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Title: Stochastic models for valuation and risk management of credit-sensitive hybrid derivatives
Author: Pede, Nicola
ISNI:       0000 0004 7658 5797
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2018
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We investigated different ways to model the dependence between the credit and other market risk components in hybrid derivatives. To do so, we used both structural and reduced-form frameworks for credit risk modelling. In particular, we applied results from Analytically Tractable First-Passage (AT1P) model - a model belonging to the family of structural approaches - to the pricing of Contingent Conversion bonds and a reduced- form approach to the pricing of quanto Credit Default Swaps (CDS). With respect to the former problem, we proposed a method to incorporate regulatory capital information into an AT1P-based model. With respect to the latter, we showed how to derive coupled two-dimensional PDE systems to price quanto CDSs in reduced form approaches. Furthermore, we investigated the impact of jumps to default on the FX/credit dependence structure, arguing that this is necessary mechanism to explain the observed quanto CDS spreads on Italian Republic during the Euro-debt cri- sis of 2011-2012. We proved that an invariance property of the FX rate with respect to replacing it with its reciprocal rate is satisfied by our proposed, jump-to-default / diffusion, model. Finally, we applied both approaches to Credit Valuation Adjustment (CVA) estimation, where we discussed the modelling-choice impact on the wrong-way risk estimation.
Supervisor: Brigo, Damiano Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral