Dynamic Initial Margin Estimation Based on Quantiles of Johnson Distributions

24 Pages Posted: 1 Dec 2022

See all articles by Thomas McWalter

Thomas McWalter

University of Cape Town (UCT); University of Johannesburg

Joerg Kienitz

University of Cape Town (UCT) - The African Institute of Financial Markets and Risk Management

Nikolai Nowaczyk

Independent

Ralph Rudd

University of Cape Town (UCT) - The African Institute of Financial Markets and Risk Management

Sarp Kaya Acar

Quaternion Risk Management

Multiple version iconThere are 2 versions of this paper

Date Written: July 12, 2022

Abstract

The estimation of dynamic initial margin (DIM) is a challenging problem. We describe an accurate new approach using Johnson-type distributions, which are fitted to conditional moments, estimated using a least-squares Monte Carlo simulation (the Johnson least-squares Monte Carlo (JLSMC) algorithm). We compare the JLSMC DIM estimates with those computed using an accurate nested Monte Carlo simulation as a benchmark, and with another method that assumes portfolio changes are Gaussian. The comparisons reveal that the JLSMC algorithm is accurate and efficient, producing results that are comparable with nested Monte Carlo with an order of magnitude less computational effort. We provide illustrative examples using the Hull–White and Heston models for different derivatives and portfolios. A further advantage of our new approach is that it relies only on the readily available data that is needed for any exposure or value adjustment calculation.

Keywords: dynamic initial margin (DIM), margin value adjustment (MVA), quantiles, Johnson distributions, least squares Monte Carlo

Suggested Citation

McWalter, Thomas and Kienitz, Joerg and Nowaczyk, Nikolai and Rudd, Ralph and Acar, Sarp Kaya, Dynamic Initial Margin Estimation Based on Quantiles of Johnson Distributions (July 12, 2022). Journal of Credit Risk, Vol. 18, No. 4, 2022, Available at SSRN: https://ssrn.com/abstract=4289728

Thomas McWalter (Contact Author)

University of Cape Town (UCT) ( email )

Private Bag X3
Rondebosch, Western Cape 7701
South Africa

University of Johannesburg ( email )

PO Box 524
Auckland Park
Johannesburg, Gauteng 2006
South Africa

Joerg Kienitz

University of Cape Town (UCT) - The African Institute of Financial Markets and Risk Management

Nikolai Nowaczyk

Independent

Ralph Rudd

University of Cape Town (UCT) - The African Institute of Financial Markets and Risk Management ( email )

Leslie Commerce Building
Rondebosch
Cape Town, Western Cape 7700
South Africa

Sarp Kaya Acar

Quaternion Risk Management ( email )

54 Fitzwilliam Square North
Dublin, D02X308
Ireland

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