XXVI Edition

14-15-16 December 2017"

Parameter uncertainty in CCP initial margin models

Wood Michael, Bank of England
Gurrola-Perez Pedro, Bank of England
Sarychev Andrei , Bank of England

Models play a fundamental role in financial risk management but their use invariably leads to model risk, which is the risk arising from the uncertainty in the choice of the model or of its parameters. We use a Bayesian approach to quantify parameter uncertainty in Value-at-Risk (VaR) models where conditional volatility is estimated using an exponentially weighted moving average (EWMA) process. These models are widely used in the industry and, in particular, are often at the base of the methodologies that many central counterparties use to estimate their margin requirements. Our results show that incorporating uncertainty around the estimation of the decay factor in an EWMA model can produce materially different risk estimates, and we identify situations where these estimates are less reliable. By investigating the sensitivity of parameter uncertainty to the data sample, we uncover some risks that are associated with the use of EWMA VaR specifications.

Area: Risk management

Keywords: EWMA models, model risk, parameter uncertainty, filtered historical simulation (FHS), Bayesian estimation, initial margin models

Paper file

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