Thoughts About Volatility

Back in September, I was testing the Connors RSI pullback strategy, and I posted an observation that the strategy performs best in a volatile market.  Volatility gives you the setups, and mean reversion gives you the profits.  If the market is in a steady uptrend, you’re better off with a momentum strategy.

The volatility measure I used in that post was STDEV(40).  This was a good predictor of when Connors is profitable, but it’s not a scaled measurement, so I coded up my own HV(40) indicator.  Below is a current chart of various volatility measures.  For comparison, all the periods are 20 days.

VolatilityThe main chart is SPX, where the width of the Bollinger band is a good measure of volatility.  The bottom chart is also based on standard deviation, but it is 1X STDEV scaled to a percentage.  Bollinger bands are typically 2X and not scaled.  That’s good for trading, but not so good for research.  I also annualized the indicator, to give comparable units.

This brings us to the middle chart, which has VIX and HV(20) + 4.  Why the plus 4?  I wanted to show both series with the same scale, and still have them line up.  You can see that HV tracks VIX pretty well in the flats and on inclines, as option prices rise in response to daily price swings, but not so well on declines.

Remember that VIX is supposed to be predicting the variability of SPX going forward.  If option traders are pricing risk correctly, you would expect to see VIX leading HV, especially given the 20 day lookback.  You would at least expect to see VIX track even with HV, and in both directions.  Here, it appears that traders tend to underestimate volatility when prices are rising.

At the June low, for example, VIX has spiked and then declines over the next month as prices rise.  But HV remains elevated and the Bollinger bands widen over this period.  You can see the same thing at the April low.  A likely cause of this anomaly would be the prices of protective puts, spiking and then quickly subsiding as the uptrend resumes.

Volatility2The chart above provides some circumstantial evidence for this idea.  The bottom panel is the two-day moving average of daily percentage loss.  That’s loss only, MAX(-∆P%, 0), not absolute change or signed change.  This suggests that VIX is, as they say, a “fear index.”

CometNext, I regressed VIX on HV(20).  You have probably seen this chart before, but I am not so sure VIX is the dependent variable.  Traders undoubtedly consider HV when pricing options, and then VIX is derived from option prices.  So, it’s a tautology.  That’s why the RSQR is 82.

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