Parametric VaR
Connect expected returns, volatility, and the variance-covariance matrix with the assumptions behind a portfolio loss estimate.
Portfolio Risk / Simulation / Statistics
Value at Risk
Three ways to estimate portfolio losses. Understand parametric, Monte Carlo, and historical VaR—and when each method helps.
25OFF_TG_OCT_2026Offer ends November 6 (Eastern time)3VaR methodologies
5Focused lectures
TIM GLAUNERCourse instructor
Understand the estimate
Know what your risk number assumes.
For finance professionals, risk managers, and students who want a clear introduction to portfolio Value at Risk.
Monte Carlo VaR
Use simulated scenarios to build a distribution of possible portfolio outcomes.
Historical VaR
Understand how historical observations shape an estimate, and why clean, continuous data matters.
Five lectures
From definition to method selection.
- Introduction to Value at Risk
- Parametric Value at Risk (Variance-Covariance Approach)
- Monte Carlo Value at Risk
- Historical Value at Risk
- Pros and Cons of Each Methodology
October 2026 course offer
Build your portfolio risk vocabulary.
Lifetime access through Udemy. Prices in other currencies and applicable taxes are shown at checkout. Refunds are subject to Udemy's policy.