Gaussian Process Regression for Derivative Portfolio Modeling and Application to CVA Computations

Author:

Crépey Stéphane,Dixon Matthew Francis

Publisher

Elsevier BV

Reference43 articles.

1. Supplementary file 2.

2. S0 stack gas gives (NH)S0

3. illustrates how to simulate the CVA-VaR of a portfolio using MC-GP. The implementation assumes a Black-Scholes model with a dynamic default intensity model given by Equation (31). The BS parameters and portfolio configuration are the same as the previous listing. Note, for conciseness, that this excerpt should only be run after running the previous excerpt. See Example-4-MC-GPA-BSprocess regression and Monte Carlo simulation (MC-GP) approach for fast evaluation of derivative portfolios, their sensitivities, and related counterparty credit risk metrics such as the EPE and the CVA. The approach is demonstrated by References Abbas;L A Turki;International Journal of Theoretical and Applied Finance,2018

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. KrigHedge: Gaussian Process Surrogates for Delta Hedging;Applied Mathematical Finance;2021-07-04

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