Algorithmic Exposure and CVA for Exotic Derivatives

31 Pages Posted: 18 Nov 2011 Last revised: 14 Apr 2012

Date Written: November 17, 2011

Abstract

We develop the algorithmic approach for Counterparty exposure calculation and automate its application to arbitrary complicated instruments. Assuming that the portfolio is priced by the backward (American) Monte-Carlo method, our approach allows calculating the credit exposure as a pricing by-product, essentially without modifications in the usual pricing procedure.

In particular, for the exposure calculation of callable instruments we manage to avoid a cumbersome aggregation of exercise indicators, applying them sequentially in parallel with the main pricing.

We explain how the obtained exposure can be integrated into the Credit Valuation Adjustment (CVA), based on the extension of the pricing model with a Counterparty credit component.

The presented approach to the exposure computation is formulated in an arbitrary probability measure. To perform the measure change we use the cross-currency model semantics and calibrate the model to the real-world measure using indexes projections.

Keywords: Credit Exposure, Credit Valuation Adjustment, CVA, American Monte Carlo, backwards pricing, exotic detivatives

JEL Classification: C1, C3, C5, C6

Suggested Citation

Antonov, Alexandre and Issakov, Serguei and Mechkov, Serguei, Algorithmic Exposure and CVA for Exotic Derivatives (November 17, 2011). Available at SSRN: https://ssrn.com/abstract=1960773 or http://dx.doi.org/10.2139/ssrn.1960773

Alexandre Antonov (Contact Author)

Abu Dhabi Investment Authority ( email )

211 Corniche Road
Abu Dhabi, Abu Dhabi PO Box3600
United Arab Emirates

ADIA ( email )

211 Corniche
abu Dhabi
United Arab Emirates

Serguei Issakov

Numerix ( email )

99 Park Avenue, 5th Floor
New York, NY 10016
United States

Serguei Mechkov

Numerix ( email )

99 Park Avenue, 5th Floor
New York, NY 10016
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
2,248
Abstract Views
8,537
Rank
12,445
PlumX Metrics