Oct 13, 2021 8:00 PM
Registration deadline: Oct 13, 2021

Libor Transition: Looking Forward to Backward-Looking Rates

by Dr. Fabio Mercurio - Global Head of Quant Analytics at Bloomberg | Online


Abstract: In this talk, we show how the generalized Forward Market Model (FMM) introduced by Lyashenko and Mercurio (2019) can be extended to make it a complete term-structure model describing the evolution of all points on a yield curve, as well as that of the bank account. The ability to model the bank account, in addition to the forward curve, is going to be of crucial importance once Libor rates are replaced with setting-in-arrears risk-free rates in derivative and cash contracts, where fixings are defined in terms of the realized bank account values.

To obtain the evolution of all points on the yield curve, we embed the FMM into a (finite-dimensional) Markovian Heath-Jarrow-Morton (HJM) model with separable volatility structure by aligning the HJM and FMM dynamics of the forward term rates modeled by the FMM. This FMM-aligned HJM model is effectively a hybrid between an instantaneous forward-rate model and a LMM, and shares the advantages of both approaches, with the caveat that the number of variables to simulate could be too high. A more efficient approach is then derived by expressing the price of an arbitrary zero-coupon bond, as well as the bank account, as a function of the modeled forward term rates and their volatilities.

Dr. Fabio Mercurio - Global Head of Quant Analytics at Bloomberg

Dr. Fabio Mercurio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU. He has jointly authored the book "Interest rate models: theory and practice" and published extensively in books and international journals, including 19 cutting-edge articles in Risk Magazine. Fabio is the recipient of the 2020 Risk quant of the year award.

Registration deadline: Oct 13, 2021

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