CVA with Greeks and AAD
Calculating CVA is a daunting task. Here, Adil Reghai, Othmane Kettani and Marouen Messaoud introduce a new approach for CVA valuation in a Monte Carlo setting using adjoint algorithmic differentiation. They take advantage of the duality relationships between parameter and hedging sensitivities combined with the martingale representation theorem to calculate CVA in an efficient manner
Since the outbreak of the financial crisis, it has become apparent that counterparty credit risk can no longer be ignored and should be priced: this is the purpose of credit valuation adjustment (CVA). CVA is now of paramount importance in the financial industry, becoming a focus for not only practitioners and regulators but also for academics. One only has to look at the fast-growing literature
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
More on Banking
Neural networks unleashed: joint SPX/VIX calibration has never been faster
SPX and VIX options can be jointly calibrated in real time with deep neural networks
Bridging credit transitions and spread dynamics
A fast-to-calibrate model to simulate a credit rating transition matrix is presented
Floating exercise boundaries for American options in time-inhomogeneous models
A pricing model is extended to account for negative interest rates or convenience yields
The relative entropy of expectation and price
The replacement of risk-neutral pricing with entropic risk optimisation
The importance of modelling futures dynamics in commodity index derivatives
Index-based and underlying-based pricing methods for commodity derivatives are presented
AI as pricing law
A neural network tailored to financial asset pricing principles is introduced
Skewing the correlation in local and stochastic volatility frameworks via copulas
A copula-based model to capture correlation skew in multi-asset derivatives is presented
Capital-neutral securitisation risk weights
A closed-form formula to allocate capital to the tranches of a securitisation is presented
