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Main Authors: Kyakutwika, Nelson, Alfeus, Mesias, Schlögl, Erik
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.23409
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author Kyakutwika, Nelson
Alfeus, Mesias
Schlögl, Erik
author_facet Kyakutwika, Nelson
Alfeus, Mesias
Schlögl, Erik
contents We apply vector quantisation within mixed one- and two-factor Bergomi models to implement a fast and efficient approach for option pricing in these models. This allows us to calibrate such models to market data of VIX futures and options. Our numerical tests confirm the efficacy of vector quantisation, making calibration feasible over daily data covering several months. This permits us to evaluate the calibration accuracy and the stability of the calibrated parameters, and we provide a comprehensive assessment of the two models. Both models show excellent performance in fitting VIX derivatives, and their parameters show satisfactory stability over time.
format Preprint
id arxiv_https___arxiv_org_abs_2506_23409
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Pricing and Calibration of VIX Derivatives in Mixed Bergomi Models via Quantisation
Kyakutwika, Nelson
Alfeus, Mesias
Schlögl, Erik
Pricing of Securities
We apply vector quantisation within mixed one- and two-factor Bergomi models to implement a fast and efficient approach for option pricing in these models. This allows us to calibrate such models to market data of VIX futures and options. Our numerical tests confirm the efficacy of vector quantisation, making calibration feasible over daily data covering several months. This permits us to evaluate the calibration accuracy and the stability of the calibrated parameters, and we provide a comprehensive assessment of the two models. Both models show excellent performance in fitting VIX derivatives, and their parameters show satisfactory stability over time.
title Pricing and Calibration of VIX Derivatives in Mixed Bergomi Models via Quantisation
topic Pricing of Securities
url https://arxiv.org/abs/2506.23409