In the attached image I have a plot of the rolling correlation of 90-day historic volatility (using the Garman Klass estimator based on Sinclair's Volatility Trading) of JPM v. the S&P. As can be clearly seen, the correlation is generally somewhere near 1. However, there are times when the correlation degrades significantly (witness summer 2011). I'm curious of two things:1. Trading strategies that may be implemented to exploit the breakdown using listed equity options (assuming one expects the correlation to revert back near the historic norm, in this case near 1)2. How one might use the information to help predict future volatility

Get real, take a look on VIX. Both cases are jumps."the correlation to revert back near the historic norm" sounds to me like "vol to revert to its lower twenties".

The chart would be kinda interesting if valid, but I suspect it's not. Looking at the rolling 90-day correlation of Log (H/L), for example, never shows anything that close to 1.

Skull, sure volatility jumped. JPM is in the S&P500 so one would expect the volatility of both S&P and JPM to jump nearly together. However, they diverged significantly which makes me think it is more than just overall volatility increase. Further, VIX measures implied volatility while the chart above is the correlation of realized volatility.Alan, I used the Garman Klass estimator defined aswith prices adjusted for dividends and splits

Here's what I get when I attempt to reproduce your chart.This is the rolling 90-day correlation of the GK statistic you posted, using JPM and SP500:Raw data from Jan 1, 2008 - Apr 25, 2012; first correlation point 90 days from start of raw data: See my problem with your chart?