MVA：通过复制和回归进行初始保证金估值调整
MVA: Initial Margin Valuation Adjustment by Replication and Regression
摘要：
初始保证金要求正成为衍生品市场越来越普遍的特征。然而，虽然通过估值调整确定了抵押（Piterbarg 2010，Piterbarg 2012）、无担保融资成本（FVA）下的交易对手风险（Burgard 2011，Burgard 2011，Burgard 2013）和存在监管资本（KVA）（Green 2014）下的衍生品估值，但迄今尚未考虑初始保证金。本文进一步扩展了（Burgard 2013 a）的半复制框架，该框架后来被（Green 2014）扩展，以涵盖初始保证金的成本，从而导致保证金估值调整（MVA）。初始保证金要求通常通过使用VAR或CVAR模型生成。给定MVA的形式作为对预期初始裕度曲线的积分，如果使用蛮力计算，则这将导致过多的计算成本。因此，我们还提出了一种计算效率高的方法来计算MVA，通过使用回归技术，Longstaff-Schwartz增强压缩（LSAC）。
英文摘要：
Initial margin requirements are becoming an increasingly common feature of derivative markets. However, while the valuation of derivatives under collateralisation (Piterbarg 2010, Piterbarg2012), under counterparty risk with unsecured funding costs (FVA) (Burgard2011, Burgard2011, Burgard2013) and in the presence of regulatory capital (KVA) (Green2014) are established through valuation adjustments, hitherto initial margin has not been considered. This paper further extends the semi-replication framework of (Burgard2013a), itself later extended by (Green2014), to cover the cost of initial margin, leading to Margin Valuation Adjustment (MVA). Initial margin requirements are typically generated through the use of VAR or CVAR models. Given the form of MVA as an integral over the expected initial margin profile this would lead to excessive computational costs if a brute force calculation were to be used. Hence we also propose a computationally efficient approach to the calculation of MVA through the use of regression techniques, Longstaff-Schwartz Augmented Compression (LSAC).
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