Credit valuation adjustments (CVAs) are accounting adjustments made to reserve a portion of profits on uncollateralized financial derivatives. They are charged by a bank to a risky (capable of default) counterparty to compensate the bank for taking on the credit risk of the counterparty during the life of the transaction. These most common transaction types are interest rate derivatives, foreign exchange derivatives, and combinations thereof. The reserved profits can be viewed mathematically as the net present value of the credit risk embedded in the transaction.

In financial mathematics one defines CVA as the difference between the risk-free portfolio value and the true portfolio value that takes into account the possibility of a counterparty's default. In other words, CVA is the market value of counterparty credit risk. This price depends on counterparty credit spreads as well as on the market risk factors that drive derivatives' values and, therefore, exposure. CVA is one of a family of related valuation adjustments, collectively xVA; for further context here see Financial economics § Derivative pricing.

Unilateral CVA is given by the risk-neutral expectation of the discounted loss. The risk-neutral expectation can be written as

where   is the maturity of the longest transaction in the portfolio, is the future value of one unit of the base currency invested today at the prevailing interest rate for maturity , is the loss given default, is the time of default, is the exposure at time , and is the risk neutral probability of counterparty default between times and .[1] These probabilities can be obtained from the term structure of credit default swap (CDS) spreads.

More generally CVA can refer to a few different concepts:

According to the Basel Committee on Banking Supervision's July 2015 consultation document regarding CVA calculations, if CVA is calculated using 100 timesteps with 10,000 scenarios per timestep, 1 million simulations are required to compute the value of CVA. Calculating CVA risk would require 250 daily market risk scenarios over the 12-month stress period. CVA has to be calculated for each market risk scenario, resulting in 250 million simulations. These calculations have to be repeated across 6 risk types and 5 liquidity horizons, resulting in potentially 8.75 billion simulations.[2]

Exposure, independent of counterparty default

Assuming independence between exposure and counterparty's credit quality greatly simplifies the analysis. Under this assumption this simplifies to

where is the risk-neutral discounted expected exposure (EE):


Full calculation of CVA is done via Monte-Carlo simulation of all risk factors which is very computationally demanding. There exists a simple approximation for CVA which consists in buying just one default protection (Credit Default Swap) for amount of NPV of netted set of derivatives for each counterparty.[3]

Function of the CVA desk and implications for technology

In the view of leading investment banks, CVA is essentially an activity carried out by both finance and a trading desk in the Front Office. Tier 1 banks either already generate counterparty EPE and ENE (expected positive/negative exposure) under the ownership of the CVA desk (although this often has another name) or plan to do so. Whilst a CVA platform is based on an exposure measurement platform, the requirements of an active CVA desk differ from those of a Risk Control group and it is not uncommon to see institutions use different systems for risk exposure management on one hand and CVA pricing and hedging on the other.

A good introduction can be found in a paper by Michael Pykhtin and Steven Zhu.[4] Karlsson et al. (2016) present a numerical efficient method for calculating expected exposure, potential future exposure and CVA for interest rate derivatives, in particular Bermudan swaptions.[5]

See also


  1. ^ "EBA Report on CVA" (PDF). EBA. 25 February 2015. Archived from the original (PDF) on 2015-06-07.
  2. ^ Alvin Lee (17 August 2015). "The Triple Convergence Of Credit Valuation Adjustment (CVA)". Global Trading.
  3. ^ "Simple Derivatives CVA Calculation Example (Credit valuation adjustment) excel". 7 October 2013.
  4. ^ A Guide to Modeling Counterparty Credit Risk, GARP Risk Review,July–August 2007 Related SSRN Research Paper
  5. ^ Patrik Karlsson, Shashi Jain. and Cornelis W. Oosterlee. Counterparty Credit Exposures for Interest Rate Derivatives using the Stochastic Grid Bundling Method. Applied Mathematical Finance. Forthcoming 2016. [1]