• Medientyp: Sonstige Veröffentlichung; Bericht; E-Book
  • Titel: RKHS regularization of singular local stochastic volatility McKean--Vlasov models
  • Beteiligte: Bayer, Christian [Verfasser:in]; Belomestny, Denis [Verfasser:in]; Butkovsky, Oleg [Verfasser:in]; Schoenmakers, John G. M. [Verfasser:in]
  • Erschienen: Weierstrass Institute for Applied Analysis and Stochastics publication server, 2022
  • Sprache: Englisch
  • DOI: https://doi.org/10.20347/WIAS.PREPRINT.2921
  • Schlagwörter: 65C30 ; 46E22 ; article ; 91G20
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: Motivated by the challenges related to the calibration of financial models, we consider the problem of solving numerically a singular McKean-Vlasov equation, which represents a singular local stochastic volatility model. Whilst such models are quite popular among practitioners, unfortunately, its well-posedness has not been fully understood yet and, in general, is possibly not guaranteed at all. We develop a novel regularization approach based on the reproducing kernel Hilbert space (RKHS) technique and show that the regularized model is well-posed. Furthermore, we prove propagation of chaos. We demonstrate numerically that a thus regularized model is able to perfectly replicate option prices due to typical local volatility models. Our results are also applicable to more general McKean--Vlasov equations.
  • Zugangsstatus: Freier Zugang