Fast Greeks: Case of Credit Valuation Adjustments
Summary
(Counterparty) Credit Valuation Adjustments (CVA) has become a prevailing form
of pricing default risk on over-the-counter (OTC) contracts. Due to the large size
of portfolios included in the CVA calculation and its computational complexity,
large computing grids are needed for the evaluation.
The main purpose of this thesis is to investigate an even more computationally
demanding problem, namely computing the sensitivities of CVA to the market
and model parameters, a topic which was hardly addressed in the literature so far.
We show that the pathwise sensitivities method can be applied for CVA and that
it gives significant speed improvement over the conventional finite-differencing
techniques. Additionally, we take advantage of the GPU technology to obtain the
Greeks fast enough for daily hedging and risk management activities.