Unbiasing and robustifying implied volatility calibration in a cryptocurrency market with large bid-ask spreads and missing quotes
针对加密货币期权市场的大买卖价差和缺失报价问题，设计了一种新的校准程序，比基于交易价和中间价的普通方法更稳健、更准确。
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.