This is the essential course for experienced risk managers who are responsible for a firm's value-at-risk (VaR) reporting or anyone who is about to purchase, implement, or design a VaR system. The course has two objectives:

To communicate the many practical challenges and pitfalls of implementing production VaR systems.

To sift through the vast literature on VaR to identify those sophisticated computational techniques that are useful in production VaR system.

Whether you implement a system internally or purchase one off the shelf, this course will teach you what you need to know

the practical realities of operating a production VaR system;

what computational techniques work and how to implement them;

simple things you can do today to significantly improve your VaR reporting; and

pitfalls to look out for.

Assuming familiarity with the basics of VaR, the course delves into the practical and theoretical issues that implementers and sophisticated users need to know.

Learn the mathematics of quadratic ("delta-gamma") value-at-risk. Explore the ins-and-outs of data sourcing and cleaning—especially in illiquid or OTC markets. Find out how to "fix" estimated covariance matrices that are not positive definite. Learn how to dramatically speed up Monte Carlo simulations—without sacrificing accuracy. Master the Cornish-Fisher expansion, copulas, principal component remappings, mixed probability distributions, and much more.

Instructor Glyn Holton is a leading authority on value-at-risk. All attendees receive a copy of his groundbreaking text Value-at-Risk: Theory and Practice in addition to other course materials.

Prerequisites for this course are completion of the Financial Math series of courses or prior knowledge of the math covered in those courses. You should also have some prior familiarity with value-at-risk. This course is for serious users.  If you want to dramatically expand your understanding of value-at-risk, this is the course for you.