Calculating Historical Volatility from Log Returns with Natenberg's Method

Summary

This short note defines historical volatility as the standard deviation of regularly sampled logarithmic price changes, following Sheldon Natenberg’s description in an options-pricing text. Its indicator recipe calculates close-to-close log returns, takes their standard deviation over 10 observations, and scales the result by the square root of 365 divided by 7. The output is labeled Natenberg’s Volatility.

The document supplies a formula but no market example, empirical comparison, or evidence about how well the measure forecasts future volatility. Its interpretation depends on the observation interval and the annualization convention: the 365/7 scaling assumes a particular conversion of the sampling period, so users should ensure it matches their data frequency. Historical volatility summarizes past price variation and does not by itself predict future movement or capture all features relevant to option pricing. The remaining text is privacy-policy boilerplate rather than material about the calculation.

Key ideas

• Historical volatility is calculated as the standard deviation of regularly sampled log price changes.
• The example uses close-to-close log returns and a 10-observation standard deviation window.
• The result is scaled by the square root of 365 divided by 7, so the scaling convention should match the data interval.
• The note provides a formula but no empirical evaluation or forecasting evidence.
• Historical volatility describes past variation and does not alone determine future volatility or option value.

Tags

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