Estimating Cross-Model Correlations for CCR & XVA

The QuantMinds International event held on December 9, 2021 brought together leading quant practitioners and academics to focus on some of the key pillars of quant finance, including generating alpha through quant strategies, the IBOR transition, risk management, modelling, XVA pricing, algo trading, and more.

At the conference, Numerix’s Andrew McClelland, SVP of Quantitative Research, delivered a presentation titled Estimating Cross-Model Correlations for CCR & XVA. During the presentation, he addressed the following:

  • Defining cross model correlations and looking at how they would work in the PCA (principal components analysis) world and why cross model correlations are required to generate certain portfolio scenarios.
  • How these correlations are crucial in CCR & XVA risk settings and the ways parameter values can significantly affect pricing, risk capacity, etc.
  • A look at extending a PCA analogy for pricing models.
  • Explores an approach based on extracting factor innovations from historical data, inspired by PCA.
  • An approach that reduces simple regressions onto model-specific response profiles.

Watch this on-demand video presentation today.

Featured Speakers:

Andrew McClelland, Ph.D., Senior Vice President of Quantitative Research, Numerix
Andrew McClelland’s quantitative research at Numerix focuses on XVA pricing and hedging, generating counterparty credit risk metrics for structured products, and estimating risk model parameters via time-series estimation. He earned his PhD in finance at the Queensland University of Technology for a thesis on financial econometrics. He considered markets exhibiting crash feedback, option pricing for such markets, and parameter estimation for such markets using particle filtering methods. Dr. McClelland’s work has been published in the Journal of Banking and Finance, the Journal of Econometrics, and the Journal of Business and Economic Statistics.


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