论文标题
在加密货币市场中，公正和可靠的隐含波动性校准，差价很大，报价很大
Unbiasing and robustifying implied volatility calibration in a cryptocurrency market with large bid-ask spreads and missing quotes
论文作者
论文摘要
我们设计了一个新颖的校准程序，旨在处理加密货币市场的选项的特定特征，即大型出价式差价以及在被考虑的数据集中丢失或不相互价格的可能性。我们表明，这种校准程序比基于贸易和中级标准的标准校准程序明显更强和准确。
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 standard one based on trade and mid-prices.
