Unbiasing and robustifying implied volatility calibration in a cryptocurrency market with large bid-ask spreads and missing quotes

Mnacho Echenim (), Emmanuel Gobet () and Anne-Claire Maurice ()
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Mnacho Echenim: LIG - Laboratoire d'Informatique de Grenoble - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, CAPP - Calculs algorithmes programmes et preuves - LIG - Laboratoire d'Informatique de Grenoble - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes
Emmanuel Gobet: CMAP - Centre de Mathématiques Appliquées de l'Ecole polytechnique - Inria - Institut National de Recherche en Informatique et en Automatique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique

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Abstract: We design a novel calibration procedure that is designed to handle the specific characteristics of options on cryptocurrency markets, namely large bid-ask spreads and the possibility of missing or incoherent prices in the considered data sets. We show that this calibration procedure is significantly more robust and accurate than the standard one based on trade and mid-prices.

Keywords: implied volatility; calibration; bid-ask spread; missing data; data augmentation (search for similar items in EconPapers)
Date: 2023-07-20
New Economics Papers: this item is included in nep-pay and nep-rmg
Note: View the original document on HAL open archive server: https://hal.science/hal-03715921v1
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Published in Quantitative Finance, 2023, 23 (9), pp.1285-1304. ⟨10.1080/14697688.2023.2229022⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03715921

DOI: 10.1080/14697688.2023.2229022

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