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Frequently Asked Questions

Dr K VIX Volatility Model
I understand the Volatility Model has fail-safes to minimize drawdowns and capture profits. Please explain.

Volatility ETFs can be quite volatile, but with volatility can come good profits provided the risk element is controlled. The model is self-learning such that its fail-safes adjust to the price environment of a number of variables such as the VIX, 1x volatility ETFs, and general market.

During periods of amplified volatility, expect more than one try to hit a profitable trade. That said, amplified volatility increases the odds of hitting a 12-18% gain in UVXY in which case the profit taking rule kicks in.

Some examples of our fail-safes in action:

Buy signal on 8/27/15 = Instead of a loss of -10.2%, you would have been stopped out at a loss of -1.5%.

Sell signal on 8/31/15 = You would have closed out the trade on 9/1/15 for a two day gain of just over 20% using VXX, the 1x ETF. The 1x ETF VIXY would also work. Before the fail-safes were active, I remarked in an email update sent to members prior to the model's cash signal that taking at least partial profits when you have such huge profits in such a short time is wise. The model's fail-safes now account for this rare event where profits are huge in a matter of a few days or less. 

Sell signal on 9/4/15 = Instead of a loss of -5.3%, you would have been stopped out at a loss of -3.6%.

Similar improvements apply to the other signals prior to the time the fail-safes were put in place in October 2015. Since the signals can be fairly frequent, profits in backtests over just a few weeks can be substantial, even in a largely trendless year such as 2015. The key is in taking advantage of the volatile moves in volatility-based ETFs such as SVXY, VIXY, XIV, VXX, and UVXY. The fail-safes generally keep losses to a minimum while profitable signals are often far greater. That said, roughly one out of ten signals will result in a loss of greater than 5%, and on very rare occasion greater than 20%, so position size with care. Also, always remember that past performance is no guarantee of future results. 

Published: Oct 27 2015, Modified: Apr 18 2017