Volatility Estimator Lab
Close-to-close volatility misses intraday action. Compare 5 range-based estimators — Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang — on your own OHLC data.
OHLC Data
Minimum 20 days for stable estimates. Comma separated.
Estimator Comparison (Annualized %)
Yang-Zhang (Best)
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Close-to-Close
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Efficiency Gain
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Frequently Asked Questions
Why not just use close-to-close?
Close-to-close ignores the entire trading day — a stock swinging ±5% intraday but closing flat shows zero volatility. Range estimators capture that hidden movement.
Which estimator is best?
Yang-Zhang: most efficient (up to 14x vs close-to-close), handles overnight jumps and drift. Garman-Klass is the classic 7x-efficient choice; Parkinson simplest.
What does efficiency mean?
How much data you need for the same accuracy. Yang-Zhang needs ~1/14th the days of close-to-close for equal precision — crucial with limited history.
Disclaimer: Standard academic estimators for education. Annualization assumes 252 trading days. Results depend on data quality — verify OHLC accuracy.