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Efficient estimation of sensitivities for counterparty credit risk with the finite difference Monte Carlo method

机译:有限差分蒙特卡罗方法有效估计交易对手信用风险的敏感性

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According to Basel III, financial institutions have to charge a credit valuation adjustment (CVA) to account for a possible counterparty default. Calculating this measure and its sensitivities is one of the biggest challenges in risk management. Here, we introduce an efficient method for the estimation of CVA and its sensitivities for a portfolio of financial derivatives. We use the finite difference Monte Carlo (FDMC) method to measure exposure profiles and consider the computationally challenging case of foreign exchange barrier options in the context of the Black-Scholes as well as the Heston stochastic volatility model, with and without stochastic domestic interest rate, for a wide range of parameters. In the case of a fixed domestic interest rate, our results show that FDMC is an accurate method compared with the semi-analytic COS method and, advantageously, can compute multiple options on one grid. In the more general case of a stochastic domestic interest rate, we show that we can accurately compute exposures of discontinuous one-touch options by using a linear interpolation technique as well as sensitivities with respect to initial interest rate and variance. This paves the way for real portfolio level risk analysis.
机译:根据巴塞尔协议III,金融机构必须收取信用评估调整(CVA),以应对可能的交易对手违约。计算该度量及其敏感性是风险管理中的最大挑战之一。在这里,我们介绍了一种有效的方法来估算CVA及其对金融衍生产品组合的敏感性。我们使用有限差分蒙特卡洛(FDMC)方法来测量风险敞口,并在布莱克-斯科尔斯以及Heston随机波动率模型(有或没有国内利率)的背景下考虑外汇障碍期权在计算方面的挑战性情况,适用于各种参数。在固定国内利率的情况下,我们的结果表明,与半解析COS方法相比,FDMC是一种准确的方法,并且可以在一个网格上计算多个选项。在更一般的国内利率随机情况下,我们表明,通过使用线性插值技术以及对初始利率和方差的敏感性,我们可以准确地计算出不连续的一键式期权的敞口。这为真实的投资组合级风险分析铺平了道路。

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