Parkinson Estimator

What is the Parkinson Estimator?

The Parkinson estimator computes historical volatility from the high-low range: the per-bar variance estimate is the squared natural log of high over low, divided by four times the natural log of two, then averaged over a window and annualized. Physicist Michael Parkinson published it in 1980. The intuition is that a bar's extremes sample the whole path traveled rather than one endpoint, so under idealized assumptions (zero drift, continuous trading) it is roughly five times more efficient than close-to-close historical volatility: a much shorter window achieves the same precision.

Its blind spots are its inputs. Overnight gaps never appear inside a bar's span, so gap-prone assets are understated; there is no mean adjustment, so strong drift widens ranges and bleeds trend into the estimate; and discretely traded highs and lows sit inside the true continuous extremes, a mild downward bias in thin markets. The Garman-Klass estimator adds open/close information, and the Yang-Zhang estimator handles gaps and drift together.

How traders use it

• As a fast-settling volatility input for bands, stop distances, and sizing when the lookback must stay short: the range is informative enough that modest windows give usable readings.
• As a gap diagnostic next to close-to-close volatility: Parkinson well below it says movement arrives between sessions; well above it says sessions are churny and wide-ranged even when closes land quietly.
• As one leg of estimator composites: OHLC volatility studies often report Parkinson beside Garman-Klass and Rogers-Satchell so the spreads between them can be inspected.