A Scary Groundhog Tale

A Scary Groundhog TaleScary Groundhog  

It seems appropriate to write this tale on October 31, 2019 in celebration of yet another Halloween. But our tale begins on Groundhog Day, February 2, 2018.  It was on that fateful Friday that VIX futures started their steep rise which culminated after the stock market closed on Monday February 5th with what was called “Volmageddon” or volatility Armageddon.  During this particular 2-day period, the index that tracks inverse volatility, which represented and still represents a 15% allocation of the Sera Capital Optimism Index, lost 14% and 96% respectively.  The 96% drop was the single largest one day drop in the history of the index and so right out of the gate, we were down almost 15%.

Our launch timing could not have been worse. However, if looked through a different prism, a proof of concept prism, our timing could not have been better since yesterday the Sera Capital Optimism Index went to new all-time highs closing at 296.25.  How could this have happened?  How can one component of your index get virtually wiped out and yet less than 21 months later be at new all-time highs?  The answer is found by looking at the trading rules inside the index and by understanding how inverse volatility moves over time.

A quick reminder. The Sera Capital Optimism Index has a 15% allocation to inverse volatility and an 85% allocation to 7-10-year US Government Bonds that gets rebalanced every month.  It could not possibly be easier to understand. The ability for the index to make its comeback is because at the end of February 2018, the trading rules called for re-establishing the original allocation back to 15% inverse volatility and 85% bonds.  This obviously means the selling of bonds and the purchase of inverse volatility at that time.  At the end of March 2018, you would rebalance again as you would at the end of April 2018 and you keep doing this every month.  This explains the trading rules.  But what is it about inverse volatility’s movements that make it so powerful as a complement to bonds?

To understand how inverse volatility works, one must recognize that it is positively correlated to the S&P 500.  So typically, if the S&P 500 were to drop, then the inverse volatility index drops.  If the S&P 500 were to rise, then inverse volatility would also rise.  However, inverse volatility has a feature that the S&P 500 does not have.  If one were to invest in an index fund that tracks the S&P 500 then generally, the only way to benefit from this investment is when the S&P 500 rises.  If it drops you lose and if it stays still you don’t make anything.  Inverse volatility is different.  It also makes money while the S&P 500 rises, also loses when it drops but it differs because it makes money when the S&P 500 stays still.  So inverse volatility can make money in two types of stock market conditions while the S&P 500 only makes money during rising periods.  This is a glaring advantage.  But what’s the disadvantage?  If you answered that inverse volatility is about 4 times more volatile than the S&P 500 and will always be subject to large quick losses then you would be correct.  These large quick losses make inverse volatility a poor stand-alone long term buy and hold investment but an incredible part of a portfolio when coupled with bonds.

As many of our readers know, the Sera Capital Optimism Index is designed to outperform a traditional 60/40 portfolio over multiple stock market cycles and do it with less risk as measured by maximum drawdown.  An analysis of the past shows that while the events surrounding Groundhog Day in 2018 were dramatic because the large losses occurred over a 2-day period, losses in the index in excess of 75% happened multiple times in the past. The difference was that instead of 2 days, they transpired over 6-8 weeks.  Simply stated, history shows that losses of the magnitude experienced 21 months ago were not out of the norm nor is rapid recovery.

So, what makes inverse volatility such a powerful complement to bonds? The answer is the frequency and amplitude of inverse volatility vs the S&P 500.  We tested the period from January 3, 2007 through September 2019 to measure frequency and amplitude.  We used daily data and tested the inverse volatility index symbol SPVXSPIT vs the ETF SPY.  Our test was simple, we were trying to understand the number of cycles, or bull and bear cycles of each.

The specifics of our test were as follow, if the index experiences a 10% drop for example, then the breakeven point to recover is 11.11% due to the mathematics of recovery. If it were to drop again the next day, we still require an 11.11% gain from the new low to call it a complete cycle. The following table shows how inverse volatility cycles vs the S&P 500.

A Cycle Analysis of Inverse Volatility vs the S&P 500

Initial Required Inverse
Drop Recovery Volatility S&P 500 Ratio
1.00% 1.01% 617 294 2.10
2.00% 2.04% 467 146 3.20
3.00% 3.09% 366 95 3.85
4.00% 4.17% 296 61 4.85
5.00% 5.26% 235 48 4.90
6.00% 6.38% 184 35 5.26
7.00% 7.53% 160 24 6.67
8.00% 8.70% 138 17 8.12
9.00% 9.89% 119 14 8.50
10.00% 11.11% 99 11 9.00
11.00% 12.36% 89 9 9.89
12.00% 13.64% 77 8 9.63
13.00% 14.94% 72 7 10.29
14.00% 16.28% 65 6 10.83
15.00% 17.65% 62 6 10.33
16.00% 19.05% 58 5 11.60
17.00% 20.48% 50 4 12.50
18.00% 21.95% 46 4 11.50
19.00% 23.46% 38 3 12.67
20.00% 25.00% 34 1 34.00

 

An examination of the above table clearly shows that inverse volatility experiences more bull and bear cycles than the S&P 500.  This significantly increased frequency suggests that there would be a better rules design than the one we use which is as basic as it gets.  Nevertheless, our design, the Sera Capital Optimism Index, is not intended to optimize a set of trading rules but to show the power of simplicity by making the rules so transparent.

There is much more to learn and to understand about why we chose to only allocate only 15% to inverse volatility but the essence is twofold.  Inverse volatility is roughly 4 times more volatile on a month to month basis than the S&P 500 and since we wanted to design an index that used volatility as an investment and was benchmarked to a traditional 60/40 stock/bond portfolio then 60% divided by 4 equals 15%.  The uses of including inverse volatility or selling volatility as part of one’s portfolio are only limited by your imagination.

Happy Halloween!

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