Multi-curve Cheyette-style models with lower bounds on tenor basis spreads

This article presents a general multi-curve Cheyette-style model that allows precise control over tenor basis spreads. The specification was proposed by Grbac and Runggaldier, but a solution for the no-arbitrage drift function has remained elusive. Drs. Michael Konikov and Andrew McClelland of Numerix recover the drift function via an ansatz and proceed to fully develop the model, providing an example with a level-dependent volatility function to secure lower bounds on spreads.

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Author: Dr. Michael Konikov, Senior Vice President and Head of Quantitative Development, Numerix

Dr. Michael Konikov is a Senior Vice President and Head of Quantitative Development at Numerix, where he manages a team responsible for the development and delivery of models in Numerix software.  Previously, he worked at Citigroup, Barclays, and Bloomberg in quantitative research and desk quant roles.  He completed his PhD in mathematical finance at the University of Maryland College Park, concentrating, in particular, on the application of pure jump processes to option pricing.  Dr. Konikov's publications cover diverse asset classes ranging from equity to interest rates and credit. He has been published four technical articles in RISK Magazine on interest rate modeling, SABR model, and algorithmic differentiation for PV and XVA Greeks. Dr. Konikov is also co-author of the upcoming book Alexandre Antonov, Michael Konikov, Michael Spector “Modern SABR Analytics,” Springer (2019).

Author: Andrew McClelland, Ph.D., Senior Vice President, Quantitative Research at Numerix

Andrew McClelland's work at Numerix focuses on counterparty credit risk issues including valuation adjustments and counterparty exposure production for structured products. He also works on numerical methods for efficient production of risk profiles under real-world measures.
Dr. McClelland received his Ph.D. in finance at the Queensland University of Technology in financial econometrics. His research involved markets exhibiting crash feedback, option pricing, and parameter estimation using particle filtering methods. His 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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