Margin Value Adjustment for CCPs with Q-Simulated Initial Margin
Roberto Daluiso, Giorgio Facchinetti and Massimo Morini
Introduction
Variation and Initial Margin in the ISDA Credit Support Annex
Variation and Initial Margin Required by Central Counterparty Clearing Houses
Margin Requirements for Over-the-Counter Derivatives: A Supervisory Perspective
The Emergence and Concepts of the SIMM Methodology
The ISDA Standard Initial Margin Model Backtesting Framework
The Impact of Margin on Regulatory Capital
XVA for Margined Trading Positions
Modelling Forward Initial Margin Requirements for Bilateral Trading
Forward Valuation of Initial Margin in Exposure and Funding Calculations
Margin Value Adjustment for CCPs with Q-Simulated Initial Margin
Bilateral Exposure in the Presence of Margin
Central Counterparty Risk
Robust Computation of XVA Metrics for Central Counterparty Clearing Houses
Efficient Initial Margin Optimisation
Procyclicality in Sensitivity-Based Margin Requirements
Systemic Risks in Central Counterparty Clearing House Networks
10.1 INTRODUCTION
The initial margin (IM) is an amount of collateral posted to cover possible swings of the net present value of a deal between the last date of the variation margin (VM) update and the default closeout. At least from June 2013, when central clearing became mandatory for a number of derivatives, managing IM has been a relevant issue for banks, since IM is always required when dealing with central counterparty clearing houses (CCPs). By 2016 it had also become a requirement in bilateral deals. Since IM is an additional amount of collateral on top of the standard VM that tracks the net present value of a deal, and considering that there are no or limited possibilities of rehypothecation for IM, it generates an extra funding cost. Computing this funding cost associated with IM requirements, at times called margin value adjustment (MVA), presents both conceptual and computational challenges. In this chapter we propose a method that, unlike some other proposals in the literature, does not involve nested Monte Carlo simulations under different probability measures, but involves only risk-adjusted simulation without approximations. We also show how to achieve
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