We propose a new unbiased robust volatility estimator based on extreme values of asset prices. We show that the proposed Add Extreme Value Robust Volatility Estimator (AEVRVE) is unbiased and is 2–3 times more efficient relative to the Classical Robust Volatility Estimator (CRVE). We put forth a novel procedure to remove the downward bias present in the data even without increasing the number of steps in the stock price path. We perform Monte Carlo simulation experiments to show the properties of unbiasedness and efficiency. The proposed estimator remains exactly unbiased relative to the standard robust volatility estimator in the empirical data based on global stock indices namely CAC 40, DOW, IBOVESPA, NIKKEI, S&P 500 and SET 50.

中文翻译：

---

一种使用资产价格极值的新的无偏可加稳健波动率估计

我们提出了一种基于资产价格极值的新的无偏稳健波动率估计器。我们表明，所提出的添加极值稳健波动率估计器 (AEVRVE) 是无偏的，并且相对于经典稳健波动率估计器 (CRVE) 的效率高 2-3 倍。我们提出了一种新颖的程序，即使不增加股价路径中的步骤数，也可以消除数据中存在的向下偏差。我们进行蒙特卡罗模拟实验来展示无偏性和效率的特性。相对于基于全球股票指数 CAC 40、DOW、IBOVESPA、NIKKEI、S&P 500 和 SET 50 的经验数据中的标准稳健波动率估计量，建议的估计量保持完全无偏。