hedge equity, option, and fixed-income portfolios using derivatives; estimate volatility with options models and GARCH models; and model ESG and Climate risk. The course is highly structured and organized by topic into semester long learning threads. Each week, readings and assignments will take another step forward along these threads: regression models, classification models, time series analysis, options and volatility modeling, fixed income modeling, factor models and portfolio management, tail risk modeling. These concepts will be demonstrated in python and students are expected to be able to understand and run python code.
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In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
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