CFEM & UBS AI & Data Research Seminars: Michael Ludkovski (UC Santa Barbara)

Description

Don't miss our last speaker for the spring semester! It is our pleasure to host Michael Ludkovski (UC Santa Barbara) for the CFEM and UBS AI & Data Research Seminar on Tuesday, April 23rd. Please join us for an enlightening discussion on "Gaussian Process Models: From Option Greeks to Stochastic Impulse Control."

This webinar is free and open to all. Registration is required (RSVP). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from no-reply@zoom.us). 

Abstract:  In the first half of the talk I will survey Gaussian Process (GP) models which offer a flexible probabilistic framework for functional approximation and interpolation. GP training, kernel selection and observation noise modeling will be covered. The second half will consist of two applications: (i) statistical learning and uncertainty quantification of derivative contract sensitivities using GP gradients; (ii) GP surrogates for value- and policy-approximation within the Regression Monte Carlo framework for stochastic control problems.  

Speaker Bio:  Mike Ludkovski is a Professor of Statistics and Applied Probability at University of California Santa Barbara where he co-directs the Center for Financial Mathematics and Actuarial Research. Among his research interests are Monte Carlo techniques for optimal stopping/stochastic control, modeling of renewable energy markets, Gaussian process models for quantitative finance, and mortality analysis. His research has been supported by NSF, DOE, ARPA-E and CAS.  He holds a Ph.D. in Operations Research and Financial Engineering from Princeton University and has held visiting positions at London School of Economics and Paris Dauphine University.