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

被引：0

作者：

Echenim, Mnacho ^{[1
]}

Gobet, Emmanuel ^{[2
]}

Maurice, Anne-Claire ^{[3
]}

机构：

[1] Domaine Univ, Lab Informat Grenoble LIG, CNRS, Grenoble INP,UGA, 700 Ave Cent, F-38401 Saint Martin Heres, France

[2] Inst Polytech Paris, Ecole Polytech, Ctr Math Appl CMAP, CNRS, Route Saclay, F-91128 Palaiseau, France

[3] Kaiko Quantitat Data, 2 Rue Choiseul, F-75002 Paris, France

来源：

QUANTITATIVE FINANCE | 2023年 / 23卷 / 09期

关键词：

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

D O I：

10.1080/14697688.2023.2229022

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页码：1285 / 1304

页数：20

共 40 条

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