Counterparty Credit Risk and Wrong Way Risk; a Least Square Montecarlo Approach

2017 ◽  
Author(s):  
Peter Joe Silva ◽  
Hernan Reisin ◽  
Manuel Maurette
Keyword(s):  
Credit Risk ◽  
Least Square ◽  
Counterparty Credit Risk

scholarly journals Calculation of Credit Valuation Adjustment Based on Least Square Monte Carlo Methods

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Qian Liu
Keyword(s):  
Monte Carlo ◽  
Credit Risk ◽  
Financial Markets ◽  
Financial Institutions ◽  
Least Square ◽  
Copula Functions ◽  
Default Intensity ◽  
Interest Rate Swaps ◽  
Counterparty Credit Risk ◽  
Credit Valuation Adjustment

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced mathematically. We examine this issue using interest rate swaps. This largely traded financial product allows us to well identify the risk profiles of both institutions and their counterparties. Concretely, Hull-White model for rate and mean-reverting model for default intensity have proven to be in correspondence with the reality and to be well suited for financial institutions. Besides, we find that least square Monte Carlo method is quite efficient in the calculation of credit valuation adjustment (CVA, for short) as it avoids the redundant step to generate inner scenarios. As a result, it accelerates the convergence speed of the CVA estimators. In the second part, we propose a new method to calculate bilateral CVA to avoid double counting in the existing bibliographies, where several copula functions are adopted to describe the dependence of two first to default times.

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