Numerical approximations of McKean anticipative backward stochastic differential equations arising in initial margin requirements

Ankush Agarwal, S. Marco, E. Gobet, J. López-Salas, Fanny Noubiagain, Alexandre Zhou
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引用次数: 8

Abstract

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.
初始裕度要求下McKean预期倒向随机微分方程的数值近似
我们引入了一类新的具有McKean型依赖于解律的期望倒向随机微分方程,我们将其命名为MKABSDE。我们在一般框架下给出了存在唯一性结果,并对系数作了相对一般的正则性假设。我们展示了这种随机方程是如何在衍生品定价的现代范式中出现的,其中中央对手方(CCP)要求成员存入变化和初始保证金以覆盖其风险敞口。在初始保证金与合同价格的条件风险价值(CVaR)成正比的情况下,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的简单近似,我们使用不同的数值(确定性和蒙特卡罗)方法来求解。
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