A computational approach to hedging Credit Valuation Adjustment in a jump-diffusion setting

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This study contributes to understanding Valuation Adjustments (xVA) by focussing on the dynamic hedging of Credit Valuation Adjustment (CVA), corresponding Profit & Loss (P&L) and the P&L explain. This is done in a Monte Carlo simulation setting, based on a theoretical hedging framework discussed in existing literature. We look at hedging CVA market risk for a portfolio with European options on a stock, first in a Black-Scholes setting, then in a Merton jump-diffusion setting. Furthermore, we analyze the trading business at a bank after including xVAs in pricing. We provide insights into the hedging of derivatives and their xVAs by analyzing and visualizing the cash-flows of a portfolio from a desk structure perspective. The case study shows that not charging CVA at trade inception results in an expected loss. Furthermore, hedging CVA market risk is crucial to end up with a stable trading strategy. In the Black-Scholes setting this can be done using the underlying stock, whereas in the Merton jump-diffusion setting we need to add extra options to the hedge portfolio to properly hedge the jump risk. In addition to the simulation, we derive analytical results that explain our observations from the numerical experiments. Understanding the hedging of CVA helps to deal with xVAs in a practical setting.

Original languageEnglish
Article number125671
Pages (from-to)1-21
Number of pages21
JournalApplied Mathematics and Computation
Volume391
DOIs
Publication statusPublished - 2021

Keywords

  • Computational finance
  • Counterparty credit risk (CCR)
  • Credit Valuation Adjustment (CVA)
  • Dynamic hedging
  • Merton jump-diffusion
  • xVA hedging

Fingerprint Dive into the research topics of 'A computational approach to hedging Credit Valuation Adjustment in a jump-diffusion setting'. Together they form a unique fingerprint.

Cite this