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

Mnacho Echenim; Emmanuel Gobet; Anne Claire Maurice

doi:10.1080/14697688.2023.2229022

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

Mnacho Echenim
, Emmanuel Gobet
, Anne Claire Maurice

Research output: Contribution to journal › Article › peer-review

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 ordinary one based on trade and mid-prices.

Original language	English
Pages (from-to)	1285-1304
Number of pages	20
Journal	Quantitative Finance
Volume	23
Issue number	9
DOIs	https://doi.org/10.1080/14697688.2023.2229022
Publication status	Published - 1 Jan 2023

Keywords

Bid-ask spread
Calibration
Crypto-assets
Data augmentation
Implied volatility
Missing data

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10.1080/14697688.2023.2229022

Cite this

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

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 ordinary one based on trade and mid-prices.",

keywords = "Bid-ask spread, Calibration, Crypto-assets, Data augmentation, Implied volatility, Missing data",

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N2 - 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 ordinary one based on trade and mid-prices.

AB - 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 ordinary one based on trade and mid-prices.

KW - Bid-ask spread

KW - Calibration

KW - Crypto-assets

KW - Data augmentation

KW - Implied volatility

KW - Missing data

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DO - 10.1080/14697688.2023.2229022

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JO - Quantitative Finance

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

Abstract

Keywords

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