Skip to main navigation Skip to search Skip to main content

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

  • Centre national de la recherche scientifique
  • Kaiko – Quantitative Data

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

2 Citations (Scopus)

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 languageEnglish
Pages (from-to)1285-1304
Number of pages20
JournalQuantitative Finance
Volume23
Issue number9
DOIs
Publication statusPublished - 1 Jan 2023

Keywords

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

Fingerprint

Dive into the research topics of 'Unbiasing and robustifying implied volatility calibration in a cryptocurrency market with large bid-ask spreads and missing quotes'. Together they form a unique fingerprint.

Cite this