6:00 PM Seminar Begins
7:30 PM Reception
Hybrid Event:
Fordham University
McNally Amphitheater
140 West 62nd Street
New York, NY 10023
Free Registration!
For Virtual Attendees: Please select Virtual instead of member type upon registration.
Abstract:
Using the path-integral formalism we develop an accurate and easy-to-compute semi-analytical approximation to transition probabilities and Arrow-Debreu densities for arbitrary diffusions. We illustrate the accuracy of the method by presenting results for the Black-Karasinski model for which the proposed approximation provides remarkably accurate results, even in regimes of high volatility and for multi-year time horizons. The accuracy and the computational efficiency of the proposed approximation makes it a viable alternative to fully numerical schemes for a variety of applications, ranging from maximum-likelihood estimation in econometrics to derivatives pricing.
Bio:
Luca runs Quantitative Strategies (QS) at UBS for the Non-Core and Legacy division. Previously to this role, Luca ran QS Credit at Credit Suisse. Luca’s best-known contribution is his work on Adjoint Algorithmic Differentiation (AAD), for which he holds a US Patent. Luca is an adjunct professor at Columbia University and Baruch College, and an assistant editor of the journal Quantitative Finance. Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in the field of high-temperature superconductivity. Luca holds an M.Sc. and Ph.D (honors) in Theoretical Physics.
