An automatic bias correction procedure for volatility estimation using extreme values of asset prices

We propose and implement an empirical automatic bias correction (ABC) procedure for correcting the downward bias in the volatility estimators that utilize extreme value of asset prices. The bias originates from the random walk effect. The proposed estimator does not require knowledge of N, the number of steps. We find that the procedure works well in real life data.