初始保证金要求中出现的麦肯预期后向随机微分方程的数值近似值

A. Agarwal, S. De Marco, E. Gobet, J. G. Lopez-Salas, F. Noubiagain, A. Zhou
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引用次数: 0

摘要

我们引入了一类新的预期后向随机微分方程,其解的规律与麦金类型有关,我们将其命名为 MKABSDE。我们展示了这类随机方程是如何在现代衍生品定价范式中出现的,在现代衍生品定价范式中,中央对手方(CCP)要求成员存入变动保证金和初始保证金以覆盖其风险敞口。在初始保证金与合约价格的条件风险值 (CVaR) 成比例的情况下,我们应用一般结果将价格定义为 MKABSDE 的解。我们提供了几种线性和非线性更简单的近似方法,并使用不同的数值(确定性和蒙特卡洛)方法进行求解。
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Numerical approximations of McKean Anticipative Backward Stochastic Differential Equations arising in Initial Margin requirements
We introduce a new class of anticipative backward stochastic differential equations with a dependence of McKean type on the law of the solution, that we name MKABSDE. We provide existence and uniqueness results in a general framework with relatively general regularity assumptions on the coefficients. We show how such stochastic equations arise within the modern paradigm of derivative pricing where a central counterparty (CCP) requires the members to deposit variation and initial margins to cover their exposure. In the case when the initial margin is proportional to the Conditional Value-at-Risk (CVaR) of the contract price, we apply our general result to define the price as a solution of a MKABSDE. We provide several linear and non-linear simpler approximations, which we solve using different numerical (deterministic and Monte-Carlo) methods.
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