Estimating Historical Volatility from High-Low Price Ranges with Parkinson’s Method

Summary

The document explains Parkinson’s historical volatility measure, which uses each period’s high and low prices to estimate return variability under a random-walk assumption. It defines the high-low return as the natural logarithm of the high divided by the low, and notes that the provider calculates daily values over several fixed lookback intervals. The displayed text refers to a return expression and a Parkinson formula but does not include the equations themselves.

The measure can help characterize intraday price distributions and market dynamics. The note also proposes comparing it with volatility estimated from periodically sampled prices to investigate mean-reversion tendencies and stop-loss placement. It gives no empirical comparison, calibration guidance, or performance evidence. Because the estimate relies on high and low observations and an assumed price process, the excerpt alone does not establish how well it works for any particular asset, sampling interval, or market regime.

Key ideas

• Parkinson volatility estimates variability using the high-low range within each observation period.
• The high-low return is the natural logarithm of the period high divided by its low.
• Comparisons with sampled-price volatility may help examine mean reversion and stop-loss distributions.
• The excerpt omits the actual estimator equations and gives no empirical validation.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.