BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
X-WR-TIMEZONE:America/New_York
PRODID:-//Apple Inc.//iCal 3.0//EN
CALSCALE:GREGORIAN
X-APPLE-CALENDAR-COLOR:#222222
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
SEQUENCE:711
DTSTART;TZID=America/New_York:20220929T170000
SUMMARY:Calibrating FX local volatility or leverage functions with standard Monte-Carlo simulations
DESCRIPTION:Speaker: Orcan Ogetbil, Director of Corporate Model Risk at Advanced Technologies of Modeling at Wells Fargo
Abstract
When building Cross-Currency local volatility models without or with stochastic volatility, one needs to determine local volatility or leverage functions that reprice given FX implied volatility surfaces under given interest rate models for both currencies. Standard approaches are to embed the repricing of the vanilla options in the model and use particle filters or to address the computation of the needed conditional expectations through PDE methods.
In this talk, we present alternative methods that can be directly implemented purely through local computations and standard MC simulations. Such methods could be more easily integrated within standard MC simulation frameworks, do not require the development of new code and methods, and also run in higher dimensions where PDE methods are no longer feasible. First, we will present the models covered. Second, we will present the conditional expectations to be computed, derived from extended Dupire’s formulas. Third, we will present how to compute such expectations through standard MC simulations (and regressions, for the leverage function). Finally, we will present numerical results from calibration and repricing with FX and interest rate market data from 2020. This is joint work with Narayan Ganesan and Bernhard Hientzsch.
Biography
Orcan Ogetbil is a director of Corporate Model Risk at Advanced Technologies of Modeling group within Wells Fargo. His work focuses on building and implementing mathematical finance models and tools for application in model validation space. During his tenure as a practitioner, Orcan studied pricing and risk models and methodologies associated with several asset classes, including equity, FX, fixed income, commodity and utilized them in valuation and validation testing. Orcan received his PhD in theoretical physics from Penn State University with his research specializing in deSitter solutions of N=2 supergravity. In his spare time, Orcan enjoys traveling with his boys, playing with his band, and long distance running.
September 29, 20225 pm – 6 pmBabbio 503
DTEND;TZID=America/New_York:20220929T180000
END:VEVENT
END:VCALENDAR