Capturing Initial Margin in Counterparty Risk Calculations

Journal of Risk Management in Financial Institutions, Vol. 10, 2017, pp. 118-129

Posted: 6 Jul 2016 Last revised: 31 Mar 2017

Date Written: March 30, 2017

Abstract

This paper compares a range of alternative approaches to incorporate Initial Margins (IMs) in the modelling of counterparty credit risk exposures. With the rise of Central Counterparties to clear OTC derivatives and the incoming legislation requiring bilateral margining for uncleared derivatives between financial counterparties the reflection of IMs becomes an essential model component that drives exposures, associated regulatory capital requirements and valuation adjustments such as CVA and MVA. The influence of the modelling choices is explored by means of typical derivatives portfolios. For the actual estimation of a path-dependent (“stochastic”) IM through time the use of quantile regression is suggested as an econometrically reliable approximation. Banks’ internal counterparty risk models will likely exhibit a basis vis-à-vis the actual IM mechanisms in practice (for example, owing to different risk factor representations and/or calibrations). In this context, the paper suggests that a simplified representation in the form of a “dynamic IM” can approximate most of the quantities of interest to a reasonable degree.

Keywords: Initial Margin, Clearing, Bilateral Margining, Counterparty Risk, IMM

JEL Classification: G10, G18

Suggested Citation

Moran, Lee and Wilkens, Sascha, Capturing Initial Margin in Counterparty Risk Calculations (March 30, 2017). Journal of Risk Management in Financial Institutions, Vol. 10, 2017, pp. 118-129, Available at SSRN: https://ssrn.com/abstract=2803499 or http://dx.doi.org/10.2139/ssrn.2803499

Lee Moran

BNP Paribas, London ( email )

10 Harewood Avenue
London, NW1 6AA
United Kingdom

Sascha Wilkens (Contact Author)

Independent

No Address Available

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
1,724
PlumX Metrics